JP4402099B2 - Point information search device, point information search method, and program - Google Patents

Description

  The present invention relates to an apparatus that is provided in a mobile terminal such as a car navigation system and that provides information to a user by searching for information related to a spot, and more particularly, to an apparatus that provides information related to a user's purpose.

  Conventionally, a technique for searching for a destination by inputting a keyword in a mobile terminal such as a car navigation system (hereinafter also simply referred to as “car navigation”) has been proposed (for example, see Patent Document 1).

FIG. 82 is a block diagram showing a configuration of a navigation device in the prior art described in Patent Document 1. In FIG. The map data storage device 4 is a device that stores a map, and stores the names and genres of facilities. The remote control sensor 10 is a sensor that receives an input from the remote control 11 and acquires a genre and the like from the remote control 11 when a user searches for a destination. Based on the acquired genre and the like, the control circuit 2 searches for a corresponding destination and displays information obtained by the search on the display device 7.
JP 2004-132984 A

  However, the above-described conventional technique has a problem that there is only one destination to be finally searched, and information cannot be provided in consideration of a plurality of destinations. When the user moves, the user may move to fulfill a plurality of acts and purposes. For example, after bowling at a bowling alley, considering a meal at a restaurant, a facility may be searched. However, the destination search in the above prior art does not consider these multiple purposes. For this reason, a bowling alley is searched first, and then a restaurant is searched. Therefore, it is not possible to perform a search in consideration of the positional relationship of these destinations. Therefore, the conventional technology has a problem that the user cannot always search for a suitable destination.

  The user goes to a destination and does not always have one action, but may be more than one. At that time, in the case of movement by car, for example, it is repeated that a plurality of stores capable of performing the act are sequentially moved and parking is performed again for each store. The repetition is very cumbersome.

  Therefore, the present invention has been made in view of such a problem, and is a point information search that can search and provide information on points that can optimally fulfill a plurality of purposes related to the behavior desired by the user. An object is to provide a device or the like.

In order to achieve the above object, a point information search device of the present invention is provided in a mobile terminal, and is a point information search device for searching for information related to a point and providing it to a user, wherein the position of the mobile terminal is determined. Position information acquisition means for acquiring position information to be indicated, point information storage means for storing point information in which position information of a point is associated with attribute information regarding an action that can be performed at the point classification or the point For a purpose that the user desires, a multi-purpose acquisition unit that acquires information for specifying a plurality of purposes, and a point indicated by position information included in the point information from the point information stored in the point information storage unit; An attribute corresponding to a plurality of purposes acquired by the multi-purpose acquiring unit and having a predetermined fixed relationship with the position indicated by the position information acquired by the position information acquiring unit Comprising search means for searching for point information including the broadcast, and information providing means for providing information related to the point indicated by the position information included in the retrieved point information by said retrieval means, said retrieval means further said search means In the case where the number of pieces of point information searched in is less than a predetermined number, the position information is included in the point information from the position condition correcting unit for correcting the fixed relationship and the point information stored in the point information storing unit. The position indicated by the position information and the position indicated by the position information acquired by the position information acquisition means are in a fixed relationship corrected by the position condition correction means, and the plurality of acquired by the multi-purpose acquisition means Re-searching means for searching for point information including attribute information corresponding to the purpose of the point information, the searching means from the point information stored in the point information storage means The point indicated by the position information included and the position indicated by the position information acquired by the position information acquisition unit have a predetermined fixed relationship, and among the plurality of purposes acquired by the multi-purpose acquisition unit After searching for point information including attribute information corresponding to one of the points, including position information indicating a point having a fixed relationship with the point indicated by the position information included in the searched point information, and the plurality of purposes The point information including the attribute information corresponding to the remaining purpose is searched from the point information stored in the point information storage unit, and the information providing unit includes the plurality of purposes searched by the search unit. JP that you provide information related to the point indicated by the position information included in the point information including the attribute information corresponding to the purpose of the point information including the attribute information corresponding to one remaining ones of said plurality of objects It is a sign.
The point information search device of the present invention is a point information search device provided in a mobile terminal for searching for information related to a point and providing it to a user, and acquires position information indicating the position of the mobile terminal. Location information acquisition means, multipurpose acquisition means for acquiring information for specifying a plurality of purposes, and actions that can be performed at the location of the location or the location or the location A point information storage unit that stores point information associated with attribute information, a point indicated by the position information included in the point information, and the position information acquisition unit from the point information stored in the point information storage unit The point information including attribute information corresponding to a plurality of purposes acquired by the multi-purpose acquisition unit has a predetermined relationship with the position indicated by the acquired position information. Search means for searching, and information providing means for providing information relating to the location indicated by the location information included in the location information searched by the search means, wherein the multipurpose acquisition means further includes a movement history of the mobile terminal. A movement history accumulating unit for accumulating information, a movement history accumulated in the movement history accumulating unit, and position information acquired by the position information acquiring unit. And a purpose extracting unit, wherein the multi-purpose acquiring unit acquires information for specifying a plurality of purposes including the trust purpose specified by the trust purpose extracting unit.

  The present invention can be realized not only as such a point information search apparatus, but also as a point information search method using a processing means constituting the point information search apparatus as a step, or executing the method on a computer. It can also be realized as a program to be executed, or as a recording medium such as a computer-readable CD-ROM in which the program is recorded.

  According to the present invention, a plurality of inputted actions and classifications, that is, points that meet a plurality of purposes and that can efficiently perform those actions are searched, Information about the point is provided.

  Therefore, when performing an action that fulfills a plurality of purposes, it is possible to avoid an inefficient action of sequentially moving around a plurality of destinations that are distant from each other. The practical value of the present invention is extremely high.

  When searching for location information, the user can perform multiple purposes in one go, so that the classification information of locations such as “restaurants” and “play facilities”, “meal”, A plurality of actions to be performed at a point such as “boring” may be input, and a point suitable for them may be searched. However, conventionally, when a point that satisfies the input information is not searched, only the information that there is no search result is presented to the user. Further, after confirming the information “no search result”, the user needs to input the search condition again. Further, even if there are search results that satisfy each condition, the information is only provided independently, and the desired action, the classification of the facility to be visited, etc. (hereinafter referred to as “purpose”). ) Is not proposed for a combination of points that can efficiently (or visit).

  Therefore, in the present embodiment, when information on the classification or action of points regarding a plurality of purposes is input, the optimal point that satisfies both of the search conditions (or all of the plurality of search information) Search for and provide information about the location. If such a point does not exist, a plurality of purposes input by the user can be efficiently performed by correcting the condition regarding the position of the point from the point information satisfying each search condition. We are going to provide information about the best points where we can.

(Embodiment 1)
First, the point information search apparatus in Embodiment 1 of this invention is demonstrated. In the present embodiment, the basic concept of the point information retrieval apparatus according to the present invention will be described, and in the following second to fourth embodiments, detailed description will be given using specific examples.

  FIG. 1 is a block diagram showing a configuration of a spot information search apparatus 200 according to Embodiment 1 of the present invention. This point information search device 200 is a device provided in a mobile terminal such as a car navigation system, and is a device that searches for information related to a point and provides it to a user. The position information acquisition unit acquires position information indicating the position of the mobile terminal. 210, a point information storage unit 220 that stores point information that associates position information with attribute information about an action that can be performed at a point classification or point, and a purpose that the user desires, Acquired by the location information acquisition unit 210 and the location indicated by the location information included in the location information from the location information stored in the location information storage unit 220 and the multi-purpose acquisition unit 230 that acquires information specifying a plurality of purposes. Search for point information that has a predetermined relationship with the position indicated by the position information and includes attribute information corresponding to a plurality of purposes acquired by the multi-purpose acquisition unit 230 Provided that a search unit 240, and an information providing unit 250 for providing information related to the point indicated by the position information included in the point information searched by the search unit 240.

  Here, as a specific example of the fixed relationship, for example, the search unit 240 is acquired from the point information stored in the point information storage unit 220 by the location indicated by the location information included in the location information and the location information acquisition unit 210. The point information including the attribute information corresponding to a plurality of purposes acquired by the multi-purpose acquisition unit 230 is searched for within a predetermined distance range. As a result, when the points necessary to achieve a plurality of purposes are in a certain relationship, for example, within a certain distance, information on the points is provided, so that the user fulfills the plurality of purposes. When performing an action, it is possible to avoid an inefficient action of sequentially moving around a plurality of destinations at a distance.

  The search unit 240 further includes a position condition correction unit 241, a re-search unit 242, and a distance calculation unit 243 as additional functions.

  The position condition correction unit 241 is a processing unit that corrects the predetermined relationship when the number of spot information searched by the search unit 240 is less than a predetermined number.

  The re-search unit 242 is a position condition correction unit based on the point information stored in the point information storage unit 220 and the position indicated by the position information included in the point information and the position indicated by the position information acquired by the position information acquisition unit 210. The processing unit searches for point information that includes the attribute information corresponding to the plurality of purposes acquired by the multi-purpose acquisition unit 230 in the fixed relationship corrected by the H.241.

  For example, by correcting the position condition, the search unit 240 acquires the location indicated by the location information included in the location information and the location information acquired by the location information acquisition unit 210 from the location information stored in the location information storage unit 220. And the position indicated by is searched after searching for point information including attribute information corresponding to one of a plurality of purposes acquired by the multi-purpose acquisition unit 230. The location information storage unit 220 includes location information that includes location information that indicates a location that has a certain relationship with the location indicated by the location information included in the location information, and that includes attribute information that corresponds to the remaining purpose among a plurality of purposes. Search from the point information stored in. Then, the information providing unit 250 includes point information including attribute information corresponding to one of the plurality of purposes searched by the searching unit 240 and point information including attribute information corresponding to the remaining purpose among the plurality of purposes. The information regarding the point indicated by the position information included in is provided.

  As a result, even when the points convenient for achieving multiple purposes are not concentrated in one place, the points convenient for achieving each purpose have a certain relationship, for example, a certain distance. When the position is within the range, information on those points is provided, so that the position candidate is slightly relaxed, and the next candidate point that is convenient for achieving a plurality of purposes is found.

  As a specific example related to the relaxation of one condition, the search unit 240 searches for a plurality of pieces of point information including attribute information corresponding to one of a plurality of purposes, and then the position information included in the plurality of pieces of searched point information. The point information is stored as point information including position information indicating points having a fixed relationship with high-density points per unit area and including attribute information corresponding to the remaining purposes among the plurality of points. After searching from the spot information stored in the unit 220 or searching for a plurality of spot information including attribute information corresponding to one of a plurality of purposes, the position information included in the searched spot information indicates Identifies roads that pass near multiple points, includes location information that indicates points along the specified roads, and includes point information that includes attribute information corresponding to the remaining purposes among multiple purposes. It should be searched from the stored location information to the section 220.

  When the point information includes information indicating the parking lot and information indicating the distance from the parking lot to the point, the distance calculating unit 243 calculates the distances included in the plurality of point information searched by the searching unit 240. It is a processing unit that calculates the distance that the user should move to achieve the purpose corresponding to the plurality of pieces of point information by referring to the information shown. The information providing unit 250 provides information regarding a parking lot with a small distance calculated by the distance calculating unit 243. Thus, the distance traveled by the vehicle is presented to the user, which is convenient.

  The multi-purpose acquisition unit 230 further includes a movement history storage unit 231, a target ontology storage unit 232, a confidence value calculation unit 233, and a trust purpose extraction unit 234 as additional functions.

  The movement history storage unit 231 is a processing unit that incorporates a hard disk or the like that stores the movement history of the mobile terminal.

  The trust purpose extraction unit 234 is a processing unit that identifies a trust purpose that is an action predicted by the user from the movement history accumulated in the movement history accumulation unit 231 and the position information acquired by the position information acquisition unit 210. . With this trust purpose extraction unit 234, the multi-purpose acquisition unit 230 can specify a plurality of purposes including the trust purpose specified by the trust purpose extraction unit 234.

  More specifically, the movement history accumulating unit 231 identifies the attribute information corresponding to the arrival point of the movement history by referring to the point information stored in the point information storage unit 220, and uses the identified attribute information. The movement history including the information on the arrival point is accumulated as the purpose.

  The trust value calculation unit 233 identifies the purpose corresponding to the predicted arrival point of the mobile terminal by referring to the movement history accumulated in the movement history accumulation unit 231, and the destination candidate for each identified purpose. As a confidence value. Thereby, the trust purpose extraction unit 234 can specify the trust purpose based on the trust value for each purpose calculated by the trust value calculation unit 233.

  For example, for each purpose included in the movement history, the movement history accumulation unit 231 calculates a confidence value that is a probability that the target action is taken, accumulates the movement history including the calculated reliability value together with the corresponding purpose, The reliability value calculation unit 233 identifies a plurality of movement histories corresponding to a plurality of predicted arrival points of the mobile terminal from the movement history accumulation unit 231 and trusts corresponding to the same purpose included in the plurality of identified movement histories. By adding the values, a confidence value as a destination candidate is calculated for each purpose.

  Alternatively, the movement history accumulation unit 231 accumulates the movement history by including the points included in the movement route and the classification information of the points including the information indicating that it is home, and the trust purpose extraction unit 234 further includes By referring to the classification information included in the movement history, the distance from the user's home to the arrival point corresponding to the trust purpose is calculated, and the trust purpose is specified using the calculated distance. As a result, information on a point that is predicted to be optimal for achieving a plurality of purposes is provided at a higher hit rate, and convenience is improved.

  The purpose ontology storage unit 232 is a hard disk or the like that stores synonyms relating to the purpose indicated by the attribute information of the point information. The trust value calculation unit 233 further refers to the synonym stored in the target ontology storage unit 232 to determine the identity of the target included in the travel history stored in the travel history storage unit 231, and the mobile terminal A purpose corresponding to the predicted arrival point is identified, and a confidence value as a destination candidate is calculated for each identified purpose. Then, the trust purpose extraction unit 234 specifies the trust purpose based on the trust value for each purpose calculated by the trust value calculation unit 233. Thus, by referring to the target ontology, even if it is a different purpose in the history, for example, if it is common as a superordinate concept, it can be interpreted as a common purpose to reflect the user's behavior. As a result, it is possible to provide purpose information useful for the user.

  Hereinafter, the point information search device according to the present invention will be described in more detail using specific examples.

(Embodiment 2)
Next, the point information search apparatus in Embodiment 2 of this invention is demonstrated.

  FIG. 2 is a block diagram showing the configuration of the point information search apparatus according to Embodiment 2 of the present invention. This point information search device is a device that is provided in a mobile terminal such as a car navigation system and provides information related to a point suitable for performing a plurality of purposes input by a user. A storage unit 220a, a multipurpose acquisition unit 230a, a search unit 240a, and an information providing unit 250a are provided.

  The position information acquisition unit 210a corresponds to the processing unit that acquires position information indicating the position of the mobile terminal, that is, the position information acquisition unit 210 in the first embodiment. In the present embodiment, as an example, The position information detection unit 101 is included.

  The point information storage unit 220a stores the point information in which the position information of the point is associated with the attribute information related to the classification of the point or the action that can be performed at the point, that is, the point information in the first embodiment. This embodiment corresponds to the storage unit 220. In the present embodiment, the point information storage unit 103 is provided as an example.

  The multi-purpose acquisition unit 230a corresponds to the processing unit that acquires information for specifying a plurality of purposes for a purpose that is an action desired by the user, that is, the multi-purpose acquisition unit 230 in the first embodiment. As an example, the multi-purpose input unit 131 is provided.

  The search unit 240a is a fixed point in which the location indicated by the location information included in the location information and the location indicated by the location information acquired by the location information acquisition unit 210 are predetermined from the location information stored in the location information storage unit 220. And a processing unit that searches for point information including attribute information corresponding to a plurality of purposes acquired by the multi-purpose acquiring unit 230, that is, corresponds to the searching unit 240 in the first embodiment. In this embodiment, the information processing apparatus includes a point information search unit 122, a purpose match determination unit 126, a density calculation unit 132, a re-search unit 133, a distance calculation unit 124, a position condition generation unit 511, and a position condition correction unit 512.

  The information providing unit 250a corresponds to the processing unit that provides information related to the location indicated by the location information included in the location information searched by the search unit 240, that is, the information providing unit 250 in the first embodiment. In embodiment, it has the point information presentation part 125 as the example.

Hereinafter, the function of each component will be described in detail.
The position information detection unit 101 detects the position of the mobile terminal in which the point information search device is incorporated or the position indicating the position of the user carrying the point information search device (that is, acquires position information). GPS and the like. Note that the position information detection unit 101 may be an input device that accepts input of position information from the user and acquires it directly from the user as position information of the mobile terminal or the position of the user or the area to be searched. .

  The multi-purpose input unit 131 is a processing unit that acquires information for specifying a plurality of purposes for a purpose that is an action desired by the user. In this embodiment, the multi-purpose input unit 131 is used to input a plurality of purposes that the user is going to perform. It is an input device. FIG. 3 shows a display screen of the present apparatus constituted by, for example, a car navigation system, and the current position of the user is shown on the screen. FIG. 3 shows a display screen composed of a touch panel or the like, and the multi-purpose input unit 131 is a processing unit that receives a user input using, for example, a touch panel. As for the purpose input from the user, information related to the classification of points (for example, “restaurant”, “boring alley”, “tennis court”, “gas station”, etc.) is input, and the actions performed at the points (“meals” A plurality of types of information relating to bowling, tennis, refueling, etc. are input.

  In FIG. 3, a cursor for accepting a plurality of target inputs is shown in the upper right of the screen. Here, for example, the purpose “boring” and “family restaurant” are input by the user through a pull-down menu or the like. Note that the user may directly input text.

  As described above, when the user moves, the user may move to achieve a plurality of purposes instead of searching for a destination for performing one purpose. Also, if you can serve that purpose, you may not place much importance on the location. Specifically, although the user is currently aiming at “boring”, he / she is not searching for a specific bowling alley. As long as the purpose of the action of bowling can be achieved, the user thinks whether it is “boring alley A” or “boring alley B”. In this way, although a point is not specified, a search for a destination is often performed so as to fulfill a predetermined purpose.

  On the other hand, it doesn't matter what kind of bowling alley, but they also want to eat at "Familys". However, for the purpose “family restaurant”, the search is not performed by designating a specific store, and the user thinks that the family restaurant C or the family restaurant D may be used as long as the user can eat at “family restaurant”. . That is, instead of searching for a point by specifying a certain point, a plurality of purposes are input, and a search for a point that can fulfill these multiple purposes in one place or efficiently is performed. Conventionally, a technique for inputting a search keyword such as a category and searching for a corresponding point has been disclosed. However, a technique for inputting a plurality of purposes and proposing a place where these can be efficiently performed is disclosed. Not disclosed. Therefore, in this embodiment, a point information search apparatus that proposes a place that can efficiently fulfill these multiple purposes will be described.

  In the present embodiment, point information is used in order to search for a point that can fulfill the purpose when a certain purpose is input. In the present embodiment, the point information is defined as information having a predetermined point and information (attribute information) related to the point, and is stored in a server or the like in a general format such as XML. The point information storage unit 103 is a hard disk or the like that stores such point information. That is, the location information storage unit 103 is a hard disk or the like that stores location information that associates location information of locations with attribute information related to actions that can be performed at a location or location. Hereinafter, the point information will be described in detail first.

FIGS. 4A and 4B show point information related to the parking lot N of a certain “restaurant N”. The point information includes “location information” of a reference point and information related to the classification of the point or actions that can be performed at the point, that is, “attribute information” related to the position. The location information has general-purpose information such as latitude and longitude information so that it can be used in various applications. On the other hand, the attribute information can be used according to the application or by each point information use company. It may be something that can be created independently.

  As shown in FIGS. 4A and 4B, the position information includes, for example, information on a reference position and the name of the point. Moreover, it has the information regarding the range (cover area) which the point information considers. The reference position is represented by latitude and longitude, and is indicated by, for example, “latitude tag” and “longitude tag”. The name is indicated by “name tag” and the cover area is indicated by “cover area tag”. For example, as shown in FIG. 4B, the location information of “parking lot N” includes latitude “N35.41”, longitude “E135.51”, name “parking lot N”, The cover area is “radius 100 m”.

  FIG. 5 is a diagram for explaining the spot information of “parking lot N” shown in FIGS. 4 (a) and 4 (b). In FIG. 5, the cross mark (×) is a reference position (N35.41, E135.51). A circle drawn with a dotted line indicates the cover area “radius 100 m”. That is, the point information of this “parking lot N” is used at points within the cover area “radius of 100 m”. For example, when there is a user at a position indicated by oblique lines, the point information to be used is point information of “parking lot N”.

  Further, the point information has information such as peripheral stores existing in the cover area as attribute information. As shown in FIG. 5, “Restaurant N” exists in the cover area of “Parking N”. Therefore, the point information further includes information on these stores. In the point information shown in FIGS. 4A and 4B, information on these neighboring stores is described as attribute information. For example, “Restaurant N” is written as peripheral store information. Furthermore, as commercial information of each store, for example, the homepage of “Restaurant N” is linked with an address where commercial information is written, such as “www.Restaurant-N.com”.

  As described above, the point information refers to information obtained by associating a certain point with attribute information related to the point, for example, information related to neighboring stores.

  Further, the number of stores around a point is not limited to one, and may be point information where a plurality of stores are adjacent. For example, FIGS. 6A and 6B show point information regarding a certain “parking lot A”. The point information of “parking lot A” includes latitude “N35.001”, longitude “E135.01”, name “parking lot A”, and cover area “radius 100 m” as a reference position. Further, in the case of “parking lot A”, there are a plurality of peripheral stores, and information on peripheral stores and the like existing in the cover area is described. The point information of “parking lot A” shown in FIGS. 6A and 6B will be described with reference to FIG.

  In FIG. 7, the cross marks are reference positions (N35.01, E135.01). A circle drawn with a dotted line indicates the cover area “radius 100 m”. That is, the point information of the “parking lot A” is used at points within the cover area “radius of 100 m”. For example, when the user is at a position indicated by diagonal lines, the point information to be used is point information of “parking lot A”. Further, the point information has information such as peripheral stores existing in the cover area as attribute information. As shown in FIG. 7, there are a plurality of stores such as “home appliance shop B”, “restaurant C”, and “movie theater D” in the cover area of “parking lot A”. The point information further includes information on the plurality of stores. In the point information shown in FIGS. 6A and 6B, information on these neighboring stores is described as attribute information. For example, “appliances shop B”, “restaurant C”, “movie theater D”, etc. are written as peripheral store information. Furthermore, as commercial information of each store, for example, the homepage of “home appliance shop B” is linked with an address where commercial information is written, such as “www.kaden.com”.

  FIG. 8 is a diagram illustrating an example of use of peripheral information that is one of attribute information. For example, assume that the user is located at the position shown on the screen 1. Here, it is assumed that the user searches for nearby stores. Conventionally, when searching for nearby stores, a user accesses a related page and searches for information to be searched for by himself / herself, or filters prefectures and regions as keywords from information stored in advance by each device such as a car navigation system. However, in the present embodiment, it is possible to perform the search using point information.

  First, based on the point where the user is located, the corresponding point information, the point information of “parking lot A” will be used. As described above, the location information of “parking lot A” includes peripheral store information. Therefore, for example, when the user performs “peripheral search” (screen 1), the peripheral store information of the point information is used, and the corresponding stores “electric shop B”, “restaurant C”, and “movie theater D” are candidates. (Screen 2). Further, for example, when “Electric Shop B” is selected (screen 3), “www.kaden.com” linked to “Electric Shop B” in the store information is accessed and commercial information is displayed ( Screen 4). As described above, the point information has information related to the point and the surroundings based on the predetermined point, and can be used when, for example, searching for the surroundings. Note that the above description of using spot information for peripheral search is merely an example, and the use method of spot information is not limited to this. The point information in the present embodiment is a general-purpose format, for example, by using the position information indicated by latitude and longitude as a reference, it is possible to use the point information based on the point with different devices. Furthermore, by including information necessary for individual devices and functions as attribute information, various applications and functions can be realized.

  In the present embodiment, it is assumed that the point information is accumulated by associating a point with a purpose that can be achieved at the point. The point information of “parking lot N” shown in FIGS. 4A and 4B has “purpose information” as attribute information. The purpose information is information reflecting the purpose of the destination candidate from the point, and is described here by “purpose tag”. For example, since a Japanese meal can be performed at “parking lot N”, there is “restaurant N” as a destination candidate for the user who came to “parking lot N”. There is a purpose “meal (Japanese food)”, and this information is included as purpose information.

  Further, there may be a plurality of pieces of purpose information for one point. For example, as the purpose information of “parking lot A” shown in FIGS. 6A and 6B, a user who came to “parking lot A” can purchase home appliances at “home appliance shop B”. There is “Electric shop B” as one of the destination candidates, and in this embodiment, there is a purpose “purchase home appliance” at the destination, and this information is included as the purpose information. Alternatively, there is “restaurant C” as another destination candidate, and it is possible to dine there, so “meal” is included as the purpose information. Furthermore, there is “Movie Theater D” as a destination candidate, and the purpose “Movie Viewing” there. In this way, the point information is, as one of the information related to the point, for example, the target information reflecting the destination store from the point, the purpose of the action at the store, etc. based on the store in the cover area have.

  Here, some application examples of the point information will be described. FIG. 9 shows a map near a certain “parking lot E”. In the vicinity of “Parking E”, there are “Bookstore F” and “CD Shop G”. On the other hand, there is a super I near the “parking lot H”. Point information exists at these points. For example, the point information of “parking lot E” is centered on the reference points “E135.11, N35.11” and has a radius of 80 m as a cover area. In addition, regarding the point information of “parking lot H”, the reference point is “E135.21N35.10”, and the cover area surrounds “parking lot H”. Thus, in the point information, the size and shape of the cover area can be arbitrarily set based on, for example, latitude and longitude which are general-purpose values. For example, it is possible to change the area covered by the point information based on the positions of the surrounding parking lots.

  FIGS. 10A and 10B show details of the spot information of “parking lot E” and “parking lot H” shown in FIG. The position, the cover area, the name, and the like are written in the same manner as the point information of “parking lot A” described above. In addition, the location information of “parking lot E” includes, as attribute information, peripheral stores “bookstore F”, “CD shop G”, and commercial information of those stores. In addition, the purpose “book purchase” that will be performed at “bookstore F”, the purpose “CD purchase” that will be performed at “CD shop G”, and the like are described as destination candidate information. On the other hand, the location information of “parking lot H” includes the neighboring stores “Super I” and “CD Shop G”. As described above, the surrounding store information may be a plurality of points. For example, a store that has contracted with many parking lots, such as a large department store, can write commercial information in a plurality of pieces of point information, which leads to an advertising effect for the user to use. In addition, the purpose information “purchase of food”, “purchase of clothes”, and the like that will be performed at “Super I” are described. As described above, even in one store, a single purpose is not limited to one, and a plurality of purposes can be described. For example, even users who use the same “Super I” can change the information to be provided according to the purpose.

  The purpose information may be given by a system designer, as well as by a person for the purpose of advertising, such as a map production company, a parking lot manager, or a nearby store manager. Furthermore, it is also possible to perform morpheme analysis from commercial information such as homepages and advertising information of stores, etc., to extract target keywords and automatically create them.

  In the present embodiment, the destination information that can fulfill the input purpose is searched using the destination information described in the point information.

  The position condition generation unit 511 generates a condition regarding a position for searching the spot information storage unit 103 based on the position information input by the position information detection unit 101. For example, when a certain position (latitude, longitude) is input, a position condition such as a predetermined range (for example, a range of 1 km) is generated from the position, and thereby the target condition input within the generated position condition is generated. Search is possible. In addition, in the case of searching around the vehicle, the position condition generation unit 511 is a search condition for position information in a predetermined range (for example, a range of 3 km) in consideration of the traveling direction of the vehicle with reference to the current position of the vehicle. Is generated. For example, in the case of a vehicle, it is not easy to change the direction, and a search considering the traveling direction may be preferable. In addition, when the predetermined position condition is not set in this way, if information on points in Japan is stored in the point information storage unit 103, the point information becomes enormous, and unnecessary information is searched. It will end up. As illustrated in FIG. 12, the position condition generation unit 511 can generate several position conditions for the reference position input or detected by the position information detection unit 101.

  For example, as in the example of the position condition shown in FIG. 12, the position condition A is a position condition for searching for a point having a predetermined distance with respect to the reference position, and the position condition B takes into account the traveling direction of the vehicle. It is a position condition. The position condition C is a position condition by a rectangle including the reference point, and the position condition D is a condition for searching for a point adjacent to the main road closest to the reference position. For example, in the case of a vehicle or the like, it is easier for a user to visit a store adjacent to a route or along a main road that is relatively easy to travel, and is often suitable as a search. It is. In this way, by setting the position condition, it becomes possible to efficiently search for point information that is likely to be required by the user at present.

  The point information search unit 122 generates a position condition from the point information stored in the point information storage unit 103 based on the point indicated by the position information included in the point information and the position indicated by the position information acquired by the position information detection unit 101. The point information that satisfies the position condition generated by the unit 511 is searched. Then, the purpose match determination unit 126 searches for point information including attribute information corresponding to a plurality of purposes acquired by the multi-purpose input unit 131 from the point information searched by the point information search unit 122. Based on the plurality of purposes input by the multi-purpose input unit 131 and the position-related conditions generated by the position condition generation unit 511 by the point information search unit 122 and the purpose match determination unit 126, the point information storage unit 103 A point that can fulfill a plurality of purposes is searched from the position information of the points stored in the.

  For example, when a position search condition having a radius within 500 meters centered on the current position of the user is generated, the point information of the area is searched. FIG. 11 shows the searched point information in a list format. For example, as the point information “001”, the point information of the position “135 degrees 01 minutes east longitude, 35 degrees 01 minutes north latitude”, the name “parking lot A”, and the purpose “family restaurant” is acquired. As described above, the point information is accumulated along with the purpose information obtained from the predetermined point and its surrounding stores. For example, parking at the “parking lot A” and eating at a nearby family restaurant It can be done.

  On the other hand, the location corresponding to “Family” is not limited to “Parking A”, but in the example shown in FIG. 11, “Nishimaru Department Store” with location information “002”, “Joy Fool” with location information “003”, location It is shown from the retrieved point information that the restaurant “Hanamachi General Restaurant” with the information “004” can be used for a family restaurant. In this way, there are many points where a predetermined purpose can be achieved, and a plurality of points are searched.

  FIG. 13 is a map showing the points corresponding to the object “family restaurant” shown in FIG. The location of “Nishimaru Department Store”, “Joy Fool”, “General Restaurant”, “Regal Host”, etc. acquired as point information of a point located within a radius of 500 meters centered on the current position of the user is displayed on a map. Has been.

  The point information search unit 122 further searches for point information corresponding to another purpose “boring”, and can use the acquired point information to fulfill the purposes of “family restaurant” and “boring”. Is calculated and provided to the user.

  For example, if there is a point that can fulfill the purposes of the multiple purposes “family restaurant” and “boring”, the purpose match determination unit 126 determines whether or not they match, and the point information presentation unit 125 These point information is presented. Alternatively, as will be described later, the distance calculation unit 124 may calculate a more appropriate point in consideration of the distance between stores that can fulfill these multiple purposes, and provide information.

  However, there is not always a point that matches all of the plurality of purposes. In the future, it will be unrealistic in terms of search costs, etc., to search for all of these point information in an environment where point information showing commercial information such as various stores can be used. As shown in the form, it is necessary to provide a position condition and perform an efficient search. On the other hand, the provision of the position condition does not necessarily mean that the points that match these plural purposes are searched. For example, in the case of this example, it is assumed that there is no corresponding point in the search range in the position condition generated by the position condition generation unit 511. That is, in FIG. 13, it is assumed that there is no point where another purpose of “boring” can be performed within a radius of 500 meters centered on the user. The purpose match determination unit 126 determines that they do not match.

  Therefore, in the present embodiment, the density calculation unit 132 calculates the number of point information per unit area, that is, the density of the point information, and the re-search unit 133 generates the position condition generated by the position condition generation unit 511. The point information is searched again by changing.

  The re-search unit 133 determines in advance the location indicated by the location information included in the location information and the location indicated by the location information acquired by the location information detection unit 101 from the location information accumulated in the location information accumulation unit 103. After searching for point information that has a certain relationship and includes attribute information corresponding to one of the plurality of purposes acquired by the multi-purpose input unit 131, the position information included in the searched point information is Search for point information including position information indicating a point having a certain relationship with the indicated point and including attribute information corresponding to the remaining purpose among a plurality of purposes from the point information accumulated in the point information accumulation unit 103 It is a processing unit. In the present embodiment, search is performed after searching for a plurality of pieces of point information including attribute information corresponding to one of a plurality of purposes by the cooperative operation of the re-search unit 133, the density calculation unit 132, and the distance calculation unit 124. The location information included in the location information includes location information indicating locations that have a fixed relationship with the locations with high density per unit area, and corresponds to the remaining objectives of the multiple purposes. The point information including the attribute information to be searched is searched from the point information stored in the point information storage unit 103. Hereinafter, the function of the re-search unit 133 will be described using a specific example.

  As shown in FIG. 13, there may be a plurality of pieces of point information depending on the region. For example, there are a relatively large number of stores and a lot of point information in urban areas and cities. Further, the point information is not limited to “Familys”, and since the information of all stores is accumulated, the number thereof can be enormous. In such an environment, simply expanding the search range is not preferable because of the calculation cost of the search. Therefore, the density calculation unit 132 calculates the density of the spot information, and the position condition correction unit 512 corrects the position condition generated by the position condition generation unit 511.

  The position condition correction unit 512 has a predetermined number of pieces of point information searched by the point information search unit 122 and determined to match the purpose input from the multipurpose input unit 131 by the purpose match determination unit 126. When the number is less than the number (in the present embodiment, when the density calculated by the density calculation unit 132 is lower than a certain value), the position condition generated by the position condition generation unit 511 is corrected.

  For example, only the point information corresponding to one object “family restaurant” is used, and the center point where the point information is dense is calculated. A clustering method for calculating a predetermined number of center points from a sample located in a space, such as the Segmental-K-Means method, is conventionally known. For example, two-dimensional coordinates are taken with the latitude as the X axis and the longitude as the Y axis, and the crowded points are calculated using the latitude and longitude information of each point given to the point information.

  As shown in FIG. 14, the central point where the point information is concentrated from “Nishimaru Department Store”, “Joy Fool”, “Regal Host”, “Hanamachi General Restaurant”, etc. corresponding to one purpose “Family” Z is calculated. Therefore, the position condition correction unit 512 sets a new search area within a radius of 500 meters centered on the center point Z, and the re-search unit 133 corresponds to another purpose “boring” in the new search area. Search for location information. FIG. 15 is a diagram illustrating a result of searching for point information again by expanding the search area. FIG. 15 shows “Star Bowling” and “Strike No. 1” corresponding to the purpose “Bowling”.

  The point information search unit 122 searches the points stored in the point information storage unit 103 for each piece of input information input by the multi-purpose input unit 131, and the position condition correction unit 512 includes the multi-purpose input unit. Using the position information of the points satisfying the single input information input in 131, the position condition generated by the position condition generating unit 511 is determined from the density of the searched points per unit area. It has been corrected to include. Thereby, even when there is no point that achieves a plurality of purposes, it is possible to present the search result to the user by correcting the search condition regarding the position. However, the number of points that can fulfill the purposes of the multiple purposes “family restaurant” and “boring” is not limited to one, and a plurality of points may be calculated. In this case, the point information presenting unit 125 may present the calculated plurality of points and allow the user to select, but calculates a point that can achieve these multiple purposes more efficiently, It may be provided to the user.

  For example, when providing a user with a point where a store capable of fulfilling a plurality of purposes exists, the distance between these stores is often an important concern of the user. As an example, when the user moves on foot, the user moves between stores that can fulfill each purpose among a plurality of purposes. Therefore, it is often preferable that the moving distance is small. In addition, when the user moves by vehicle, parking is completed only once and the user moves between the stores by walking or the like. Therefore, it is often preferable that the moving distance is short. Therefore, in the present embodiment, the distance between a plurality of points that can achieve these purposes is calculated, and information on points more suitable for the user is provided.

  The distance calculation unit 124 is a processing unit that calculates the distance between a plurality of points that can fulfill the purpose, that is, calculates the distance that the user should move to achieve the purpose corresponding to the plurality of point information. . For example, the distance between points is calculated using point information corresponding to a plurality of selected purposes “Family” and “Bowling”, and the points that can fulfill these multiple purposes are calculated most efficiently. .

  FIG. 16 shows the purpose of “Nishimaru Department Store”, “Joy Fool”, “Hanamachi General Restaurant”, “Regal Host”, which is the “family restaurant”, and “Star Bowling”, “Strike No1”, which are the purpose “boring”. The distance is shown in a table. Here, the distance “340 meters” between “Star Bowling” and “Nishimaru Department Store” is calculated from the point information. Similarly, “Joy Fool” and “400 meters”, “Hanamachi General Restaurant” and “300 meters”, “Regal Host” and “620 meters” are calculated. Also, the distance between “Star Bowling No. 1” and “Nishimaru Department Store” is “500 meters”, “Joy Fool” and “480 meters”, “Hanamachi General Restaurant” and “720 meters”, “Legal Host” and “420 meters” Is calculated. In this case, since the distance between “Star Bowling” and “Hanamachi General Restaurant” is the closest to “300 meters”, the purpose of this time “Family” and “Bowling” can be achieved most efficiently. As the points, the point information presenting unit 125 provides these information to the user via a screen or the like.

  The spot information presentation unit 125 is searched by the spot information search unit 122, and the point match determination unit 126 re-sends the point information determined to match the purpose input by the multi-purpose input unit 131 or the condition. Information about the point indicated by the position information included in the point information, which is re-searched by the search unit 133 and the distance between the points calculated by the distance calculation unit 124 within a certain range, is displayed via a screen or the like. And a processing unit provided to the user. In the above example, since “Star Bowling” and “Hanamachi General Restaurant” are searched, as shown in FIG. 18, the first stop from the current location is “Hanamachi General Restaurant”, and then “Star Bowling”. The route to go and the commercial information at each point. The point information presenting unit 125 reads out from the map information and commercial information stored in the car navigation system in which the point information search device is incorporated, or accesses a website on the Internet by wireless communication. Information regarding points such as commercial information at each point is acquired and provided to the user.

  For a plurality of purposes, if the distance between the points is sufficiently short (for example, within walking distance), the purpose can be achieved by one parking of the vehicle. Therefore, it is not always necessary to determine the order of visits. On the other hand, when the distance between the points is relatively long, the order of visiting may be further determined. Conventionally, as shown in FIG. 19, the result of each search condition is presented for each purpose. Therefore, in order to perform a plurality of purposes in one go, it is necessary to consider again which combination of visits is suitable for the point information of the presented search results as shown in FIG. There is. However, in the present embodiment, by selecting a combination of points searched for a plurality of purposes in consideration of the distance of each point, the user does not need to consider a combination of points as a search result. Furthermore, by determining the order of visiting in consideration of the distance between the points, it is possible to provide information required by the user without complicated operations. For example, rules relating to distance are further accumulated in the re-search unit 133 and the like. And it is good also as the said order, for example, less than 300m being set as the walking area, and when outside the walking area, the visit order is further calculated and presented.

  As shown in the present embodiment, when there are no points corresponding to a plurality of purposes, the search range is expanded based on the points where the points that can fulfill one purpose are densely arranged. It becomes possible to reduce the cost concerning. In addition, since searching is performed based on points where points corresponding to one purpose are crowded, the options on the user side are widened. For example, even if the calculated “Hanamachi General Restaurant” is not used, the “Famires” alternatives “Hanamachi General Restaurant”, “Nishimaru Department Store”, “Joy Fool”, “Legal” Since the “host” is located in the vicinity, even if another “family restaurant” is used, the purpose can be achieved relatively efficiently.

  Next, the operation flow of the point information retrieval apparatus in the present embodiment configured as described above will be described with reference to FIG. First, the multi-purpose input unit 131 accepts a plurality of inputs by the user regarding purposes such as classification of points and contents of actions at the points (step S501). As shown in FIG. 3, the objectives “family restaurant” and “boring” are input in this example. Next, the spot information search unit 122 searches the spot information storage unit 103 for spot information corresponding to the input purpose. However, the position condition generation unit 511 generates a search condition related to the position using the position detected by the position information detection unit 101 (step S502), and the point information search unit 122, for example, stores point information within a radius of 500 meters. Search is performed (step S503).

  Then, the purpose match determination unit 126 determines whether or not point information corresponding to a plurality of purposes exists (step S504). If it exists (Yes in step S504), the spot information presentation unit 125 presents information required by the user, such as commercial information and route information, using the spot information (step S509). If a plurality of searches are made here, as described above, the distance calculation unit 124 may calculate the distance between points, and the point information presentation unit 125 may present the closest one (step S508). ).

  On the other hand, when there is no point information corresponding to a plurality of purposes (No in step S504), for example, the density calculation unit 132 calculates a crowded point using at least one point information corresponding to the purpose (step S504). S505). For example, the crosses in FIG. 14 are points where crowded points are calculated using point information corresponding to “family restaurant” which is one of the purposes. If there is no relevant purpose, simply expanding the search area is not preferable in terms of search cost. Therefore, the position condition correction unit 512 corrects the position-related conditions with reference to an area where the point information corresponding to one purpose is crowded, so that the search cost can be reduced and the point corresponding to the other purpose can be reduced. When calculated, it is possible to efficiently calculate a point in consideration of both.

  Next, the re-search unit 133 searches again for point information corresponding to the purpose based on the obtained center point (step S506). Then, it is determined whether or not there is a point corresponding to the purpose (step S507). If it exists (Yes in step S507), the distance calculation unit 124 calculates the distance between the searched points (step S507). S508), the point information presentation unit 125 provides information (step S509). On the other hand, if it does not exist (No in step S507), the position condition correction unit 512 corrects the position condition again (to step S505), and the re-search unit 133 performs a search. FIG. 15 is a diagram illustrating an example in which the search area is expanded again and a point corresponding to the purpose “boring” is calculated. It is shown that “Star Bowling” and “Strike No. 1” that could not be searched in the search area shown in FIG. 13 are newly searched.

  Then, as described above, the distance calculation unit 124 calculates the distance between points that can fulfill the plurality of purposes by using the point information corresponding to the plurality of purposes (step S508). FIG. 16 is a diagram illustrating the calculated distances between points. In this case, the distance “300 meters” between “Star Bowling” and “Hanamachi General Restaurant” is the closest distance, and the point information can be presented as the points that can most efficiently serve multiple purposes. The unit 125 presents information (step S509).

  As described above, according to the present embodiment, using the point information, a destination and a movement route suitable for efficiently performing a plurality of purposes input by the user are shown. Also, it is avoided that the route search is repeated or an inefficient route is moved.

  In the present embodiment, a point satisfying a single purpose input by the multi-purpose input unit 131 is searched, and the position condition generated by the position condition generation unit 511 is corrected using the center of gravity of the position information. did. Instead, after searching for a point that satisfies a single purpose, if the point is crowded along a certain road, search for a point that satisfies the next purpose along that road. The search condition regarding the position may be corrected. Thereby, there is a high possibility that a point satisfying a plurality of purposes facing the same road will be searched, and it will be possible to provide information on a point that is efficient for the user.

  FIG. 20 is a block diagram showing a configuration of a point information search apparatus in a modified example in which the search condition is corrected using the road of the searched point information as described above. This point information search device is a device that is provided in a mobile terminal such as a car navigation system and provides information related to a point suitable for performing a plurality of purposes input by a user. A storage unit 220a, a multipurpose acquisition unit 230a, a search unit 240b, and an information providing unit 250a are provided. This point information search device has basically the same configuration as the point information search device in the second embodiment, but differs from the second embodiment in that a search unit 240b is provided instead of the search unit 240a.

  The search unit 240b is a fixed point in which the location indicated by the location information included in the location information and the location indicated by the location information acquired by the location information acquisition unit 210 are predetermined from the location information stored in the location information storage unit 220. And a processing unit that searches for point information including attribute information corresponding to a plurality of purposes acquired by the multi-purpose acquiring unit 230, that is, corresponds to the searching unit 240 in the first embodiment. In this modification, the information processing device includes a point information search unit 122, a related road extraction unit 126a, a road determination unit 132a, a re-search unit 133, a position condition generation unit 511, and a position condition correction unit 512. Hereinafter, the same components as those of the second embodiment are denoted by the same reference numerals, and the description thereof is omitted.

  The related road extraction unit 126a uses the conditions related to the position of the point information generated by the position condition generation unit 511 and the point information stored in the point information storage unit 103B for one purpose input by the multi-purpose input unit 131. The road that is along the point information searched by the information search unit 122 is extracted. It is assumed that the correspondence between each point and the road is accumulated in the point information accumulation unit 103. Alternatively, the nearest road may be calculated from the position information of each point, and the road may be used as a road along each point. For example, it is assumed that “restaurant” and “boring” are input as multi-purpose inputs. At this time, as shown in FIG. 21, it is assumed that a vehicle exists at a point indicated by an arrow, and a search condition related to position information is generated so as to search for point information around the vehicle. Further, as shown in FIG. 21, for a plurality of purposes, it is assumed that only “restaurant” point information exists and “boring” point information does not exist within a range close to the current position. At this time, as shown in FIG. 22 (a), the related road extracting unit 126a extracts the roads near the place where each restaurant exists for the searched restaurants A to E. As a result, as shown in FIG. 22A, a table in which a road ID is associated with each restaurant is generated.

  The road determination unit 132a determines a road to be used as a search condition from the roads extracted by the related road extraction unit 126a. For example, as shown in FIG. 22A, when roads are extracted, those roads are used when expanding the search condition. Using these road information, the search conditions generated by the position condition generation unit 511B are relaxed.

  The position condition correcting unit 512 corrects the search condition generated by the position condition generating unit 511 using the road information determined by the road determining unit 132a. For example, as shown in FIG. 22 (a), when roads R201, R202, and R210 are selected, each road is again input with respect to a condition in which point information cannot be searched although it is input at the multi-purpose input unit. Perform a search.

  The re-search unit 133 searches the point information again with the search condition corrected by the position condition correction unit 512. That is, the re-search unit 133 searches the plurality of spot information after the spot information search unit 122 searches for a plurality of spot information including attribute information corresponding to one of the plurality of objectives input by the multi-purpose input unit 131. Attribute that identifies the road that passes near the multiple points indicated by the location information included in the location information, includes location information that indicates the location along the identified road, and corresponds to the remaining purpose among the multiple purposes The point information including the information is searched from the point information stored in the point information storage unit 103.

  For example, as illustrated in FIG. 22A, the re-search unit 133 performs a search again on the condition of “boring” using the selected road. As a result, as shown in FIG. 22 (b), point information capable of “boring” along each road is searched. Since each road is road information obtained as a result of a search for “restaurant”, a combination of a restaurant and a bowling alley can be selected for each road as shown in FIG. . As described above, even when the point information satisfying some of the plural purposes cannot be searched, the point information can be efficiently searched using the road information.

  FIG. 23 shows an operation flow of the point information search apparatus in this modification. This flow will be described with a focus on a search condition correction flow using road information. First, the multi-purpose input unit 131 inputs a plurality of purposes (S58F0). The position condition generation unit 511 determines a search condition regarding a position for inspecting the spot information (S58F1). For example, a search condition for point information within a radius of 1 km from the current position is generated. The point information is searched for within the range of the search condition generated by the position condition generation unit 511B for the input plural purposes (S58F2). If there is point information satisfying for a plurality of purposes (No in S58F3), the process proceeds to S58F6, and the point information presentation unit 125 presents a combination of the point information (S58F6). If there is no point information that satisfies a plurality of purposes (Yes in S58F3), the process proceeds to S58F4. When there is no point information that satisfies both of the plurality of purposes, the related road extraction unit 126a selects the point information that satisfies one of the plurality of purposes, and the nearest point for each piece of point information is selected. A road is extracted (S58F4). As a result, in this example, as shown in FIG. 22A, a road is determined for each point information. Further, the road determination unit 132a corrects the search condition using the road information, and returns to S58F2 (S58F5). As a result of the above operation, point information for performing a plurality of purposes along the same road is searched, so that it is possible to search for point information that can be easily moved by a vehicle or the like for the plurality of purposes.

  In this embodiment, when there is no point that satisfies one purpose included in a plurality of input purposes, the search condition related to the position condition is corrected. However, the point that satisfies one purpose If the number is less than the predetermined number, the search condition may be corrected. For example, when only a smaller number of pieces of data than the number of point data that can be displayed on the display device are searched, the search condition related to the point condition may be corrected.

  In the present embodiment, the distance calculation unit 124 is provided, the distance between the calculated multiple destinations is calculated, and a point more suitable for the user is provided. However, this component is not necessarily required. Not limited to this, the configuration excluding the distance calculation unit 124, that is, the configuration shown in FIG. The purpose of movement is to fulfill a plurality of purposes, and the movement distance between them is not necessarily a matter of interest to the user. If a plurality of input purposes can be achieved, the distance between the points is not limited, or the user may actively select from the proposed point candidates. It is good.

(Embodiment 3)
Next, a third embodiment of the present invention will be described.

  In the second embodiment, the method of searching for a point that can efficiently fulfill a plurality of inputted purposes using the point information and providing the information has been described. In addition, since a point that can fulfill a plurality of purposes does not necessarily exist in the search range, and simply expanding the search range causes a problem of processing cost of a huge amount of point information. The search method of the point which can change the search range to the standard and can achieve multiple purposes more efficiently has been explained.

  By the way, instead of the user entering all of these multiple goals, when a single goal is entered, a destination that can guess the multiple goals and simultaneously fulfill these multiple goals is recommended. It is also convenient. For example, if a user's input of one purpose is stored in the history of normal travel, the destination may be recommended in consideration of the purpose of having performed another purpose at the same time in the past. is there. In particular, in recent years, with the emergence of a complex facility formed by combining various stores, a user can achieve a plurality of purposes in one place. In addition, the user may visit such a facility in an attempt to complete a plurality of tasks with one parking. For example, there may be a case where a plurality of purposes such as visiting a certain point and purchasing a book or a CD are fulfilled, and further, the plurality of purposes may be completed by one parking. Or, after bowling or the like, there is a case of eating at a restaurant. It is cumbersome to input these multiple purposes each time, and if the destination that can fulfill these multiple purposes at the same time is recommended based on the movement history, the other purpose can be estimated. This makes it possible to support the user with easier operation.

  2. Description of the Related Art Conventionally, a technique for predicting a driver's favorite destination from a travel history and providing route information to that point and new information at that point has been disclosed.

  However, such conventional technology does not take into account the plurality of purposes of the user, and there is only one favorite destination. The user's purpose is rarely one, and there may be a demand for a place where a plurality of purposes can be processed simultaneously. Therefore, in this embodiment, a point information search apparatus that proposes a place where a plurality of purposes can be achieved using the purpose information will be described. For example, when the purpose of “book purchase” is input based on the movement history of the user, a plurality of purposes such as “purchase CD” are further estimated, and a place where these multiple purposes can be achieved is proposed. To do.

  FIG. 25 is a block diagram showing the configuration of the point information search apparatus in the present embodiment. This point information retrieval device is a device that estimates the other purpose from one input object, provides information on the destination that can simultaneously fulfill these multiple purposes, and information on the destination. Unit 210a, point information storage unit 220a, multi-purpose acquisition unit 230b, search unit 240d, and information providing unit 250a. This point information search device has basically the same configuration as the point information search device in the first embodiment, but includes a multi-purpose acquisition unit 230b instead of the multi-purpose acquisition unit 230, and searches instead of the search unit 240. The point provided with the part 240d is different from the first embodiment.

  The multi-purpose acquisition unit 230b corresponds to the processing unit that acquires information for specifying a plurality of purposes for a purpose that is an action desired by the user, that is, the multi-purpose acquisition unit 230 in the first embodiment. In this embodiment, the information processing apparatus includes a position information storage unit 121, a destination point specifying unit 102, a destination candidate specifying unit 1031, a movement history storage unit 104, a confidence value calculation unit 106, a trust purpose extraction unit 123, and a multipurpose input unit 131.

  The search unit 240d is a fixed point in which the point indicated by the position information included in the point information and the position indicated by the position information acquired by the position information acquisition unit 210 are predetermined from the point information stored in the point information storage unit 220. And a processing unit that searches for point information including attribute information corresponding to a plurality of purposes acquired by the multi-purpose acquiring unit 230, that is, corresponds to the searching unit 240 in the first embodiment. In this embodiment, the information processing device includes a point information search unit 122 and a distance calculation unit 124.

Hereinafter, a description will be given focusing on differences from the first and second embodiments.
The position information detection unit 101 is a processing unit that detects the current position of the mobile terminal. The position information detection unit 101 is configured by, for example, a GPS antenna provided in a mobile terminal and detects the latitude / longitude information of the user.

  The position information storage unit 121 is a hard disk or the like that stores detected position information. For example, FIG. 26 is a diagram showing the movement of the car navigation system having the present point information search device on a map. Suppose that the user has left home and has passed through the first, second, and third intersections as indicated by the thick black line in FIG. On the other hand, white circles are position information detected by the position information detection unit 101.

  FIG. 27 specifically shows an example of position information in numerical values. In addition, it is good also as providing the time obtained from GPS, or a calendar clock etc., and detecting the date time information from which the positional information was detected simultaneously. Here, it is detected that “position is 135 degrees 20 minutes 35 seconds east longitude, 34 degrees 44 minutes 35 seconds north latitude” at “8:10 on December 10, 2004”, and the like.

  The arrival point specifying unit 102 is a processing unit that determines a user's arrival point from the detected position information. For example, in car navigation systems, it is possible to determine a point where the engine is stopped as a destination point. As shown in FIG. 28, it is assumed that the user who has turned right at the third intersection has stopped the engine in the vicinity of “parking lot A”. In this case, for example, the parking lot A can be determined as the arrival point by using landmark information on the map accumulated in the car navigation system. For example, when a pedestrian uses a mobile phone, it can be determined as a destination based on a predetermined staying time.

  A conventional information providing apparatus accumulates these arrival points, and provides information by judging a user's favorite destination using the accumulated history of arrival points. For example, if a restaurant has a place where it has arrived and the restaurant is visited frequently, the restaurant can be determined as a favorite restaurant and information on the restaurant can be provided.

  In such a conventional information providing apparatus, there is only one point for determining preference or the like, and it does not reflect a plurality of purposes. For example, as shown in FIG. 28, when the vehicle has reached the parking lot A, it is possible to consider the frequency of arrival at the point of the parking lot A, but this is the original purpose of the user at that point. It is not possible to estimate the destination. For example, after reaching a parking lot A, a user may move to an electrical shop B to purchase an appliance. Or you may visit Movie Theater D to watch a movie. Furthermore, after watching a movie in the movie theater D, the restaurant C may have visited the parking lot A to serve food and fulfill multiple purposes. Therefore, even if an attempt is made to provide information to the user, the purpose cannot be specified, and thus accurate information cannot be provided. For example, in the former case, it is preferable that the information to be provided is sales information at the electrical store B, and in the latter case, it is preferably the movie show time information. Furthermore, in recent years, with the advent of complex facilities, there are a plurality of adjacent stores for such a single arrival point, and the user may visit these multiple stores to fulfill a plurality of purposes. . Further, in the case of car navigation, it is not preferable to disturb the driving task, so it is necessary to provide information according to the user's destination and purpose rather than providing all the information of the destination candidates.

  Therefore, in the present embodiment, the purpose information given corresponding to the point shown in the second embodiment is used, the movement history and the purpose at that point are accumulated, and the user's favorite purpose is determined. The method of recommending the destination according to the purpose is adopted. Therefore, in the present embodiment, the aforementioned “point information” is used in order to identify the arrival point, the destination from the arrival point, and the purpose at the destination.

  The destination candidate specifying unit 1031 is a processing unit that specifies destination candidates from the arrival point using the point information stored in the point information storage unit 103.

  The movement history accumulating unit 104 is a processing unit that accumulates a movement history including an arrival point and a purpose of a destination candidate from the arrival point, and has a hard disk or the like inside. For example, as shown in FIG. 26, a user who has left his home and has passed through the first intersection, the second intersection, and the third intersection has reached “parking lot A” as shown in FIG. 28. To do. The movement history accumulating unit 104 accumulates the movement destination from the reached point, that is, the movement destination candidate in “parking lot A” based on the movement destination candidate information of the point information. For example, as shown in FIGS. 6A and 6B, the location information of “parking lot A” includes “electric appliance purchase”, “meal”, and “movie appreciation” as destination information. These destinations (in this embodiment, the target at the destination) are accumulated.

  FIG. 29 is a diagram illustrating an example of the movement destination candidate history accumulated in the movement history accumulation unit 104. For example, the destination candidate history ID “001” includes “purchase appliances” at the destination “electric shop A” from the destination “parking lot A”, “meal” at “restaurant C”, “movie theater D”. Has been accumulated.

  The reliability value calculation unit 106 is a processing unit that calculates the reliability value of the movement destination candidate accumulated in the movement history accumulation unit 104. That is, the reliability value calculation unit 106 predicts by referring to the movement history accumulated in the movement history accumulation unit 104. The purpose corresponding to the designated arrival point is specified, and a confidence value as a destination candidate is calculated for each specified purpose. More specifically, the reliability value calculation unit 106 identifies a plurality of movement histories corresponding to the plurality of predicted arrival points from the reliability value calculation unit 106, and corresponds to the same purpose included in the plurality of identified movement histories. By adding the confidence value, a confidence value as a destination candidate is calculated for each purpose.

  Hereinafter, the function of the confidence value calculation unit 106 will be described using a specific example. FIG. 30A shows the history of the movement destination candidates accumulated in the movement history accumulation unit 104. For example, the destination candidate history ID “001” stores the destination from the destination “parking lot A” and “purchase appliances”, “meal”, and “movie appreciation” as the purpose at the destination. Yes. In addition, the destination “history purchase”, “meal”, and “book purchase” at the destination from the destination “Nishimaru Department Store” are stored in the destination candidate history ID “002”. Furthermore, in this embodiment, a confidence value is given to each destination candidate at each destination.

  The confidence value is given to each destination from each arrival point and indicates the probability that the target action (movement to the destination) is taken from that position (arrival point). The current destination is determined using this confidence value. Even if it is one arrival point, there may be a plurality of original destinations from there, and the intended purpose differs depending on the user. For example, if there is a history that the vehicle has reached “parking lot A”, it is certain that it has gone to a point called “parking lot A”, but the destination from there can “purchase electronics”. “Electric shop B”, “meal” “restaurant C”, “movie appreciation” “movie theater D” and multiple destination candidates, and it is not known what the user went to “parking lot A” for the purpose. . For example, a user may always aim at “purchasing electrical appliances” and not “watching movies” at all. On the other hand, another user may go to a location called “parking lot A” for the purpose of “movie appreciation”. Therefore, first, a reliability value (for example, 1) is given for each history of each arrival point, and the value is equally distributed for each destination from there. For example, in the case of the movement destination candidate history ID “001”, the arrival point is “parking lot A”, and the movement destination candidates “electric appliance purchase”, “meal”, and “movie viewing” are equal to “1 / 3 "is distributed. In the case of the destination candidate history ID “003”, the destination is “Hanamachi Amusement”, and “½” is equally distributed to the destination candidates “Karaoke” and “Bowling”. The In other words, even if you go to a certain arrival point, if there are multiple destinations from that point, the destination cannot be narrowed down, so this value will be low, while if the destination is limited, this value Will automatically be expensive.

  The determination of the movement destination in the present embodiment is performed using this confidence value. For example, the reliability value calculation unit 106 calculates the sum of the reliability values of the respective movement destination candidates in the movement destination candidate history, and the reliability purpose extraction unit 123 and the point information search unit 122 can select from the purposes with higher reliability values. Determine the purpose for the user to visit. That is, it is assumed that the objective α exists at a certain arrival point A. On the other hand, it is assumed that the objective α also exists at other reaching points B. In this case, although the arrival points are different, the presence of a plurality of them can be understood that the user has probably reached these points in order to carry out this purpose α, and this is regarded as a confidence value. This is reflected in the sum.

  For example, in the case of the travel destination candidate history shown in FIG. 30A, the confidence value calculation unit 106 trusts the travel destination candidate history ID “001” and one of the travel destinations “meal” at the destination “parking lot A”. From the value “1/3”, the purpose history ID “002”, and the reliability value “1/3” of the destination “meal” at the destination “Nishimaru Department Store”, as shown in FIG. "Is calculated as" 2/3 (= 1/3 + 1/3) ". Similarly, in the history example of FIG. 30A, the reliability value calculation unit 106, as shown in FIG. 30B, “4/3” as “book purchase” and “1” as “CD purchase”. The reliability value is calculated as “1/2” for bowling and karaoke, and “1/3” for purchasing electrical appliances and foods.

  The trust purpose extraction unit 123 is a processing unit that identifies a trust purpose that is a predicted action of the user based on the movement history accumulated in the movement history accumulation unit 104 and the position information acquired by the position information detection unit 101. Yes, among the purposes calculated by the reliability value calculation unit 106, an object having a higher reliability value is extracted.

  Among the purposes performed by the user accumulated in the movement history accumulating unit 104, an object with a high reliability value can be regarded as an object often performed by the user. The trust purpose extraction unit 123 calculates a trust value that is higher than the trust value of each purpose calculated by the trust value calculation unit 106. Here, “book purchase” and “CD purchase” with relatively high confidence values “4/3” and “1” are extracted. As described above, the purpose with a high reliability value calculated from the purpose history accumulated in the history is the purpose considered to be performed by the user at a predetermined point, and there may be a plurality of purposes. Also, the user may want to park these vehicles for a single purpose rather than performing these multiple purposes at different locations. Therefore, in this embodiment, a place where these multiple purposes can be achieved is searched.

  The point information search unit 122 is a processing unit that searches the point information stored in the point information storage unit 103 for the point information corresponding to the purpose with the high reliability value described above. For example, a plurality of purposes including a single purpose inputted by the above-mentioned multi-purpose input unit 131 and a purpose having a higher reliability value are searched, and points where these multi-purposes can be achieved are searched. Note that the multi-purpose input unit 131 may notify the point information search unit 122 of a plurality of purposes that combine the purpose input by the user and the trust purpose extracted by the trust purpose extraction unit 123.

  Further, the search range may be a search target in consideration of the current position of the user, the traveling direction, or the like such as a radius of 500 meters centered on the current position as shown in FIG. For example, it is assumed that the purpose “CD purchase” is first input in the multi-purpose input unit 131. On the other hand, the trust purpose extraction unit 123 calculates a purpose “book purchase” with a high trust value, and the purpose “book purchase” with a high trust value is usually intended to be fulfilled by the user with “CD purchase”. It is assumed that a search for a place where “CD purchase” and “book purchase” can be performed simultaneously is performed. In the example shown in FIG. 31, there are a parking lot J, a parking lot K, and a parking lot L within a radius of 500 meters centered on the current position, and these pieces of point information correspond. As shown in the second embodiment, the point information includes information (purpose information) related to the purpose that can be performed at the point based on the point and stores around the point.

  FIG. 32 shows an example of the acquired purpose information. The point information “001” indicates that “book purchase”, “CD purchase”, and “meal”, which are purposes in the parking lot J, can be performed. Similarly, the point information “002” indicates “book purchase” and “CD purchase” which are the purposes in the parking lot K, and the point information “003” is “CD purchase” and “tennis” which are the purposes in the parking lot L. ”And“ Swimming ”. The spot information search unit 122 extracts spot information corresponding to a purpose with a high reliability value from the searched spot information.

  In this case, point information that allows “book purchase” and “CD purchase” to be performed simultaneously is extracted. As a result, as shown in FIG. 33, two parking spots J, which are “001” and “002”, are extracted as locations where “book purchase” and “CD purchase” can be performed simultaneously. Is done. In the present embodiment, as will be described later, information on a point most suitable for the user is selected and provided in consideration of, for example, the distance between points where each purpose can be achieved among the corresponding points. The

  In recent years, with the emergence of complex facilities where various stores are integrated, there are many places that can fulfill various purposes at once. For example, there are many places where various facilities are fused so that restaurants, movie theaters, and shopping can be performed. On the other hand, when a user moves to a certain destination, there is not always one purpose that he / she wants to achieve, and there are many cases where a user seeks a place where a plurality of purposes can be completed at once. However, stores and the like that can fulfill a plurality of purposes of the user are not necessarily adjacent to each other depending on the location. For example, even in a parking lot that can fulfill a plurality of purposes such as “book purchase” and “CD purchase”, the user may need to move a long distance on foot because the store is away. Therefore, in consideration of the distance between points that can achieve each purpose, information on the point most suitable for the user is provided.

  FIGS. 34A and 34B show examples of the spot information of the parking lot J and the parking lot K. FIG. As in the second embodiment, information about a point and purpose information obtained from stores around the point are attached and accumulated. Here, the parking lot J is located at 35 degrees 16 minutes north latitude and 135 degrees 21 minutes east longitude, and “Book No. 1”, “Top record”, and “Ramen Torayoshi” exist as neighboring stores. Also, from these stores, “book purchase”, “CD purchase”, and “meal” that can be performed at that point are accumulated. Furthermore, in this Embodiment, the distance from the point (in this case parking lot J) to a store is described as information regarding a surrounding store. Here, it is written that “Book No. 1” is 200 meters from the parking lot J. Similarly, the distance to the “top record” is shown as 300 meters. As described above, the point information may store not only information on a predetermined point and the purpose there but also information such as the distance to the store. Similarly, in the location information of the parking lot K, the distance from the parking lot to the “Mori Shobo” is 50 meters, the distance from the parking lot K to the “Hamazaki CD” is 70 meters, etc. Has been.

  The distance calculation unit 124 calculates the distance that the user needs to move to achieve a plurality of purposes using the distance from the parking lot or the like described in the point information.

  FIG. 35 is a map showing the positional relationship between the parking lot J and “Book No. 1” and “Top Record”, and the positional relationship between the parking lot K and “Hamazaki CD” and “Mori Shobo”. As shown in the point information, the parking lot J and “Book No. 1” are located at a distance of 200 meters, and “Top Record” is located at a distance of 300 meters. In addition, parking lot K and “Hamazaki CD” are 70 meters away, and “Mori Shobo” is 50 meters away. Therefore, the distance calculation unit 124 calculates the distance that the user needs to move by summing up these distances. In this case, the parking lot J is 500 meters (300 + 200), and the parking lot K is 120 meters (70 + 50). Therefore, the spot information presenting unit 125 determines that the parking lot K having a short moving distance is the most suitable place that can fulfill a plurality of purposes, and provides information on the parking lot K.

  FIG. 36 is a diagram illustrating a screen display example such as car navigation by the point information presentation unit 125. The user's current position and the surrounding map, the current time “9:20”, and the like are displayed. Moreover, the information regarding the parking lot K is displayed on the upper right of the screen. Information obtained from a map of the parking lot K and its vicinity, an estimated arrival time, and point information is shown. Here, since the user is aiming at “book purchase” and “CD purchase”, information such as “new work is now in stock” as “Mori Shobo” commercial information and “Az new song” as “Hamazaki CD” commercial information. Information such as “Miracle Soul” is shown.

  Next, the operation flow of the point information search apparatus according to the present embodiment configured as described above will be described with reference to the flowcharts of FIGS.

  First, the position information storage unit 121 stores a movement history (position information). For example, since the position is detected by the position information detection unit 101 when the engine is started or the like, position information regarding the departure place is accumulated (step S101). Then, the position information is detected by the position information detection unit 101 at predetermined intervals along with the movement (step S102). Therefore, the position information storage unit 121 determines whether or not the engine has been stopped (step S103), and if the movement is performed without stopping the engine (No in step S103), determines whether or not the vehicle has passed the intersection. (Step S104). When passing through the intersection (Yes in step S104), the passing intersection is accumulated (step S105). On the other hand, if the vehicle has not passed through the intersection (No in step S104), the process returns to the position detection loop (to step S102). When the engine is stopped (Yes in step S103), the arrival point specifying unit 102 specifies the arrival point and accumulates it (step S106). The purpose at each point is accumulated in the point information accumulating unit 103 such as a server as the purpose information of the point information (FIGS. 6A and 6B, etc.). Therefore, the destination candidate specifying unit 1031 refers to the location information of the arrival point (step S107), and accumulates the purpose of the arrival point in the movement history accumulation unit 104 (step S108).

  Next, the reliability value calculation unit 106 calculates a target reliability value from the stored target history (step S303). In the present embodiment, the reliability value is calculated by, for example, the sum of the reliability values for each purpose. As shown in FIG. 30B, a “book purchase” reliability value “4/3”, a “CD purchase” reliability value “1”, and the like are calculated.

  Then, the trust purpose extraction unit 123 determines whether or not there is a purpose whose trust value is equal to or greater than a threshold value (step S304). If it exists (Yes in step S304), the process proceeds to step S305. If it does not exist (No in step S304), the process ends. If it exists (Yes in step S304), the purpose equal to or higher than the threshold is set as the trust purpose (step S305). For example, if the threshold is “1”, a plurality of purposes “book purchase” and “CD purchase” are calculated.

  Next, the point information search unit 122 searches the trust purpose together with one purpose input from the user via the multi-purpose input unit 131, for example, “book purchase” (step S401), and has a predetermined value. The point information of the range is acquired from the point information storage unit 103 (step S402). For example, as shown in FIG. 31, point information within a radius of 500 meters with the current position as the center is acquired. And the spot information search part 122 determines the presence or absence of the spot information which has the objective to search among the acquired spot information (step S403). If it exists (Yes in step S403), the process proceeds to step S404. If it does not exist, the process ends (No in step S403). Further, the spot information search unit 122 determines whether or not there are a plurality of corresponding spots (step S404). If it exists, the process proceeds to step S405. If it does not exist (No in step S404), that is, in the case of one, the spot information presentation unit 125 presents information related to the spot information (step S408).

  In the example shown in FIG. 32, for the search purposes “book purchase” and “CD purchase”, the point information having both purposes corresponds to “parking lot J” and “parking lot K”. (Yes in step S404). Therefore, the distance calculation unit 124 refers to the information regarding the distance of the point information after step S405 (step S405), and calculates the distance of the point that can serve multiple purposes (step S406).

  As shown in FIGS. 34 (a) and (b) and FIG. 35, the distance from "Parking J" to "Book 1" is 200 meters, and the distance from "Parking J" to "Top Record" is In order to fulfill these multiple purposes, 300 meters, it is necessary to move a total of 500 meters. On the other hand, the distance from “Parking Lot K” to “Mori Books” is 50 meters, and the distance from “Parking Lot J” to “Hamazaki CD” is 70 meters, a total of 120 meters to fulfill these multiple purposes. It will be necessary to move. Accordingly, the spot information presenting unit 125 presents information on “parking lot K” (step S408), assuming that “parking lot K” is a more efficient place to fulfill a plurality of purposes (step S407). . FIG. 36 shows a screen display example in which information is presented with “parking lot K” as the destination.

  As described above, according to the present embodiment, the purpose of the subsequent action (destination) is estimated based on one movement sequence (or one arrival point), and a plurality of purposes combined with the purpose designated by the user are estimated. Information on the most suitable point to achieve the objective efficiently was provided. Thus, the user can be freed from a troublesome operation of inputting a plurality of purposes, and can know a convenient point where the plurality of purposes can be efficiently achieved in a short time.

  In the present embodiment, the plurality of purposes are composed of the input purpose and the predicted purpose having a high reliability value, and a point where the plurality of purposes can be achieved simultaneously is searched. The present invention is not limited to this.

  For example, a point search may be performed for only one purpose that has been performed at the same time as the past, based on the history of the purpose stored in the movement history for one input purpose. Hereinafter, a specific example will be described. FIG. 39A shows a target history accumulated in the movement history accumulation unit 104. Here, the ID “001” has a history of reaching the point “parking lot A”, and the purpose “meal” and “movie appreciation” there are accumulated. Further, when the reliability values for these purposes are calculated, as shown in the destination-specific reliability value 211, the reliability values for the purposes “book purchase” and “CD purchase” are “4” as shown in FIG. 39 (b). / 3 "is the highest. Thus, for example, when the purpose “movie appreciation” is input, a point where these high-confidence values are another purpose, and “movie appreciation”, “CD purchase”, and “book purchase” can be performed simultaneously. You may search for.

  By the way, these high-reliable purposes are often performed by users, but they do not always want to be performed at the same time as “movie appreciation”. For example, in the case of the user shown in this example, since “CD purchase” and “book purchase” are performed at the same time, they frequently exist in the history and the result has a high reliability value. ”, There is a tendency to eat later, and the history also stores a lot of history of places where the purpose of“ movie watching ”and“ meal ”can be performed simultaneously. Therefore, it is also possible to consider not only the purpose with a high reliability value but also the purpose performed at the same time. For example, in the target history shown in FIG. 39A, when only the purpose of “movie appreciation” is focused, history IDs “001”, “002”, and “006” are applicable. When the reliability values for these purposes are calculated, as shown in FIG. 39C, the reliability value for the purpose “meal” is the highest, “5/3”. That is, when the purpose “watching a movie” is performed, “meal” is being performed at the same time. Therefore, when the purpose “watch movie” is input by the user, “meal” that is often performed at the same time based on the history is used as the other purpose, and a search for a place that can simultaneously fulfill these multiple purposes is performed. Information may be provided.

  Further, the distance between points in the present embodiment is calculated using, for example, a linear distance expressed in units of meters, but the present invention is not limited to this. For example, in order to perform a route search for pedestrians, map information dedicated to pedestrians is further provided, and a cost is calculated by searching the distance between points using the map information dedicated to pedestrians. It is good also as providing a point.

  That is, after the user parks the vehicle, the user generally moves on foot between stores that can fulfill these multiple purposes. Therefore, instead of simply using a straight distance, the cost of moving between these stores on foot is calculated using, for example, walking-only map information, etc. It is possible to provide a destination that reflects the sense of distance when the user actually moves on foot. In recent years, a pedestrian-specific navigation system has appeared in mobile terminals, and this pedestrian-specific navigation uses a pedestrian map to perform a route search, unlike a vehicle route search in a so-called car navigation system. It is common. For example, the route cost is calculated taking into account the presence or absence of a pedestrian sidewalk, the width of a pedestrian crossing, etc., so it is not just a straight distance, but a sense of distance when the user actually moves on foot. It becomes possible to calculate by. Therefore, in this embodiment, not only the distance between stores for a plurality of purposes but also a route cost when moving between the stores on foot is calculated, and a destination more suitable for the user is provided in consideration of the cost. It is good as well. Furthermore, a means for acquiring information such as the weather may be newly provided, and in the case of rainy weather, a point with an underground walkway may be recommended even if the distance is slightly longer.

(Embodiment 4)
Next, a fourth embodiment of the present invention will be described.

  In the third embodiment, the point information accumulated by associating the point and the purpose performed at the point is stored, the purpose at the user's destination is accumulated, the user's favorite purpose is grasped, and more A method for providing appropriate destinations was explained. When a user moves, the purpose at the destination is not limited to one, and the user may move to fulfill a plurality of purposes. Furthermore, when moving by car, there is often a desire for a place where the purpose can be achieved as efficiently as possible, such as parking only once. At this time, it is convenient that the user's purpose can be grasped using the point information and a place where the purpose can be efficiently achieved can be recommended in consideration of the distance and the like. Furthermore, it is desirable to accumulate the purpose of the user's destination using the point information, predict the destination based on the user's current travel route, and further estimate the purpose of the destination. .

  2. Description of the Related Art Conventionally, a mobile terminal such as a car navigation system has a method of predicting a destination point from an accumulated user movement history and providing information.

  However, in the conventional destination prediction apparatus, the predicted arrival point is a point only and does not predict from the arrival point to the destination that the user originally intended. For example, if the location accumulated as the user's history is a parking lot, and there are several stores in the vicinity of the parking lot, even if it can be predicted to that parking lot, which store to go to That is, it does not predict the original destination. In addition, the user may visit a plurality of stores with one parking and reach the point, that is, the parking lot, in an attempt to finish the intended business at each store. In this case, when providing information according to the purpose of the user in advance, even if only the parking lot to be reached can be specified, it is not possible to provide accurate information in consideration of the destination.

  Therefore, the present embodiment accumulates, as a history, point information having a destination from the user's arrival point or a purpose at the destination, and identifies the original destination based on the accumulated history. It is possible to provide information on the destination to be moved.

  FIG. 40 is a block diagram showing an overall configuration of the point information search apparatus according to Embodiment 4 of the present invention. This point information search device is a device that provides information according to a predicted destination, and includes a mobile terminal 100 that is an information providing device such as car navigation and a point information storage unit 220a. The mobile terminal 100 further includes a position information acquisition unit 210a, a multi-purpose acquisition unit 230c, a search unit 240d, and an information provision unit 250a. This point information search apparatus has basically the same configuration as the point information search apparatus in Embodiment 3 as an overall functional configuration, except that it includes a multi-purpose acquisition unit 230c instead of the multi-purpose acquisition unit 230b. Different from the third embodiment.

  The multi-purpose acquisition unit 230b corresponds to the processing unit that acquires information for specifying a plurality of purposes for a purpose that is an action desired by the user, that is, the multi-purpose acquisition unit 230 in the first embodiment. , The destination point specifying unit 102, the destination candidate specifying unit 1031, the movement history accumulating unit 104, the destination point predicting unit 105, the confidence value calculating unit 106, the trust purpose extracting unit 123, and the multipurpose input unit 131 are included. The reliability value calculation unit 106 is a processing unit that calculates a destination from the predicted arrival point. As illustrated in FIG. 41, the reliability value calculation unit 1061 further includes a trust destination determination unit 1061, a destination reliability value recalculation unit 1062, The destination search unit 1063 is configured.

Hereinafter, a description will be given focusing on differences from the first to third embodiments.
The position information detection unit 101 is a processing unit that detects the current position of the mobile terminal 100. The position information detection unit 101 is configured by, for example, a GPS antenna provided in a mobile terminal and detects the latitude / longitude information of the user. As in the third embodiment, position information is detected at predetermined intervals as the user moves (FIGS. 26, 27, and 28).

  The conventional destination prediction apparatus accumulates these arrival points, and predicts the arrival point at the time of the current travel using the accumulated arrival point history. For example, if there is a point that has reached in the past in the current traveling direction, that point can be set as the predicted arrival point. Alternatively, it is accumulated as a set of departure point, passage route, and arrival point, and when the current travel and the accumulated route coincide, the arrival point on the coincidence route is set as the predicted arrival point. .

  On the other hand, in these conventional destination prediction apparatuses, what is predicted is only a point, and a destination from that point is not predicted. For example, as shown in FIG. 28, if the vehicle has reached the parking lot A, it can be predicted that the vehicle will go to the parking lot A, but the user's original destination at that point is the destination. Cannot be predicted. For example, after reaching a parking lot A, a user may move to an electrical shop B to purchase an appliance. Or you may visit Movie Theater D to watch a movie. Therefore, even if information is provided to the user, the destination cannot be specified, and thus accurate information cannot be provided. For example, in the former case, it is preferable that the information to be provided is sale information at the electrical store B, and in the latter case, it is preferably the movie show time information. In the case of a car navigation system, it is not preferable to disturb the driving task, so it is necessary to provide information according to the destination and purpose of the user rather than providing information on all of these destination candidates.

  Therefore, in the present embodiment, the above-described “point information” is used in order to identify the arrival point, the destination from the arrival point, and the purpose at the destination. For example, in FIG. 28, it is assumed that the user has reached “parking lot A”. Here, by accumulating “parking lot A” as a history, it is possible to predict from the conventional method to the destination “parking lot A”. It is not possible to predict the destination of the move. However, since the location information shows that there are “appliances shop B”, “restaurant C”, and “movie theater D” in the vicinity of “parking lot A”, consider at least these nearby stores as destination candidates. Will be able to. Furthermore, in the present embodiment, a history of point information of past arrival points is accumulated, and the current destination is predicted based on the history. For example, it is possible to accumulate a destination candidate at a past arrival point or information indicating the purpose of the destination candidate and predict the current destination based on the information.

  As shown in FIGS. 6A and 6B, the spot information of “parking lot A” has “purpose information” as attribute information. For example, since “home appliance shop B” can purchase home appliances, there is “electric shop B” as one of the destination candidates for the user who came to “parking lot A”. There is a purpose “purchase home appliances” in Japan, and the information is registered as purpose information. Alternatively, there is “restaurant C” as another destination candidate, and it is possible to eat there, so “meal” is registered as the purpose information. Furthermore, there is “movie theater D” as a destination candidate, and the purpose “movie appreciation” is registered there. In this way, the point information reflects, as one of the information related to the point, for example, the store of the destination candidate from the point, the purpose of the action at the store, based on the store in the cover area. Has purpose information. In the present embodiment, the purpose information is stored together with the movement history, and the determination is made based on the history of the purpose information.

  The movement history accumulation unit 104 is a processing unit that accumulates a movement history including a user's arrival point and a purpose of a destination candidate from the arrival point, and includes a hard disk or the like inside. For example, based on the arrival point specified by the arrival point specifying unit 102, the purpose information of the point information stored in the point information storage unit 103 is acquired, and the destination candidate specifying unit 1031 is used as the destination destination candidate. It is identified and stored in the movement history storage unit 104.

  Further, in the present embodiment, in order to predict the arrival point from the movement history, the movement history accumulation unit 104 simultaneously accumulates the departure place, the route that has passed, and the movement history of the arrival place. First, the movement history will be described.

  As shown in FIG. 26, it is assumed that the user who has left home and has passed through the first intersection, the second intersection, and the third intersection has reached “parking lot A” as shown in FIG. To do. The movement history accumulation unit 104 accumulates this as a user movement history.

  FIG. 42 shows an example of the accumulated movement history. As the travel history ID “001”, depart from “Home” on the date and time “Saturday, January 8, 2005, 10:00” and pass through the first intersection, the second intersection, and the third intersection. The history of reaching “A” is accumulated.

  Furthermore, the movement history accumulating unit 104 accumulates the movement destination from the reached point, that is, the movement destination candidate in the “parking lot A” based on the movement destination candidate information of the point information. For example, as shown in FIGS. 6A and 6B, “Purchase of electrical appliances”, “meal”, and “movie appreciation” are registered in the spot information of “parking lot A” as destination information. The movement history accumulating unit 104 accumulates these movement destinations (the purpose of the movement destination in this embodiment).

  FIG. 43 is a diagram illustrating a history example of destination candidates accumulated in the movement history accumulation unit 104. Here, the destination candidate history ID “001” is “Purchase of electrical appliances” at the destination “Electric Shop A” from the destination “Parking A”, “Meals” at “Restaurant C”, “Movie Theater D”. “Movie watching” is accumulated.

  First, in this Embodiment, a user's arrival point is estimated from a movement history. The arrival point prediction unit 105 is a processing unit that predicts a user's arrival point from the current position detected by the position information detection unit 101 and the movement history accumulated in the movement history accumulation unit 104.

  For example, as shown in FIG. 44, it is assumed that the user has left the home and turned right at the first intersection. Here, the arrival point prediction unit 105 predicts where the user is going. Note that the starting point of the prediction may be performed, for example, when a predetermined number (for example, the first) of intersections is passed, or may be a predetermined time (for example, 5 minutes later) after departure.

  On the other hand, FIG. 45A shows an example of the movement history accumulated in the movement history accumulation unit 104. In the movement history ID “001”, the history of departure from “home”, passing through the “first intersection”, “second intersection”, “third intersection” and reaching “parking lot A” is accumulated. Yes. Similarly, the movement history ID “002” is a history of leaving “home” and arriving at “parking lot A” via “first intersection”, “second intersection”, and “third intersection”. is there. In this way, movement that frequently exists in the history is extracted as a prediction candidate, for example, as an action pattern often performed by the user, as shown in FIG. 45B. In FIG. 45B, the departure point “home”, the transit point “first intersection”, “second intersection”, “third intersection”, and the arrival point “parking lot A” are extracted as the prediction candidate ID “001”. Has been.

  From the movement example shown in FIG. 44, since the position information detection unit 101 detects that the current user leaves “home” and passes “intersection 1”, the arrival point prediction unit 105 matches the prediction candidate. By doing so, it becomes possible to predict the arrival point. In this case, since the departure point “home” of the prediction candidate ID “001” matches the route “first intersection”, it can be predicted that the vehicle will reach “parking lot A”. Various methods for predicting the arrival point based on the movement history have been disclosed heretofore, and are not questioned here.

  Furthermore, in the present embodiment, the destination from the destination “parking lot A” is determined. The reliability value calculation unit 106 is a processing unit that determines a destination from the arrival point based on the predicted arrival point predicted by the arrival point prediction unit 105 and a history of destination candidates accumulated in the movement history accumulation unit 104. .

  For example, in the case of the movement of the user shown in FIG. 44, the predicted destination is “parking lot A”, and the destination candidate from there is “electrification from point information (FIGS. 6A and 6B). "Product purchase", "Meals", "Movie appreciation". Therefore, determination is made based on the destination candidate history from these destination candidates.

  FIG. 46A is a diagram showing the history of the movement destination candidates accumulated in the movement history accumulation unit 104. Here, in the destination candidate history ID “001”, “purchase appliances”, “meal”, and “movie appreciation” are accumulated as destinations from the destination “parking lot A” and purposes at the destination. Yes. In addition, the destination “history purchase” and “meal” at the destination from the destination “Nishimaru Department Store” are accumulated in the destination candidate history ID “002”. Furthermore, the reliability value shown above is given to each destination candidate at each destination. For example, in the case of the destination candidate history shown in FIG. 46, the destination candidate history ID “002”, the reliability value “1/2” of one of the destinations “grocery purchase” at the destination “Nishimaru Department Store”, the purpose history ID “004”, trust value “1/2” of destination “grocery purchase” at destination “Donkey Super”, purpose “grocery purchase” at “super Hanamachi” of destination candidate history ID “005” As shown in FIG. 46B, the target “food purchase” is “3/2 (= 1/2 + 1/2 + 1/2)” from the reliability value “1/2” of the above. Similarly, “Furniture purchase” is 1, movie appreciation, meal is “5/6”, bowling “1/2”, and appliance purchase “1/3”.

  For example, it is assumed here that the user is predicted to reach “Nishimaru Department Store”. On the other hand, it is assumed that the purpose candidates at “Nishimaru Department Store” are “grocery purchase” and “meal”. At this time, with reference to the above-described reliability values for each object, the object having a higher value is determined as the user's object. For example, as shown in FIG. 46C, in this case, the confidence value of “grocery purchase” is “3/2”, which is higher than the confidence value “1/2” of the meal. It is determined that “groceries are purchased”. This means that the user's purpose, which is not known simply by reaching “Nishimaru Department Store”, is determined based on the purpose at another point reached by the past user. In other words, at the points “Donky Super” and “Super Hanamachi” reached by past users, there is a possibility that the purpose “Purchase of grocery” will be performed, and since the trust value of these purposes “Purchase of food” is high, “Nishimaru Department Store” also determines that “purchase of food” is the purpose. Thus, the user's purpose can be determined by considering the purpose at another point. Furthermore, in the present embodiment, the purpose determination not only uses an object with a high reliability value but also considers a feature in which a plurality of objects are accumulated corresponding to one point. Hereinafter, an example in which “parking lot A” is predicted as the arrival point (FIG. 46B) will be described.

  As shown in FIG. 46B, the purpose candidates for “parking lot A” are “purchase of electric appliances”, “meal”, and “movie appreciation”. On the other hand, as shown in FIG. 46 (c), the sum of the reliability values for each object is calculated from the object history. The confidence value of “purchase electronics” is “1/3”, the confidence value of “meal” is “5/6”, and the confidence value of “watch movie” is “5/6”. In other words, simply by the sum of the confidence values, the confidence values of the objects “meal” and “movie viewing” are equal, and in this case, determination cannot be made. Further, simply by summing the reliability values, the purpose of frequently existing in the history is determined as a result, and the user's characteristics cannot necessarily be reflected. Therefore, a feature in which a plurality of purposes are accumulated corresponding to one point is considered. A feature in which a plurality of purposes are accumulated corresponding to one point is, for example, that even if there are a plurality of purposes at a certain arrival point, not all of the purposes that the user wants are obtained. Specifically, for example, the purposes of “Nishimaru Department Store” with the purpose history ID “002” are “purchase of food” and “meal”, and a confidence value “1/2” equal to these is given. However, the user's purpose is actually that it can be determined as either of them in some cases. For example, if “grocery purchase” is highly reliable by considering the purpose at other destinations, the purpose at “Seibu Department Store” is also considered as “grocery purchase”, and at the same time as the history The confidence value can be reduced as it is not the other purpose “meal” that existed at the same value. Along with this, a difference occurs between the purpose “meal” and “movie appreciation”, which is the same value as the sum of the reliability values, and it can be determined as “movie appreciation”. An example is shown in FIGS. 47A to 47C using specific numerical values.

  FIG. 47 (b) shows the sum of the effective values of the objectives from each objective history. For example, the trusted destination determination unit 1061 sets a threshold value (for example, a reliability value of 1 or more), and determines an object with a high reliability value as a reliability object. As shown in FIG. 47 (c), “grocery purchase” and “furniture purchase” having a confidence value equal to or greater than a threshold value are determined as the trust purpose. The trust object is an object that at least this object can be trusted with a high probability because the reliability value is high. There are multiple candidates for the purpose at the point, and it is not easy to determine the purpose from among them. On the other hand, the purpose intended by the user is generally performed in relatively various places regardless of the point. It is. For example, if a housewife visits many places such as general stores, greengrocers, department stores, etc., using a car, “grocery purchases” that are commonly associated with these destinations have a relatively high probability. It is common to be reliable. Therefore, in order to determine these reliable purposes, the sum of the reliability values is calculated, and the higher one is set as the reliability purpose.

  Next, the destination trust value recalculation unit 1062 calculates the confidence value again using the purpose determined as the trust purpose. For example, as shown in FIG. 47C, “grocery purchase” and “furniture purchase” are determined as the trust purposes. That is, it is assumed that there is a low possibility that another purpose has been performed at the arrival point where these trust objectives exist, and these trust values can be reduced. For example, the reliability value of “meal” of the purpose history ID “002” is changed from “1/2” to “0”, and the value is added to “food purchase”. The confidence value of “food purchase” has increased from “1/2” to “1”.

  Then, a confidence value for each purpose is calculated again. Then, as shown in FIG. 47 (d), the confidence value for “grocery purchase” is “2”, the confidence value for “furniture purchase” is “1”, and the confidence value for “movie viewing” is “5/6”. ”, The meal confidence value is“ 1/3 ”, etc., and there is a difference in the confidence value for each purpose. This is a result of considering a reliable purpose and considering a characteristic considered to be one, for example, although there are a plurality of purposes at each point, but not all of the original purposes.

  Here, the destination search unit 1063 refers to the predicted destination candidate “parking lot A” and searches for “movie appreciation” with the highest reliability value, and determines that it is the purpose.

  48, the information providing unit 250a provides the user with the information searched by the search unit 240d based on the arrival point predicted by the arrival point prediction unit 105 and the purpose determined by the reliability value calculation unit 106. An example is shown. Here, since the user has moved to the “parking lot A” for the purpose of “movie viewing” after passing the “first intersection”, the “arrival time 11:20” and a screening that takes this time into consideration are also shown. It is possible to provide information that the user wants to grasp in advance, such as time search.

  Next, the operation of the point information search apparatus according to the present embodiment configured as described above will be described with reference to flowcharts (FIGS. 49, 50, and 51). The operation flow of the present embodiment is roughly divided into an accumulation step for history and the like, and a step for predicting the destination and the purpose at the arrival point based on the accumulated history and the like. First, a history accumulation step will be described.

  First, the movement history accumulation unit 104 accumulates a movement history. In the present embodiment, the movement history is accumulated in the movement history accumulation unit 104 as a set of departure point, passing intersection, and arrival point in order to predict the arrival point. For example, since the position is detected by the position information detection unit 101 by engine start or the like, the movement history accumulation unit 104 accumulates the departure place (step S101). Then, the position information is detected at predetermined intervals along with the movement (step S102). Therefore, it is determined whether or not the engine has been stopped (step S103). If the movement is performed without stopping the engine (No in step S103), it is determined whether or not the vehicle has passed the intersection (step S104). When the vehicle passes through the intersection (Yes in step S104), the movement history storage unit 104 stores information on the passing intersection (step S105). On the other hand, if the vehicle has not passed through the intersection (No in step S104), the process returns to the position detection loop (to step S102). When the engine is stopped (Yes in step S103), the arrival point specifying unit 102 specifies the arrival point and stores it in the movement history storage unit 104 (step S106).

  For example, when the user performs the movement shown in FIG. 26, “home” is accumulated in the movement history accumulation unit 104 as a departure point (step S101), and the “first intersection”, “second intersection”, “ The “third intersection” is accumulated in the movement history accumulation unit 104 (loop from step S102 to S105). When the engine is stopped at “parking lot A” shown in FIG. 8 (Yes in step S103), “parking lot A” is accumulated in the movement history accumulation unit 104 as a destination. FIG. 13 shows an example of the movement history accumulated in the movement history accumulation unit 104. Here, the vehicle departs from “home” and passes through the “first intersection”, “second intersection”, and “third intersection”. The history of reaching “parking lot A” is accumulated.

  On the other hand, the purpose at each point is accumulated in the point information accumulating unit 103 such as a server as the purpose information of the point information (FIGS. 6A and 6B, etc.). Therefore, the point information of the arrival point is referred to (step S107), and the destination candidate identification unit 1031 accumulates the purpose of the arrival point in the movement history accumulation unit 104 (step S108).

  For example, FIGS. 6A and 6B show point information of “parking lot A”, in which “electrical appliance purchase”, “meal”, and “movie appreciation” are described as purpose information. Yes. By referring to this (step S107), for example, as shown in FIG. 43, the purpose stored in the movement history storage unit 104, for example, the purpose history ID “001” is “parking lot A”. Purposes “Purchase electrical appliances”, “Meals”, “Watch movies” are accumulated.

  Next, an operation flow for predicting the arrival point based on the accumulated movement history will be described. First, the arrival point prediction unit 105 detects, for example, a departure place based on position information detected by engine start (step S201). With the movement, position information is detected by the position information detection unit 101 (step S202). The arrival point prediction unit 105 determines whether or not the vehicle has passed the intersection (step S203), and if not (No in step S203), repeats these detection loops. On the other hand, when the vehicle has passed the intersection (Yes in step S204), the arrival point prediction unit 105 refers to the movement history accumulated in the movement history accumulation unit 104 (step S204). Then, the arrival point prediction unit 105 determines whether or not there is a history that matches the current travel (step S205). If there is a corresponding history (Yes in step S205), the arrival of the corresponding history is reached. The point is set as a predicted arrival point (step S206).

  For example, as shown in FIG. 44, it is assumed that the user leaves “home” (step S201) and passes the first intersection (step S204). In the movement history shown in FIG. 45 (a), there is a history of leaving “home”, passing through the “first intersection”, etc., and reaching “parking lot A” (Yes in step S205). The prediction unit 105 sets “parking lot A” as the predicted arrival point (step S206).

  Next, the reliability value calculation unit 106 determines the purpose at the predicted arrival point. First, the purpose at the predicted arrival point is referred to (step S301). Then, the target history is referred to (step S302), and the target confidence value is calculated (step S303). For example, the predicted arrival point is “parking lot A”, and the purposes are “purchase of electric appliances”, “meal”, “movie appreciation” (from the point information of FIGS. 6A and 6B), The determination is made from these. The determination is based on the target history stored in the movement history storage unit 104. FIG. 46A shows the target history. First, the confidence value calculation unit 106 calculates a confidence value for each purpose. For example, by calculating the sum of the reliability values equally distributed for each destination, the reliability value for each purpose is obtained. In this case, as shown in FIG. 46 (c), the confidence value for “grocery purchase” is “3/2”, the confidence value for “furniture purchase” is “1”, and the confidence value for “watch movie” is “ 5/6 ".

  Next, the confidence value calculation unit 106 determines whether or not there is a trust purpose whose trust value is equal to or greater than a threshold (for example, 1) (step S304), and the purpose equal to or greater than the threshold is regarded as a trust purpose (step S305). ). In this case, “purchase of food” and “furniture purchase” are determined to be the trust purposes.

  Subsequently, the confidence value calculation unit 106 searches whether or not these trust objectives exist in each objective history. For example, the purpose history ID “001” is set to start (step S306), and it is determined whether or not a trust purpose exists in the purpose candidates of each purpose history (step S307). In FIG. 47 (a), since these trust objectives do not exist in the objective history ID “001” (No in step S307), it is determined whether or not the next objective history exists (step S309), and the objective history ID is determined. Since “002” exists (Yes in step S309), the target history ID “002” is set (step S310). Then, it is determined whether or not these trust objectives exist in the objective history ID “002” (step S307). Since they exist (step S308), objective candidates other than the trust objective are reduced. For example, since the purpose history ID “002” has the trust purpose “purchase of food”, the trust value of “meal” other than this is decreased. The confidence value of “food purchase” is “1”, and the confidence value of “meal” is “0”. Repeat the same loop.

  When these loop processes are performed and the target history does not exist (No in step S309), that is, after performing these processes on all the target histories, the destination reliability value recalculation unit 1062 The confidence value is recalculated (step S311). The recalculated result is as shown in the reliability value for each purpose (FIG. 47 (d)).

  The destination search unit 1063 determines whether or not there is a purpose corresponding to the purpose of the predicted destination “parking lot A” (step S312). If there is a target (Yes in step S312), the destination search unit 1063 The purpose is determined (step S313). In this case, the reliability value of “movie viewing” is the highest, “5/6”, compared to the reliability value “1/3” of “meal” and the reliability value “1/3” of “purchase appliance”. It is determined that the purpose is “movie appreciation”. Finally, as in the third embodiment, the search unit 240d searches for information related to the purpose determined by the destination search unit 1063, and the information providing unit 250a provides the searched information to the user.

  48, the information providing unit 250a provides the user with the information searched by the search unit 240d based on the arrival point predicted by the arrival point prediction unit 105 and the purpose determined by the reliability value calculation unit 106. An example is shown.

  Since the user has moved to “parking lot A” for the purpose of “movie viewing” after passing the “first intersection”, the search time for “showing arrival time 11:20” and further taking this time into consideration is searched. For example, it is possible to provide information that the user wants to grasp in advance.

  As described above, according to the present embodiment, the arrival point of a vehicle such as a parking lot is predicted based on the point information and the movement history without performing an input operation, and further based on the arrival point, The original purpose of watching a movie is predicted, and information according to the purpose is provided to the user. Therefore, the user can obtain useful information before arriving at the destination in a manner in which the destination in the car is distinguished from the original destination after getting off the car.

  In the present embodiment, the reliability value is evenly distributed for each target candidate at each destination, but the reliability value may be preliminarily given with a slope (weight) depending on the purpose. For example, when many users go to a point with a certain purpose, a high confidence value is set in advance for the purpose at that point, which is reflected in the purpose determination in this method. Become. For example, it is assumed that there are a plurality of candidates for a purpose such as a purpose “buy book”, “purchase electrical appliance”, and “cherry-blossom viewing” for a certain “parking lot D”. On the other hand, it is assumed that many other users have reached the purpose of “cherry blossom viewing”. In this case, by setting a high value of the “cherry blossom viewing” in advance, it is possible to use many other purposes. Furthermore, time, day of the week, time, etc. may be taken into consideration in this method. For example, even if a user usually aims to “book purchase” to “parking lot D”, such as April, when many other users arrive for the purpose of “cherry-blossom viewing”, these The purpose of other users will be reflected. Alternatively, it is possible to incline the reliability value by using the user's own operation or the like. For example, when it is not known whether “movie watching” is intended or “boring” is intended, both pieces of information may be provided, and a high reliability value may be given to the user's selection.

  Further, in the present embodiment, in order to determine the purpose at the user's arrival point, a reliability value is given to the purpose at each point that the user has reached in the past, and the purpose is determined based on this reliability value. . For example, the sum of the confidence values is obtained and the object is a high value. As a result, it is possible to reflect the user's behavioral characteristics that the purpose that would have been performed at many other points in the past is likely to be the purpose at the current predicted arrival point. . However, the present invention is not limited to the requirement for determining the purpose of the user. For example, the purpose of the user can be determined according to time, day of the week, or area. Therefore, here, a modified example in consideration of these parameters will be described.

  FIG. 52 is a block diagram showing the configuration of the point information search apparatus (configuration centered on the confidence value calculation unit 106a) in Modification 1 of the present embodiment. This point information search apparatus basically has the same configuration as that of the point information search apparatus of the fourth embodiment, but the reliability value calculation unit 106a is added to the configuration of the fourth embodiment (FIGS. 40 and 41). A purpose determination condition storage unit 1064 and a purpose determination condition setting unit 1065.

  The purpose determination condition storage unit 1064 is a storage device or the like in which conditions for determining the purpose by reflecting the characteristics of user behavior are stored.

  FIG. 53 shows an example of conditions stored in the purpose determination condition storage unit 1064. Here, conditions of a question format for asking a day of the week such as “holiday” or “weekday” are accumulated. The conditions are accumulated as a tree structure, for example. Here, conditions are accumulated in the upper concept such as holiday or weekday at the upper level of the tree, and conditions of the lower concept are stored at the lower level of each condition. In the example of FIG. 53, a condition “Saturday” or “Sunday” is stored below the superordinate concept “holiday”, and a condition such as “AM” or “PM” is stored below “Saturday”. Yes.

  In this modification, this condition is set by the purpose determination condition setting unit 1065, and the reliable movement destination determination unit 1061 uses the condition and the target history accumulated in the movement history accumulation unit 104 to determine the predicted destination of the user. Precisely predict the purpose of For example, some users have characteristics that have different purposes depending on the day of the week. These users have different characteristics such as traveling for work on weekdays, entertainment on holidays, and sports on Saturdays, and it is necessary to set conditions according to the users. Hereinafter, the operation of the point information search apparatus will be described using a specific example.

  FIG. 54A shows a user's purpose history accumulated in the movement history accumulation unit 104. Here, the purpose history ID “001” reaches “parking lot A” on the date “January 1, 2005 (Sat)”, and the purpose candidate for “parking lot A” is “purchase electronics”. , “Meal” and “movie watching”. On the other hand, the purpose history ID “003” reaches “Hanamachi company” on the date and time “Monday, January 11, 2005”, and the candidate for the purpose of “Hanamachi company” is “company”. It has been shown. In addition, since the user uses for commuting, it is assumed that the movement history to this “Hanamachi company” exists frequently.

  In this case, as shown in FIG. 54 (c), it may not be possible to accurately reflect the behavioral characteristics of the user with only the sum of the confidence values. For example, as shown in FIG. 54B, it is assumed that the destination “parking lot D” is predicted by the movement of the user. Further, it is assumed that the purpose candidates in “parking lot D” are “movie appreciation” and “meal”. In this case, the reliability value of the purpose “work” is as high as “4”. For example, when the purpose of the highest reliability value is aimed, there is no purpose candidate corresponding to “work”, so the purpose is accurately set. It cannot be determined. Further, in this case, the reliability value of the purpose “work” is a value that happens to be high because the commuter is usually commuting on weekdays, and may not be suitable for determining the purpose of the user.

  Therefore, in this modification, the trusted destination determination unit 1061 uses the conditions stored in the purpose determination condition storage unit 1064. For example, since the current movement to “parking lot D” is “Saturday, January 20, 2005”, the condition “holiday” is used. Using the condition “holiday” set by the purpose determination condition setting unit 1065, the trusted destination determination unit 1061 extracts only the holiday history from the target history. FIG. 55 (a) shows an example of a holiday purpose history (movement on weekdays is indicated by diagonal lines and is not considered). When the reliability value is calculated by the reliable movement destination determination unit 1061 from the holiday purpose history, the highest reliability value is “5/6” “movie appreciation” and “5/6” as shown in FIG. "Meal". That is, it is possible to more accurately reflect the user's behavioral characteristics that could not be reflected by simply calculating the reliability value of the objective history by setting the conditions.

  On the other hand, as shown in FIG. 55 (b), since both “movie viewing” and “meal” exist in the destination candidates of the predicted destination “parking lot D”, the purpose determination condition setting unit 1065 further sets the condition Is set. For example, since the current movement is performed on Saturday, January 22, 2005, “Saturday”, which is a subordinate concept of the condition “holiday”, is set. Of the purpose histories, “Saturday” corresponds to “Saturday” when the destination reliability value recalculation unit 1062 recalculates the reliability values for these purposes from the purpose history IDs [001] and “007”. "Is the confidence value" 5/6 ", the confidence value of the purpose" meal "is" 1/3 ", and the purpose of the current movement can be determined to be" movie appreciation "(FIGS. 56A to 56C). )). In this way, by further accumulating the conditions of the lower concept in the conditions, it is possible to automatically set conditions that can reflect the user's behavior characteristics most accurately.

  Note that the method for determining which condition is used and which hierarchy most reflects the user's behavior characteristic is not limited to this. ID3 (Induction of Decision Trees) Conventionally disclosed methods such as algorithm) may be used.

  In addition, the conditions for reflecting the user's behavior are not limited to the day of the week and the time, but the cycle of the behavior, the previous purpose, and the like may be considered. For example, the purpose may be determined in a cycle such as every other day instead of the day of the week. It is also possible to consider the previous purpose. For example, if the purpose was “meal” last time, even if “meal” is the target candidate for the predicted arrival point this time, it will not be a meal again, and the confidence value will be lowered and judged from other purposes May be.

  In addition, the characteristics of the user's behavior can be reflected by considering the area and the like. Hereinafter, the point information search apparatus according to the second modification of the present embodiment that determines the purpose reflecting the user behavior characteristics by considering the area will be described using a specific example.

  FIG. 57A shows a user's purpose history accumulated in the movement history accumulation unit 104 according to the second modification. Here, the purpose history ID “001” reaches “parking lot A” on the date and time “January 1, 2005 (Sat)”, and the purpose candidate in “parking lot A” is “purchase of food”. , “Purchased medicine” and “Furniture purchased”. In addition, the purpose history ID “003” reaches “parking lot B” on the date and time “Monday, January 10, 2005”, and the candidate for the purpose in “parking lot B” is “grocery purchase”, “ It is shown that it was “book purchase”.

  FIG. 58 shows the positional relationship between “parking lot A” and “parking lot B”, which are these arrival points, on a map. It can be seen that “parking lot A” and “parking lot B” are near the user's home. In other words, the user is performing the purpose “buy food” or the like in the “parking lot A” and “parking lot B” near the home.

  On the other hand, the history of reaching “parking lot D” and “parking lot E” is also stored in the purpose history of FIG. For example, the purpose history ID “002” reaches “parking lot D” on the date and time “January 9, 2005 (Sunday)”, and the candidate candidates for “parking lot D” are “movie viewing”, “ It was shown that it was “meal”. In addition, the purpose history ID “004” reaches “parking lot E” on the date and time “Tuesday, January 11, 2005”, and the candidate candidates for “parking lot E” are “boring”, “karaoke” Is shown.

  FIG. 58 also shows the positional relationship between these arrival points “parking lot D” and “parking lot E”. It is shown that “parking lot D” and “parking lot E” are located at a point away from the user's home (for example, a city or prefecture different from the home address). That is, the user is performing the purpose “watching movies”, “boring”, etc. at the “parking lot D” and “parking lot E”, which are points away from home.

  Now, as shown in FIG. 57 (b), the user moves on “Saturday, January 22, 2005, 13:00” and the arrival point prediction method shown in the second embodiment above Assume that “parking lot G” is predicted as a destination. It is assumed that the purpose candidates in “parking lot D” are “movie appreciation” and “food purchase” by the purpose tag or the like. Therefore, based on the purpose history (FIG. 57 (a)) stored in the movement history storage unit 104, the trusted destination determination unit 1061 determines the purpose of the current movement.

  First, the trust destination determination unit 1061 calculates a trust value for each purpose as shown in the fourth embodiment. For example, the goal history ID “001”, the trust value “1/3” of “food purchase”, one of the goals at the destination “parking lot A”, the goal history ID “003”, the goal at the destination “parking lot B” From the confidence value “1/2” of “grocery purchase” and the confidence value “1/2” of the goal “buy food” at “parking lot C” with the goal history ID “005”, the purpose “buy food” Becomes “4/3 (= 1/3 + 1/2 + 1/2)”. Similarly, “1” for “movie appreciation”, “meal”, “5/6” for “daily necessities purchase”, and the like are calculated. On the other hand, the target candidates at “parking lot E”, which is the predicted destination, are “movie viewing”, “meal”, and “grocery purchase”, and referring to the confidence values of these target candidates, “grocery purchase” “4/3” is the highest, and “grocery purchase” is considered the purpose of this time.

  However, in this case, the sum of the confidence values alone does not always accurately reflect the user's behavior characteristics. For example, a user who has the purpose history shown in FIG. 57A has a lot of history for the purpose of “grocery purchase”, and therefore has a high reliability value as shown in FIG. 57C. It can be considered as one of the purposes of the user's action. On the other hand, “grocery purchase” is an action performed in “parking lot A”, “parking lot B”, and “parking lot C” near the home. is there. On the other hand, when moving away from home, for example, in “parking lot D” and “parking lot E”, it is considered that there are many purposes relating to entertainment such as “movie appreciation”, “game center”, and “boring”. . That is, the sum of the confidence values does not accurately reflect the user behavior characteristics considering these areas, and the purpose cannot always be determined accurately. Therefore, the purpose determination condition setting unit 1065 sets conditions regarding the area in order to reflect the purpose in consideration of these areas.

  FIG. 59 is a diagram illustrating conditions relating to the area accumulated in the purpose determination condition accumulation unit 1064. For example, a condition relating to a predetermined threshold value based on the registered home, for example, “is it in the area (prefecture or city)” or “is out of the area”, the same as the home, is accumulated. Note that, as shown in the above-described modified example, the upper concept “inside area” may be stored in a tree structure such as the lower concept “within 1 km”.

  Next, the purpose determination condition setting unit 1065 sets these conditions, and the trusted destination determination unit 1061 recalculates the reliability value for each purpose according to these conditions.

  FIG. 60A shows a reliability value calculated when, for example, the condition “in area” is set. A goal history that satisfies the condition “in area” can be determined based on the destination of the goal history. For explanation, FIG. 58 is used. In FIG. 58, “parking lot A”, “parking lot B”, and “parking lot C” located in the vicinity of the home are within the area. Accordingly, the trusted destination determination unit 1061 has a destination history ID [001] whose destination is “parking lot A”, a destination history ID [003] that is “parking lot B”, and a destination history that is “parking lot C”. Using the ID [005], as shown in FIG. 60C, the reliability value for each purpose is calculated. The goal history ID “001”, the trust value “1/3” of “food purchase”, one of the goals at the destination “parking lot A”, the goal history ID “003”, the goal “food” at the destination “parking lot B” FIG. 60C shows the reliability value “1/2” of “purchased product” and the reliability value “1/2” of the purpose “buy food” at “parking lot C” with the purpose history ID “005”. Thus, the purpose “buy food” is “4/3 (= 1/3 + 1/2 + 1/2)”. Similarly, for “purchased daily necessities”, a confidence value for each purpose such as “5/6” is calculated.

  On the other hand, FIG. 61A shows a reliability value calculated when, for example, the condition “out of area” is set. The purpose histories satisfying the condition “out of area” are “parking lot D”, “parking lot E”, and “parking lot F” located at a point away from home in FIG. Therefore, the trusted destination determination unit 1061 has a destination history ID [002] whose destination is “parking lot D”, a destination history ID [004] that is “parking lot E”, and a destination history that is “parking lot F”. Using the ID [006], as shown in FIG. 61 (c), the reliability value for each purpose is calculated. A goal history ID “002”, a reliability value “1/2” of “movie appreciation” as one of the goals at the destination “parking lot B”, a goal history ID “004”, a goal “movie appreciation” at the destination “parking lot D” As shown in FIG. 61 (c), the objective “movie appreciation” is “1 (= ½ + 1/2)” from the reliability value “1/2” of “”. Similarly, a confidence value for each purpose is calculated, such as “1/2” for “meal” and “1/2” for “game center”.

  Since the current predicted arrival point corresponds to “parking lot G” (FIG. 61 (b)) and “outside area”, the trusted destination determination unit 1061 calculates the reliability value calculated again using the condition “outside area”. The purpose is determined using (FIG. 61 (c)). “Movie watching” exists as a destination candidate at the predicted arrival point “parking lot F”, and since the reliability value is the highest, it is determined as “movie watching”.

  Thus, the purpose differs depending on the area depending on the user, and the user's action can be reflected by considering this area. For example, in the living area, regardless of the point of arrival, the purpose is to purchase meals, foods, and household items. On the other hand, at a point away from the living area, there are many purposes that can only be achieved there. Therefore, it is possible to reflect the user's behavior more by considering not only the stored purpose history but also the arrival point.

  In the fourth embodiment, the object information has been described as being given in advance. However, the present invention is not limited to this. For example, among the point information, for example, it may be automatically created from commercial information such as neighboring stores and assigned. Further, the given purpose information is not necessarily in a unified format. Under such an environment, it is necessary to further analyze the purpose information and appropriately determine the purpose. Therefore, here, a method for automatically assigning the purpose information and analyzing the automatically given purpose and determining the purpose will be described.

  FIG. 62 is a block diagram showing a configuration of the point information search apparatus in the third modification of the present embodiment. This point information search device basically has the same configuration as the point information search device of the fourth embodiment, but differs from the fourth embodiment in that a multipurpose acquisition unit 230d is provided instead of the multipurpose acquisition unit 230c. Different. The multi-purpose acquisition unit 230d includes a target ontology storage unit 108 in addition to the configuration (FIGS. 40 and 41) of the multi-purpose acquisition unit 230c of the fourth embodiment.

  First, automatic assignment of purpose information will be described. FIG. 63 shows point information of a certain point “parking lot A” accumulated in the point information accumulating unit 103. In the point information, as shown in the second embodiment, position information regarding the point, surrounding commercial information, and the like are accumulated.

  On the other hand, the point information in the present modification is not given object information, unlike the fourth embodiment. The purpose information is information necessary for determining the purpose of the user, which will be performed at the point as shown in the second embodiment. Therefore, in this modification, the purpose information is automatically given based on, for example, information stored as commercial information.

  In the purpose information, for example, commercial information related to nearby stores is accumulated. For example, as shown in FIG. 63, “Movie Theater D” exists as a store 3 in the vicinity, and detailed commercial information of “Movie Theater D” is linked by “www.ΔΔ.com”. Yes. Further, detailed commercial information such as “Today's screening title” is accumulated in the commercial information linked by “www.ΔΔ.com”. Therefore, from these commercial information, for example, morphological analysis or the like is performed to extract keywords that can become target information.

  The purpose ontology accumulating unit 108 is a storage device that accumulates synonyms related to the purpose indicated by the attribute information of the point information. Specifically, the word that can be the purpose information, the word-word consensus relationship, the superordinate concept, etc. A hard disk or the like that stores language relationships (ontologies). In the present modification, the movement history storage unit 104a and the confidence value calculation unit 106b refer to the purpose ontology storage unit 108 and extract keywords that can be target information.

  The trust value calculation unit 106b refers to the synonym stored in the target ontology storage unit 108 to determine the identity of the target included in the travel history stored in the travel history storage unit 104a, and the arrival point prediction unit The purpose corresponding to the arrival point predicted by 105 is specified, and a confidence value as a destination candidate is calculated for each specified purpose.

  The target ontology includes, for example, a “target word” that is a keyword that can be a candidate for target information. For example, “movie appreciation” corresponds to the target word. However, since it is not always written as “movie appreciation” in commercial information or the like, it further has a “synonymous word” having the same meaning (purpose) as the target word. For example, the synonym for “movie appreciation” indicates “movie”, “movie”, and “screening”. Furthermore, the target ontology has not only synonyms but also “superior purpose” which is a superordinate concept of these target words. For example, the target words “movie appreciation”, “karaoke”, and “boring” have “higher purpose” called “amusement”. In the present modification, the movement history storage unit 104a and the confidence value calculation unit 106b automatically extract target information using this target ontology.

  As shown in FIG. 64, when morphological analysis is performed on commercial information and nouns are extracted, for example, it is understood that a synonym “screening” for the target word “movie appreciation” is included. Therefore, “movie appreciation” is accumulated as one of the purpose candidates of “parking lot A”.

  FIG. 65 shows the target history accumulated in the movement history accumulation unit 104a. In the purpose history ID [001], it is understood that the destination is “parking lot A” and “movie appreciation” is accumulated as one of the candidate candidates.

  Next, a method for determining the user's purpose using the purpose ontology will be described with reference to FIGS.

  Now, it is assumed that the user moves to “Saturday, January 22, 2005” and “parking lot D” is predicted as a destination by the destination prediction method shown in the second embodiment. It is assumed that the target candidates in “parking lot D” are extracted as “karaoke”, “food purchase”, and “pachinko” by the above-described target ontology. Therefore, the purpose of the current movement is determined based on the purpose history (FIG. 66 (a)) accumulated in the movement history accumulation unit 104a.

  First, as shown in the second embodiment, when the reliability value calculation unit 106b calculates the reliability value for each object, as shown in FIG. 66 (c), the object “movie appreciation” is “1/3”, “Japanese food” is “1/3”, “Game center” is “1/2”, “Bowling” is “1/2”, “Tennis” is “1/2”, “Table tennis” is “1/2” " And since there is no target candidate at the current arrival point “parking lot D”, the target cannot be determined as it is. Therefore, for example, a higher-order purpose of the purpose ontology is used. In the goal ontology, higher goals indicating higher concepts of each goal are stored. With reference to this, the trust value calculation unit 106b calculates a confidence value of each higher goal. For example, “movie appreciation” and “boring” coincide with the higher purpose “amusement”, that is, these purposes may be reached for the purpose of amusement. Therefore, the reliability value calculation unit 106b calculates the sum of the reliability values for each object, and calculates the reliability value for the higher-level object. In this case, as shown in FIG. 66 (d), the confidence value of the upper purpose “amusement” is “5/6” from “1/3” of “movie appreciation” and “1/2” of “boring”. It becomes. The high value means that the user often moves for the purpose of “amusement”. On the other hand, as shown in FIG. 66 (b), “Karaoke” is one of the destination candidates of the current arrival point, and the upper purpose of the purpose “Karaoke” coincides with “Amusement”. If the purpose is also “amusement”, that is, if it is one of them “karaoke”, it is possible to perform purpose determination reflecting the user's usual behavior.

  Thus, according to this modification, by referring to the target ontology, even if the purpose is different in the history, if it is common as a superordinate concept, it is interpreted as a common purpose, The purpose reflecting the behavior can be determined, and as a result, the purpose information useful for the user is provided. In addition, even if the purpose information is not necessarily in a uniform format, it is possible to analyze the purpose information and appropriately determine the purpose. This makes it possible to implement a point information retrieval apparatus corresponding to various types of purpose information.

(Embodiment 5)
In the above embodiment, the point information has been described as being designed in advance by a system designer, a cartography company, a parking lot manager, a manager of a surrounding facility store, etc. It can also be created.

  For the purpose information, for example, from commercial information such as homepage and store advertisement information, morphological analysis etc. was performed, and the purpose keyword was extracted to create the purpose information, but in the present embodiment, A method for automatically generating area and point information covered by purpose information such as facilities will be described.

  FIG. 67 is a system configuration diagram of the present embodiment. The same reference numerals are given to the constituent elements shown in the embodiment.

  The spot information acquisition unit 301 is a processing unit that receives a spot specified by the user using, for example, a touch panel that covers the display panel.

  FIG. 68 is a diagram for explaining the acquisition of a point specified by the point information acquisition unit 301. An example in which a user designates a certain point on the display screen is shown.

  The position condition generation unit 511 is a processing unit that generates a position condition for searching for point information based on the point acquired by the point information acquisition unit 301. In the above embodiment, the position information acquisition unit 210 generates a position condition based on the current position of the user. However, as shown in the present embodiment, the user specifies a point for defining a search range. Also good. That is, the point information acquisition unit 301 is not separately provided, but a point serving as a reference for searching for point information as input information of the position information acquisition unit 210 may be specified.

  FIG. 69 is a diagram for explaining the generation of position conditions based on acquired points. For example, a specified dot is detected by setting the horizontal axis of the display screen covered with the touch panel as the X axis, the vertical axis as the Y axis, and the lower left as the origin (0, 0).

  For example, now (300, 150) is designated. On the other hand, the map displayed on the screen is a heading-up display in which north is displayed on the top, the origin (0, 0) is (135 degrees 30 minutes east, 35 degrees 10 minutes north), and the lower right (640, 0) of the screen. (135 degrees 36 minutes 40 seconds east longitude, 35 degrees 10 minutes north latitude) and the upper right (640, 480) of the screen is (135 degrees 36 minutes 40 seconds east longitude 35 degrees 14 minutes 80 seconds north latitude). From this point, it is calculated as 135 degrees 33 minutes east longitude and 35 degrees 12 minutes 50 seconds north latitude) (one dot is 1 second).

  The position condition generation unit 511 generates, for example, a radius of 500 meters as a search area for searching for point information, based on the designated point, as in the above-described embodiment.

  The multi-purpose acquisition unit 230a is a processing unit that acquires a purpose to be performed at a point, as in the above embodiment. And the spot information search part 122 is also a process part which searches the spot information applicable to the acquired objective from the produced | generated search area | region like the said embodiment.

  FIG. 70 is a diagram for explaining a search for point information. The user is about to eat a meal around Umeda Station, and “meal” is entered as the purpose information, the vicinity of Umeda Station is specified, and the corresponding facility located within a radius of 500 meters around the specified point is "Ramen" and "Yakitoriya" are searched.

  The position condition correction unit 512 is a processing unit that corrects the position condition. For example, as in the case of the above-described embodiment, the position condition correction unit 512 corrects the position condition when the number of corresponding facilities is less than a predetermined number or exceeds the predetermined number. Then, the point information re-search unit 133 searches the point information again.

  In the above-described embodiment, for example, the search area is corrected based on the location where the facilities are crowded by the cooperative operation of the density calculation unit 132, the distance calculation unit 124, and the position condition correction unit 512 in FIG. Although the method of correcting based on the traveling route has been described, the present invention is not limited to this. For example, the correction may be performed according to the distance between the current position of the user and the designated point. For example, in FIG. 68, the designated point and the current position of the user are 5000 meters. On the other hand, it is 10,000 meters in FIG.

  In the present embodiment, for example, when the distance is 5000 meters or less, the position condition correction unit 512 determines the position condition based on this distance, such as a radius of 500 meters, and a distance of 10000 meters or more, such as a radius of 1000 meters. Correct it. The search unit 240e of this embodiment is configured by omitting the density calculation unit 132, the distance calculation unit 124, and the like from the search unit 240a of FIG.

  This distance may be a linear distance or a distance obtained as a result of route search. Moreover, it is good also as changing according to the reduced scale of the present map. For example, if the current scale is a relatively wide area display such as 400 meters, the user is likely to be searching for a wide range. On the other hand, if the scale is relatively small such as 100 meters, the specified point and its surroundings are narrow. It is likely that you are seeking a search within a range. Therefore, the position condition may be generated in consideration of the current map scale.

  In general, when a user searches for information on a certain point, the specified point is an approximate guideline, and in many cases, a facility corresponding to the vicinity is searched. On the other hand, the surrounding concept often changes depending on the current position.

  For example, if the current location is close to the specified location, it is not preferable to search to the surroundings that are far away from the specified location, but it is not preferable, but if the current location is far from the specified location, that is, it is still a distance to the specified location. If there are many remaining, the specified point is only a guideline, and even if it is a little far from the specified point, it does not go so far to the surrounding facilities, and it may be desirable to search a wide range . Therefore, for example, as shown in the present embodiment, the search condition may be generated from the relationship between the current position and the designated point.

  In recent years, it has become possible for third parties to write information about facilities where ordinary people are on a map, or upload restaurant introduction information to their own diaries or bulletin boards. In such a case, unlike the conventional text information search, the search is also performed using the latitude and longitude tagged to these information. For example, as shown in the present embodiment, point information including latitude and longitude included in a range generated as a position condition is searched.

  However, there is a case where a corresponding facility does not necessarily exist in the generated point information, or conversely, a vast amount of point information is searched only by the condition of the point and its surroundings and the information requested by the user cannot be provided. . In particular, information retrieval in a mobile terminal such as a car navigation system or a mobile phone is not always good, unlike a retrieval performed while sitting at a desk, and a complicated operation during driving may be dangerous.

  Therefore, as shown in the present embodiment and the above-described embodiment, it is possible to perform information search more suitable for the user by correcting the search condition according to the situation.

  The spot information posting unit 125 is a processing unit that posts searched spot information as in the above embodiment. FIG. 72 shows a display screen as a result of performing a search with a radius of 1000 meters using the designated point as a reference. A plurality of facilities such as “Sushi Jiro” and “Pasta & Pasta” are searched as facilities corresponding to the purpose “meal”. By displaying the retrieved information on a display unit or the like, the user can grasp the point information.

  Furthermore, in this embodiment, as a characteristic process, new point information is obtained from the point information searched by the search unit 240e according to the user's designation and the user's action after the point information is searched. Generate.

  Generally, when a user performs a search on a map, the target facility is not always specified directly. For example, the target facility itself is not decided, but a certain facility or area is designated for the time being, and the vicinity is searched and the destination is finally decided. In addition, the location of the target facility may not be accurately determined, and the search may be performed by tracing the facility that is a nearby landmark. Furthermore, a terminal having a limited display screen such as a car navigation system or a mobile phone may not be able to specify a point accurately, and may not be searched by simply searching around 500 meters or the like.

  Therefore, in the present embodiment, for example, the arrival point detection unit 302 detects a point finally arriving from the user position acquired by the position information acquisition unit 210, and the arrival point and the point information acquisition unit 301 acquire the point. Generate new location information based on the location. The point information generation unit 303 is a processing unit that generates new point information based on the user's behavior after searching the point information once. This will be described below with reference to the drawings.

  As shown in FIG. 69, FIG. 70, etc., since the user eats around Umeda Station, the user designates the vicinity of Umeda Station and searches for point information of surrounding facilities. For example, in the present embodiment, not only a designated point but also point information such as a nearby facility or region is extracted from the designated point. For example, the nearest facility among the facilities displayed on the scale of the current map is set as the designated facility. In the case of this example, the designated points “E135.33.00, N35.12.25” and “Umeda Station” are extracted.

  FIG. 73 is a diagram for explaining detection of an arrival point. FIG. 73 shows a map near the pizza potter, which is one of the searched point information. As in the previous embodiment, the positions acquired by the position information acquisition unit 210 are indicated by white circles. For example, information on the cover area is attached to the location information of the pizza potter. For example, when the vehicle stops in this cover area, that is, when the engine is stopped, the arrival point detection unit 302 determines that the arrival has occurred. And

  In FIG. 73, the cover area is an area surrounding a facility and a parking lot of 100 meters × 50 meters centering on a reference point of “Pizza Potter” “135 degrees 32 minutes 13 seconds east, 35 degrees 11 minutes 20 seconds north latitude” And When the user stops in this cover area, the arrival point detection unit 302 detects the position as the arrival point. Then, it is detected that the user has visited “Pizza Potter”.

  The point information generation unit 303 is a processing unit that generates point information based on the actual user arrival point detected by the arrival point detection unit 302.

  74 (a) and 74 (b) show point information 103 related to “pizza potter”. The location of “Pizza Potter” “E135.32.13, N35.11.20”, cover area “50 m × 100 m”, name “Pizza Potter”, purpose “meal”, etc. Information about the point is shown.

  The point information generation unit 303 acquires the point information (FIG. 74A) of the “pizza potter” that is the actual user arrival point detected by the arrival point detection unit 302 and is acquired by the point information acquisition unit 301. Point information is added and newly generated as point information (FIG. 74 (b)). As the point link (PositionLink), “E135.33.00, N35.12.50” and the facility “Umeda Station” are given.

  This point link is information indicating the relationship between the point information and the actual point. As shown in the embodiment, the point information is information corresponding to a point or its cover area and purpose information at the point, and the point information is assumed to be designed in advance by a system designer, a map production company, or the like. I have done it. When the point is specified or the point or its cover area is included as the search range, the user can enjoy the point information, but when it is not included, the user cannot receive the information.

  On the other hand, when searching for information on a map, the user does not necessarily know the target point accurately, and therefore cannot always search to include a point or a cover area. In addition, even when the scale of the map is wide, it is not always possible to specify it accurately.

  For example, if you know that there is a famous restaurant "Pizza Potter" around Umeda Station, but you don't know where it is, it is common to first search around Umeda Station, If it is not included in the vicinity, it cannot be searched. After that, it will be searched by changing the surrounding distance or changing the conditions, and finally it will visit the store, but by reflecting this act newly generating point information, it is related to Umeda Station. The store can be easily searched.

  FIG. 75 is a diagram for explaining designation of points. The user now has the purpose “meal” and designates the area near Umeda Station. For example, a predetermined area such as a surrounding area of 500 m is searched. For example, since “Sant Zeria” is included in 500 m, the point information is searched. At the same time, as described above, the location information of “Pizza Potter” includes Umeda Station as a point link, so even if it is not included in the predetermined search area within 500 m, Umeda Station is searched. Is extracted as a medium, so that point information can be enjoyed.

  Further, the present embodiment is not limited to information retrieval performed by one user. For example, as shown in the above example, a user A searches for a place where he / she can eat by specifying Umeda Station, finally arrives at “Pizza Potter”, and the point information is generated. The point information is further efficiently searched by uploading the point information to a server and sharing it with other users.

  For example, when another user B searches Umeda Station again and searches for a place where he / she can eat, this time, the points of “Umeda Station” and “Pizza Potter” are related as point links. It will be offered as a search candidate even if it is not expanded. For example, a new store or a store preferred by multiple people, while the exact location is not known. For example, by relating it to landmarks in the vicinity or points specified by ordinary people, other users can Information can be shared, which is an effective means for searching for information based on the map shown in the present invention.

  Hereinafter, the generation of the spot information shown in the present embodiment will be described using another example. FIG. 76 shows a situation in which a user designates “North IC” as the purpose “skiing area” while stopping in the Zhongshan parking area on the expressway. For example, in the prior art in which a peripheral search is performed by designating a predetermined distance, only facilities located in the area can be searched. For example, in this example, only “B ski resort” is searched.

  However, according to the present embodiment, when point information having a point link related by another user's search is generated, information search can be performed more appropriately by the point information. For example, as shown in FIGS. 77A and 77B, it is assumed that “A ski resort” and “C ski resort” to which a user who gets off at high speed at “North IC” is generally related. That is, the point information 103 of “A ski resort” or “C ski resort” is generated so as to have a point link from the facility “North IC” indicated by the position “E135.35.00, N35.31.50”. Suppose that As a result, a user who searches for a location later can specify “A Ski Resort” or “C Ski Resort” simply by designating “North IC”, and can enjoy desired information without complicated operations.

  In FIG. 78, description will be given by taking a parking lot of a large facility as an example. The user now designates “Department Store Tiger” as the purpose “parking lot”. In this case, the technology described in the embodiments so far only searches for a parking lot from a predetermined cover area. For example, the first parking lot and the second parking lot around the “Department Store Tiger” are located in the cover area. Although it is included and searched, the third parking lot and the fourth parking lot are not included in the cover area and are not searched. However, as shown in the present example, in the present embodiment, the third parking lot and the fourth parking lot are associated with this “department store tiger” by the point link, and thus are searched.

  Specifically, as shown in FIG. 79, for example, another user once designates a department store tiger and searches for the location information, and then the search can be performed at the third parking lot and the fourth parking lot. Because the vehicle has stopped, as shown in FIGS. 80 (a) and (b), the point information of the third parking lot or the point information of the fourth parking lot having a point link to “Department Store Tiger” is newly generated. is there.

  In recent years, against the backdrop of enforcement of street parking, when there is no parking lot at the facility, parking is often done in a nearby parking lot. In order to go to a certain facility, the facility is set as a destination. However, the facility is not necessarily parked in the parking lot of the facility, and is often finally parked in a nearby parking lot. In such a case, by generating new location information of the parking lot with a point link to the facility, when visiting the facility in the future, the location information of the parking lot will also be hit and displayed. Is possible. In addition, when the spot information of the parking lot already exists, of course, such a spot link may be added to the existing spot information.

  Hereinafter, the operation flow of the point information search apparatus according to the present embodiment will be described with reference to FIG. First, the multipurpose acquisition unit 230a acquires a purpose (step S601). And the designation | designated of a spot is acquired in the spot information acquisition part 301 (step S602). For example, the position condition generation unit 511 generates a predetermined position condition centered on the designated point, and the point information search unit 122 searches for the point (step S603).

  The point information search unit 122 determines whether or not a corresponding point exists in the point information storage unit 220 (step S604). If there is a point, the process proceeds to step S608, and if not, the process proceeds to step S605. If it does not exist, the position condition correction unit 512 corrects the position condition, and the point information is searched again by the search unit 133 (step S605). If it exists, the process proceeds to step S608, and if it does not exist, the process ends.

  When the point information exists in step S604 or step S607, the arrival point detection unit 302 detects the arrival point (step S608), and the point information generation unit 303 detects the actual arrival point having a point link to the point information. The point information is newly generated (step S609), stored in the point information storage unit 220 (step S610), and the process ends.

  As mentioned above, although the point information search device concerning the present invention was explained based on the embodiment and its modification, the present invention is not limited to these embodiment and the modification. For example, embodiments realized by arbitrarily combining the constituent elements in each embodiment and modification are also included in the present invention. As an example, by providing the mobile terminal in the modification shown in FIG. 62 with the position condition generation unit 511 and the position condition correction unit 512 shown in FIG. And a point information search device that searches for the optimum point information to achieve a plurality of purposes satisfying the relaxed position condition using the corrected position condition is realized.

  Moreover, although the point information search apparatus in the said embodiment was provided with the point information storage part 103, the structure which does not include the point information storage part 103 may be sufficient as the point information search apparatus which concerns on this invention. That is, the point information search device according to the present invention is provided in a mobile terminal connected to the point information storage unit, like the mobile terminal 100 shown in FIG. 40, and communicates with the point information storage unit while communicating with the point information storage unit. It may be a device that searches for and provides it to the user.

  The correspondence between the constituent elements in the claims and the constituent elements in the embodiment and the modification is as follows, as shown in FIG.

  That is, the position information acquisition means in the claims corresponds to the position information acquisition unit 210 in the embodiment and the like, and an example thereof is the position information detection unit 101 and the like.

  The point information storage means in the claims corresponds to the point information storage unit 220 in the embodiment and the like, and an example thereof is the point information storage unit 103 and the like.

  The multi-purpose acquisition unit in the claims corresponds to the multi-purpose acquisition unit 230 in the embodiment or the like, and one example thereof is (1) a multi-purpose input unit 131, (2) a movement history storage unit 231 and a target ontology storage. Including at least one of a unit 232, a confidence value calculation unit 233, and a trust purpose extraction unit 234, (3) a multi-purpose acquisition unit 230b, (4) a multi-purpose acquisition unit 230c, (5) a multi-purpose acquisition unit 230d, etc. is there.

  The search means in the claims corresponds to the search unit 240 in the embodiment etc., and one example thereof is (1) the spot information search unit 122, (2) the position condition correction unit 241, the re-search unit 242, and the distance calculation. These include at least one of the units 243, (3) search unit 240a, (4) search unit 240b, (5) search unit 240c, (6) search unit 240d, (7) search unit 240e, and the like.

  The information providing means in the claims corresponds to the information providing unit 250a in the embodiment and the like, and an example thereof is the point information presenting unit 125.

  The position condition correction means in the claims corresponds to the position condition correction unit 241 in the embodiment and the like, and an example thereof is the position condition correction unit 512.

  The re-search means in the claims corresponds to the re-search unit 242 in the embodiment, and one example thereof is (1) a re-search unit 133, (2) a density calculation unit 132, a road determination unit 132a, and related roads. One having at least one extraction unit 126a.

  The distance calculation means in the claims corresponds to the distance calculation unit 243 in the embodiment and the like, and an example thereof is the distance calculation unit 124.

  The movement history accumulation means in the claims corresponds to the movement history accumulation unit 231 in the embodiment and the like, and one example thereof is (1) the movement history accumulation unit 104, (2) the movement history accumulation unit 104a, and the like.

  The trust purpose extracting means in the claims corresponds to the trust purpose extracting unit 234 in the embodiment and the like, and an example thereof is the trust purpose extracting unit 123.

  The reliability value calculation means in the claims corresponds to the reliability value calculation unit 233 in the embodiment, and one example thereof is (1) the reliability value calculation unit 106, (2) the reliability value calculation unit 106a, and (3) the reliability. The value calculating unit 106b and the like.

  The target ontology storage means in the claims corresponds to the target ontology storage unit 232 in the embodiment and the like, and an example thereof is the target ontology storage unit 108.

  An example of the arrival point detection means in the claims is the arrival point detection unit 302 in the embodiment.

  An example of the point information generation means in the claims is the point information generation unit 303 in the embodiment.

  The present invention efficiently achieves a plurality of purposes desired by a user, particularly as a point information search device provided in a mobile terminal, for example, as a point information search device that provides information on a destination point to a user. It can be used as a device incorporated in a car navigation system, a mobile phone or the like that provides information relating to a point where it is possible.

The block diagram which shows the structure of the point information retrieval apparatus in Embodiment 1 of this invention. The block diagram which shows the structure of the point information retrieval apparatus in Embodiment 2 of this invention. The figure which shows the example of the screen display which shows the appearance which inputs plural purposes (A) And (b) The figure which shows the example of point information The figure explaining the point information shown in FIG. (A) And (b) The figure which shows another example of point information The figure explaining the point information shown in FIG. Figure showing an example of using point information The figure which shows another example of use of point information (A) And (b) The figure which shows the example of the point information corresponding to the utilization example shown by FIG. The figure which shows the example of the searched point information Diagram showing examples of position conditions A map showing points corresponding to the purpose “family restaurant” shown in FIG. The figure which shows a mode that the center point Z where the point is crowded is calculated Figure showing the result of searching for point information again with the search area expanded The figure which shows the example of the distance between points calculated by the distance calculation part The flowchart which shows operation | movement of the point information retrieval apparatus in Embodiment 2 of this invention. The figure which shows the example of the information presentation by a point information presentation part Diagram showing a typical search result presentation example The block diagram which shows the structure of the point information retrieval apparatus in the modification of Embodiment 2 of this invention. Figure showing examples of search conditions (A)-(c) The figure which shows the searched point information The flowchart which shows operation | movement of the point information retrieval apparatus in the modification of Embodiment 2 of this invention. The block diagram which shows the structure of the point information search device in another modification of Embodiment 2 of this invention. The block diagram which shows the structure of the point information retrieval apparatus in Embodiment 3 of this invention. A map showing an example of moving a car navigation system having a point information search device The figure which shows the example of the positional information detected by a positional information detection part. Map showing examples of location information The figure which shows the example of a history of the movement destination candidate accumulate | stored in a movement history storage part. The figure which shows the log | history example of the movement destination candidate to which (a) and (b) the confidence value was provided. Figure showing a search example of point information The figure which shows the example of the point information which is referred The figure which shows the example of the point information extracted for the purpose (A) And (b) The figure which shows the example of the spot information of a parking lot Map related to point information shown in FIG. The figure which shows the example of a screen display by a point information presentation part The flowchart which shows operation | movement of the point information retrieval apparatus in Embodiment 3 of this invention. The figure which shows the continuation of the same flowchart (A)-(c) The figure which shows the example of the objective log | history accumulate | stored in the movement log | history storage part. The block diagram which shows the structure of the point information retrieval apparatus in Embodiment 4 of this invention. Block diagram showing the detailed configuration of the confidence value calculator Diagram showing an example of travel history The figure which shows the example of the movement history containing a movement destination candidate Diagram showing an example of user movement (A) And (b) The figure which shows a mode that a prediction candidate is extracted from a movement history. (A)-(c) The figure which shows a mode that the reliability value for every objective is calculated from a movement history. (A)-(d) The figure which shows a mode that the objective is determined from a movement history. The figure which shows the example of the information provision according to the determined purpose The flowchart which shows operation | movement of the point information retrieval apparatus in Embodiment 4 of this invention. Flow chart about the prediction of the arrival point by the same point information search device Flow chart about the purpose determination at the arrival point by the same point information search device The block diagram which shows the structure of the point information retrieval apparatus in the modification 1 of Embodiment 4 of this invention. Diagram showing examples of purpose determination conditions (A)-(c) The figure which shows the example of a movement history (A)-(c) The figure which shows the example of the objective determination which considered the date and time (A)-(c) The figure which shows the continuation of the example of the objective determination which considered the date and time (A)-(c) The figure which shows the example of the objective history accumulate | stored in the movement history storage part A map showing the positional relationship of “parking lot A” as the destination The figure which shows the conditions regarding the area accumulated in the purpose judgment condition accumulation part (A)-(c) The figure which shows the example of the reliability value calculated when condition "inside area" is set (A)-(c) The figure which shows the example of the reliability value calculated when condition "outside area" is set The block diagram which shows the structure of the point information retrieval apparatus in the modification 3 of Embodiment 4 of this invention. The figure which shows the example of the spot information accumulate | stored in the spot information storage part Diagram explaining the target ontology Figure showing an example of purpose history (A)-(d) The figure which shows the example of determination of the objective The block diagram which shows the structure of the point information retrieval apparatus in Embodiment 5 of this invention. The figure which shows the example of designation of the point by the user The figure which shows the example of the position condition on the basis of the specified point The figure which shows the example of the point information searched according to the position condition The figure which shows the example of the position condition on the basis of the specified point The figure which shows the example of the point information searched according to the position condition Diagram showing examples of arrival points (A) And (b) The figure which shows the example of point information The figure which shows the example of designation of the point by the user The figure which shows the example of designation of the point by the user (A) And (b) The figure which shows the example of point information The figure which shows the example of designation of the point by the user The figure which shows the example of generation of new point information (A) And (b) The figure which shows the example of point information The flowchart which shows operation | movement of the point information retrieval apparatus in Embodiment 5 of this invention. The block diagram which shows the structure of the navigation apparatus in a prior art

Explanation of symbols

DESCRIPTION OF SYMBOLS 101 Position information detection part 102 Arrival point specific | specification part 103 Point information storage part 104,104a Movement history storage part 105 Arrival point prediction part 106,106a, 106b Reliability value calculation part 108 Objective ontology storage part 121 Position information storage part 122 Point information search Unit 123 trust purpose extraction unit 124 distance calculation unit 125 point information presentation unit 126 purpose match determination unit 126a related road extraction unit 131 multi-purpose input unit 132 density calculation unit 132a road determination unit 133 re-search unit 301 point information acquisition unit 302 arrival point Detection unit 303 Point information generation unit 511 Position condition generation unit 512 Position condition correction unit 1031 Destination candidate identification unit 1061 Reliable movement destination determination unit 1062 Destination reliability value recalculation unit 1063 Destination search unit 1064 Purpose determination condition storage unit 1065 Purpose Judgment condition setting

Claims (12)

A point information search device provided in a mobile terminal for searching for information about a point and providing it to a user,
Position information acquisition means for acquiring position information indicating the position of the mobile terminal;
A multi-purpose acquisition means for acquiring information specifying a plurality of purposes for a purpose that is an action desired by the user;
Point information storage means for storing point information that associates the position information of the point with the attribute information related to the classification of the point or the action that can be performed at the point;
From the point information stored in the point information storage means, the point indicated by the position information included in the point information and the position indicated by the position information acquired by the position information acquisition means are in a predetermined fixed relationship, And search means for searching for point information including attribute information corresponding to a plurality of purposes acquired by the multi-purpose acquisition means,
Information providing means for providing information relating to the point indicated by the position information included in the point information searched by the search means;
With
The search means further includes
Position condition correction means for correcting the fixed relationship when the number of point information searched by the search means is less than a predetermined fixed number;
From the point information stored in the point information storage unit, the point indicated by the position information included in the point information and the position indicated by the position information acquired by the position information acquisition unit are fixed by the position condition correction unit. And a re-search means for searching for point information including attribute information corresponding to a plurality of purposes acquired by the multi-purpose acquisition means.
The search means is a fixed point in which the point indicated by the position information included in the point information and the position indicated by the position information acquired by the position information acquisition means are determined in advance from the point information stored in the point information storage means. The position information included in the searched point information indicates the point information including the attribute information corresponding to one of the plurality of purposes acquired by the multi-purpose acquisition unit. The point information stored in the point information storage means is searched for point information including position information indicating a point having a certain relationship with the point and including attribute information corresponding to the remaining purpose among the plurality of purposes. ,
The information providing means includes point information including attribute information corresponding to one of the plurality of purposes searched by the searching means and point information including attribute information corresponding to a remaining purpose among the plurality of purposes. earth point information retrieval device you characterized by providing information related to the point indicated by the position information included in and. The search means, after searching a plurality of spot information including attribute information corresponding to one of the plurality of purposes, per unit area for a plurality of spots indicated by the position information included in the searched spot information The point information is stored in the point information storage means including position information indicating a point having a certain relationship with the high-density point and including attribute information corresponding to the remaining purpose among the plurality of purposes. The point information search device according to claim 1 , wherein the point information is searched from information. The search means searches for a plurality of spot information including attribute information corresponding to one of the plurality of purposes, and then passes near a plurality of spots indicated by position information included in the searched spot information. A point that identifies the road, includes position information indicating a point along the identified road, and stores point information including attribute information corresponding to the remaining purpose among the plurality of purposes, in the point information storage unit The point information search device according to claim 1 , wherein the point information is searched from information. A point information search device provided in a mobile terminal for searching for information about a point and providing it to a user,
Position information acquisition means for acquiring position information indicating the position of the mobile terminal;
A multi-purpose acquisition means for acquiring information specifying a plurality of purposes for a purpose that is an action desired by the user;
Point information storage means for storing point information that associates the position information of the point with the attribute information related to the classification of the point or the action that can be performed at the point;
From the point information stored in the point information storage means, the point indicated by the position information included in the point information and the position indicated by the position information acquired by the position information acquisition means are in a predetermined fixed relationship, And search means for searching for point information including attribute information corresponding to a plurality of purposes acquired by the multi-purpose acquisition means,
Information providing means for providing information relating to the point indicated by the position information included in the point information searched by the search means;
With
The multipurpose acquisition means further includes:
Movement history accumulating means for accumulating movement history of the mobile terminal;
From the movement history stored in the movement history storage means and the position information acquired by the position information acquisition means, having a trust purpose extraction means for specifying a trust purpose that is an action predicted by the user,
The plurality of objects obtaining means, the reliable earth point information retrieval apparatus you and acquires the information specifying the plurality of purposes, including the purpose extracting means specified by trust purposes. The movement history accumulating unit identifies attribute information corresponding to the arrival point of the movement history by referring to the point information stored in the point information storage unit, and for the purpose of the identified attribute information, Accumulate travel history including information,
The multi-purpose acquisition unit further identifies a purpose corresponding to the predicted arrival point of the mobile terminal by referring to the movement history accumulated in the movement history accumulation unit, and moves for each identified purpose. Having a confidence value calculation means for calculating a confidence value as a candidate,
The point information search device according to claim 4, wherein the trust purpose extraction unit specifies the trust purpose based on a trust value for each purpose calculated by the trust value calculation unit. The movement history accumulating means calculates a confidence value that is a probability that the intended action is taken for each purpose included in the movement history, accumulates a movement history including the calculated confidence value together with a corresponding purpose,
The reliability value calculating means identifies a plurality of movement histories corresponding to a plurality of predicted arrival points of the mobile terminal from the movement history accumulation means, and corresponds to the same purpose included in the plurality of identified movement histories. The point information search device according to claim 5 , wherein a trust value as a destination candidate is calculated for each purpose by adding the trust value. The movement history accumulating means accumulates the movement history by including a point included in the movement route and classification information of the point including information indicating that it is home,
The trust purpose extracting means further calculates a distance from the user's home to the arrival point corresponding to the trust purpose by referring to the classification information included in the movement history, and uses the calculated distance, The point information search device according to claim 4, wherein the trust purpose is specified. The multipurpose acquisition means further includes:
Purpose ontology storage means for storing synonyms regarding the purpose indicated by the attribute information of the point information;
By referring to the synonym stored in the target ontology storage unit, the identity of the target included in the movement history stored in the movement history storage unit is determined, and the predicted arrival point of the mobile terminal is determined. A corresponding purpose is identified, and for each identified purpose, a confidence value calculating means for calculating a confidence value as a destination candidate is provided,
The point information search device according to claim 4, wherein the trust purpose extraction unit specifies the trust purpose based on a trust value for each purpose calculated by the trust value calculation unit.   In a mobile terminal, a point information search method for searching for information about a point and providing it to a user,
  A position information acquisition step of acquiring position information indicating the position of the mobile terminal;
  A multi-purpose acquisition step of acquiring information for specifying a plurality of purposes for a purpose that is an action desired by the user;
  Included in the point information from the point information stored in the point information storage means that stores the point information in which the position information of the point and the attribute information regarding the action that can be performed at the point classification or the point are associated The location indicated by the location information and the location indicated by the location information acquired in the location information acquisition step have a predetermined fixed relationship, and attributes corresponding to the plurality of purposes acquired in the multi-purpose acquisition step A search step for searching point information including information;
  An information providing step for providing information about the point indicated by the position information included in the point information searched by the searching step;
  Including
  The searching step further includes
  A position condition correcting step for correcting the fixed relationship when the number of the spot information searched in the searching step is less than a predetermined fixed number;
  From the point information stored in the point information storage means, the point indicated by the position information included in the point information and the position indicated by the position information acquired in the position information acquisition step are fixed in the position condition correction step. And a re-search step of searching for point information including attribute information corresponding to a plurality of purposes acquired in the multi-purpose acquisition step.
  In the search step, from the point information stored in the point information storage means, the point indicated by the position information included in the point information and the position indicated by the position information acquired in the position information acquisition step are predetermined constants. The position information included in the searched point information indicates the point information including the attribute information corresponding to one of the plurality of purposes acquired in the multi-purpose acquisition step. The point information stored in the point information storage means is searched for point information including position information indicating a point having a certain relationship with the point and including attribute information corresponding to the remaining purpose among the plurality of purposes. ,
  In the information providing step, point information including attribute information corresponding to one of the plurality of purposes searched in the searching step and attribute information corresponding to a remaining purpose among the plurality of purposes. Provides information about the location indicated by the location information included in
  The point information search method characterized by this.   In a mobile terminal, a point information search method for searching for information about a point and providing it to a user,
  A position information acquisition step of acquiring position information indicating the position of the mobile terminal;
  A multi-purpose acquisition step of acquiring information for specifying a plurality of purposes for a purpose that is an action desired by the user;
  Included in the point information from the point information stored in the point information storage means that stores the point information in which the position information of the point and the attribute information regarding the action that can be performed at the point classification or the point are associated The location indicated by the location information and the location indicated by the location information acquired in the location information acquisition step have a predetermined fixed relationship, and attributes corresponding to the plurality of purposes acquired in the multi-purpose acquisition step A search step for searching point information including information;
  An information providing step for providing information about the point indicated by the position information included in the point information searched by the searching step;
  Including
  The multipurpose acquisition step further includes:
  A movement history accumulation step for accumulating movement history of the mobile terminal;
  From the movement history accumulated in the movement history accumulation step and the position information acquired in the position information acquisition step, including a trust purpose extraction step that specifies a trust purpose that is a predicted action of the user,
  In the multipurpose acquisition step, information for specifying a plurality of purposes including the trust purpose specified in the trust purpose extraction step is acquired.
  The point information search method characterized by this.   A program for a point information search device provided in a mobile terminal for searching for information about a point and providing it to a user,
  The computer includes the steps included in the point information search method according to claim 9.
  A program characterized by that.   A program for a point information search device provided in a mobile terminal for searching for information about a point and providing it to a user,
  A step included in the point information search method according to claim 10 is executed by a computer.
  A program characterized by that.

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