JP6818717B2 - Extractor, extraction method, and extraction program - Google Patents

Description

The present invention relates to an extraction device, an extraction method, and an extraction program.

Conventionally, technologies for providing various services such as information provision have been provided according to the user. For example, based on the commuter pass information of the user (user), there is provided a technique for promoting the use of the facility by guiding the facility that suits the user's preference from the facilities at the boarding / alighting point where the boarding / alighting frequency is low.

JP-A-2016-207095

However, in the above-mentioned conventional technique, it is not always possible to appropriately extract the target user who performs a predetermined process. For example, it is often the case that the target user is not properly extracted only by guiding the facility based on the user's commuter pass information.

The present application has been made in view of the above, and an object of the present application is to provide an extraction device, an extraction method, and an extraction program for appropriately extracting a user who is a target of performing a predetermined process.

In the extraction device according to the present application, the acquisition unit that acquires the user's behavior information and the current context, which is the context of the user based on the behavior information acquired by the acquisition unit, are the user based on the user's past behavior history. If the past context is different from the normal context, which is the context corresponding to the user's daily life, the user is extracted as the target user who provides information about the area different from the area corresponding to the normal context. It is characterized by having a part.

According to one aspect of the embodiment, there is an effect that a user who is a target of performing a predetermined process can be appropriately extracted.

FIG. 1 is a diagram showing an example of an extraction process according to an embodiment. FIG. 2 is a diagram showing a configuration example of the extraction system according to the embodiment. FIG. 3 is a diagram showing a configuration example of the extraction device according to the embodiment. FIG. 4 is a diagram showing an example of a user information storage unit according to the embodiment. FIG. 5 is a diagram showing an example of the behavior information storage unit according to the embodiment. FIG. 6 is a diagram showing an example of the context information storage unit according to the embodiment. FIG. 7 is a flowchart showing an example of the extraction process according to the embodiment. FIG. 8 is a diagram showing an example of the extraction process according to the embodiment. FIG. 9 is a hardware configuration diagram showing an example of a computer that realizes the function of the extraction device.

Hereinafter, the extraction device, the extraction method, and the embodiment for implementing the extraction program (hereinafter referred to as “the embodiment”) according to the present application will be described in detail with reference to the drawings. The extraction device, extraction method, and extraction program according to the present application are not limited by this embodiment. Further, in each of the following embodiments, the same parts are designated by the same reference numerals, and duplicate description is omitted.

(Embodiment)
[1. Extraction process]
First, an example of the extraction process according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram showing an example of an extraction process according to an embodiment. In the example of FIG. 1, in the extraction device 100, the user's context (hereinafter, also referred to as “current context”) corresponding to the time when the action information is acquired is the user's past context based on the user's past action history. When the context is different from the context corresponding to the daily life of the user (hereinafter, also referred to as "normal context"), the case where the user is extracted as the target user (hereinafter, also referred to as "target user") to perform a predetermined process is shown.

Further, in the example of FIG. 1, the extraction device 100 shows a case where the extraction device 100 provides the user extracted as the target user with the recommended information according to the user. The context referred to here is information indicating the state or situation of the user including the environment in which the user is placed, which is estimated from the behavior information of the user. In the example of FIG. 1, each context is identified by the context ID. In addition, each context ID is associated with information about the position of the user corresponding to the context and the search query used by the user (hereinafter, also simply referred to as "query").

Further, in the example of FIG. 1, for simplification of the explanation, the extraction device 100 estimates the user's context based on the user's position and the information about the search query used by the user in the search among the user's behavior information. However, if the user's context can be estimated, any information may be used to estimate the user's context. For example, the extraction device 100 includes a user's action history, a user's action schedule, a user's attributes, a user's current position, a current time, a physical environment in which the user is placed, a social environment in which the user is placed, and a user's exercise state. Alternatively, the user's context may be estimated based on various information such as the user's emotions.

Further, for example, the extraction device 100 may estimate the user's context by using information on various actions such as actions that can be the estimation target of the user's intention. For example, the extraction device 100 may acquire various information such as browsing of the user's content as the user's behavior information, and estimate the user's context based on the information. Further, for example, the extraction device 100 may estimate the user's context based on the user's brain wave, heart rate, estimated emotional information, and the like.

[Extraction system configuration]
Prior to the description of FIG. 1, the configuration of the extraction system 1 will be described with reference to FIG. FIG. 2 is a diagram showing a configuration example of the extraction system according to the embodiment. As shown in FIG. 2, the extraction system 1 includes a terminal device 10 and an extraction device 100. The terminal device 10 and the extraction device 100 are communicably connected by wire or wirelessly via a predetermined network N. The extraction system 1 shown in FIG. 2 may include a plurality of terminal devices 10 and a plurality of extraction devices 100.

The terminal device 10 is an information processing device used by the user. The terminal device 10 is realized by, for example, a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. FIG. 1 shows a case where the terminal device 10 is a smartphone. Further, it is assumed that the terminal device 10 has a function such as a GPS (Global Positioning System) sensor and can detect and acquire the position of the user. Further, the terminal device 10 may have various functions such as a temperature sensor and a barometric pressure sensor, and may be able to detect and acquire environmental information such as temperature and barometric pressure in which the user is placed. Further, the terminal device 10 may have various functions such as a heart rate sensor and may be able to detect and acquire the biometric information of the user. For example, a user who uses the terminal device 10 may be able to acquire the user's own context information by the terminal device 10 by wearing a wearable device capable of communicating with the terminal device 10. For example, a user who uses the terminal device 10 wears a wristband-type wearable device capable of communicating with the terminal device 10, and the terminal device 10 acquires information on the user's own heartbeat (pulse) by the terminal device 10. It may be possible.

Further, the terminal device 10 transmits various information and the like to the extraction device 100. For example, the terminal device 10 transmits the position information about the user, the action information including the information about the search query used by the user for the search, and the like to the extraction device 100. In the following, the terminal device 10 may be referred to as a user. That is, in the following, the user can be read as the terminal device 10. The terminal device 10 accepts various operations by the user. In the example of FIG. 1, a case where the user who uses the terminal device 10 is a user identified by the user ID “U1” (hereinafter, referred to as “user U1”) is shown.

The extraction device 100 is an information processing device that extracts a user as a target user to perform a predetermined process when the current context of the user estimated based on the acquired behavior information is different from the normal context of the user. In addition, the extraction device 100 provides the user extracted as the target user with recommended information according to the user. In the example of FIG. 1, the user U1 is shown as an example for the sake of simplicity, but the extraction device 100 may perform an extraction process for a large number of users.

Further, "* (* is an arbitrary numerical value)" following "dt" in each date and time "dt *" shown in the example of FIG. 1 indicates the date and time when the corresponding action or the like was performed, and the date and time "dt *". The larger the value of "*", the newer the date. For example, the date and time "dt12" indicates that the date is newer because the numerical value following "dt" is larger than that of the date and time "dt11". In the example shown in FIG. 1, it is shown that the action of the user U1 at the date and time "dt12" was performed after the action of the user U1 at the date and time "dt11". In the example of FIG. 1, although the illustration is abstractly shown as "date and time dt11", the "date and time dt11" has a specific date and time such as "February 17, 2017 10:32:18". It shall correspond.

From here, the flow of the extraction process will be described with reference to FIG. First, the map information MP1-1 and MP1-2 shown in FIG. 1 will be briefly described. The map information MP1-1 and MP1-2 shown in FIG. 1 are diagrams schematically showing the position of the user U1 and the position of the user U1's home HM and office OF. The map information MP1-1 and the map information MP1-2 shown in FIG. 1 are for showing the difference at the time when the user's action information is acquired, and the range shown in the map information MP1-1 and the map information MP1-2. (Area) is the same area. Further, in the following, when the map information MP1-1 and MP1-2 will be described without particular distinction, the map information MP1 will be described. In the map information MP1 shown in FIG. 1, only the area A identified by the area ID "AR11" and the area K identified by the area ID "AR100" are shown, but the map information MP1 shows other areas. May also be included. The size of the area referred to here may be appropriately set according to the purpose of processing and the like. For example, as the area, areas of various sizes such as "prefecture", "city", "ward", and "town" may be appropriately set.

In FIG. 1, the extraction device 100 acquires the action information of the user U1 from the terminal device 10 used by the user U1 (step S11). For example, the extraction device 100 acquires the action information of the user U1 from the terminal device 10 in the normal life (daily life) of the user U1 as shown in the map information MP1-1. In the example of FIG. 1, the extraction device 100 acquires the action information of the user U1 at the date and time dt11 to dt52 and the like.

Then, the extraction device 100 stores the action information of the user U1 as an action history (step S12). In the example of FIG. 1, the extraction device 100 stores the action information of the user U1 as the action history in the action information storage unit 122.

For example, the "user ID" shown in the action information storage unit 122 in FIG. 1 indicates identification information for identifying a user. For example, the user identified by the user ID "U1" corresponds to the user U1 in FIG. Further, the "behavior ID" shown in the action information storage unit 122 in FIG. 1 indicates information for identifying the user's action. Further, the "type" shown in the action information storage unit 122 in FIG. 1 indicates information regarding the action type of the corresponding user. Further, the "content" shown in the action information storage unit 122 in FIG. 1 indicates the content targeted in the corresponding user's action. The “date and time” shown in the action information storage unit 122 in FIG. 1 indicates the date and time when the corresponding user's action was performed. Further, the "position" shown in the action information storage unit 122 in FIG. 1 indicates the position of the user when the corresponding action is performed. In the example of FIG. 1, for the sake of simplicity, the "position" is shown as an abstract symbol such as "area A", but may be information indicating latitude or longitude.

For example, in the example shown in FIG. 1, the user (user U1) identified by the user ID "U1" is an action identified by the action ID "AC11" (behavior AC11) or an action identified by the action ID "AC12". (Action AC12) etc. is shown.

Further, in the following, the action identified by the action ID “AC11” may be referred to as “action AC11”. As described above, in the following, when "action AC * (* is an arbitrary numerical value)" is described, it means that the action is an action identified by the action ID "AC *". For example, when "action AC15" is described, the action is an action identified by the action ID "AC15". Further, in the following, when the actions AC11, AC12, AC15, AC51, AC52 and the like of the user U1 will be described without particular distinction, they will be described as action AC.

In the example of FIG. 1, it is shown that the user U1 performed a search (behavior AC11) using the search queries "gourmet" and "area A" in the area A at the date and time dt11. For example, the action AC11 indicates that the search using the search queries "gourmet" and "area A" was performed on the terminal device 10 used by the user U1 at the date and time dt11. Further, the user U1 indicates that the settlement was made at the date and time dt12 at the restaurant A located in the area A. For example, the action AC12 indicates that the user U1 ate at the restaurant A at the date and time dt12 and made a payment using the terminal device 10 or the like.

Further, the user U1 indicates that the content C related to the gourmet site was browsed (behavior AC15) at the date and time dt15 in the area B. Further, the user U1 indicates that the search (action AC51) using the search queries "lunch" and "area A" was performed in the area A at the date and time dt51. Further, the user U1 indicates that the settlement was made at the date and time dt52 at the restaurant B located in the area A. For example, the action AC52 indicates that the user U1 ate at the restaurant B at the date and time dt52 and made a payment using the terminal device 10 or the like.

In the example of FIG. 1, the extraction device 100 stores the action history of the user U1 including the actions AC11, AC12, AC15, AC51, AC52, etc. as described above in the action information storage unit 122.

Then, the extraction device 100 estimates the user's context (step S13). In the example of FIG. 1, the extraction device 100 estimates the context at the time of each action AC of the user U1. For example, the extraction device 100 estimates the user's context based on the action history of the user U1 stored in the action information storage unit 122. In the example of FIG. 1, the extraction device 100 estimates the user's context information as shown in the context information storage unit 123.

The “user ID” shown in the context information storage unit 123 in FIG. 1 indicates identification information for identifying a user. For example, the user identified by the user ID "U1" corresponds to the user U1 shown in the example of FIG. The “date and time” shown in the context information storage unit 123 in FIG. 1 indicates the date and time when the corresponding user action was performed. Further, the "context ID" shown in the context information storage unit 123 in FIG. 1 indicates information for identifying the user's context. Further, the "position" shown in the context information storage unit 123 in FIG. 1 indicates the position of the user in the corresponding context. Further, the "search query" shown in the context information storage unit 123 in FIG. 1 indicates a search query used by the user in the corresponding context. "Query Q1" and "query Q2" in the "search query" indicate each search query used in combination by the user in the corresponding context.

In the example of FIG. 1, in the extraction device 100, the context at the time of the action AC11 corresponding to the search using the search queries “gourmet” and “area A” in the area A is the context identified by the context ID “CN11” (context). It is presumed to be CN11).

Further, in the following, the action identified by the context ID “CN11” may be referred to as “context CN11”. As described above, in the following, when "context CN * (* is an arbitrary numerical value)" is described, it means that the action is a context identified by the context ID "CN *". For example, when described as "context CN15", the action is a context identified by the context ID "CN15". Further, in the following, when the context CN11, CN12, CN15, etc. of the user U1 will be described without particular distinction, the context CN will be described.

Further, in the example of FIG. 1, the extraction device 100 estimates that the context at the time of the action AC12 corresponding to the settlement at the restaurant A in the area A is the context CN12.

Further, in the example of FIG. 1, the extraction device 100 estimates that the context at the time of the action AC15 corresponding to the viewing of the content C in the area B is the context CN15.

Further, in the example of FIG. 1, the extraction device 100 estimates that the context at the time of the action AC51 corresponding to the search using the search queries “lunch” and “area A” is the context CN11. In the example of FIG. 1, at the time of action AC51, the action AC11 and the position "area A" are common, and the search query is a combination of the query related to gourmet and the position "area A" and is common. Therefore, the extraction device 100 estimates that the context at the time of action AC51 is the same context CN11 as the context of action AC11.

Further, in the example of FIG. 1, the extraction device 100 estimates that the context at the time of the action AC52 corresponding to the settlement at the restaurant B in the area A is the context CN12. In the example of FIG. 1, at the time of action AC52, the action AC12 and the position "area A" are common, and the action is settlement and is common. Therefore, the extraction device 100 estimates that the context of the action AC52 is the same context CN12 as the context of the action AC12. The above estimation of the context is an example, and the extraction device 100 may estimate the context in any way.

Then, the extraction device 100 estimates the normal context of the user (step S14). In the example of FIG. 1, the extraction device 100 estimates the normal context of the user U1 based on the context at the time of each action AC of the user U1. For example, the extraction device 100 estimates the normal context of the user based on the context information of the user U1 stored in the context information storage unit 123.

In the example of FIG. 1, the context information storage unit 123 stores a large number of contexts CN11 and CN12 corresponding to the situation where the user U1 is located in the area A. Therefore, in the example of FIG. 1, it is estimated that the extraction device 100 is often a context CN corresponding to a situation in which the user U1 searches for gourmet food in area A and makes a payment at a restaurant in area A. Therefore, in the example of FIG. 1, the extraction device 100 estimates that the normal context of the user U1 is the contexts CN11 and CN12 corresponding to the situation located in the area A. Hereinafter, the context CN11 may be referred to as a normal context CN11, and the context CN12 may be referred to as a normal context CN12. The above estimation of the normal context is an example, and the extraction device 100 may perform the estimation of the normal context in any way.

Further, the extraction device 100 estimates the interest of the user U1 based on the action history of the user U1 (step S15). In the example of FIG. 1, as shown in the behavior information storage unit 122, for the user U1, a search using a query related to gourmet (behavior AC11, AC51), browsing of content related to gourmet (behavior AC15), and so on. , Many actions related to gourmet such as payment at a restaurant (actions AC12, AC52) are stored. Therefore, the extraction device 100 estimates the interest of the user U1 as the target "gourmet" based on the behavior history of the user U1. The estimation of the user's interest is an example, and the extraction device 100 may estimate the user's interest in any way.

From here, a case where the user U1 is extracted as the target user will be described. In FIG. 1, the extraction device 100 acquires the action information of the user U1 from the terminal device 10 used by the user U1 (step S16). For example, the extraction device 100 acquires the action information of the user U1 from the terminal device 10 as shown in the map information MP1-2 at the time of extracting the user U1. In the example of FIG. 1, it is assumed that the extraction device 100 acquires the action information of the user U1 after the date and time dt52. Specifically, the extraction device 100 acquires behavioral information related to a search using the search queries "business trip" and "area K" from the terminal device 10.

Then, the extraction device 100 estimates the current context of the user (step S17). In the example of FIG. 1, the extraction device 100 estimates the current context of the user U1 at the time of search based on the search queries "business trip" and "area K" and the position "area A". For example, the position "Area A" searched by the user U1 matches the context CN11, but the query used for the search is a "business trip" not related to gourmet food or another area "Area K" different from the area A. Therefore, the extraction device 100 estimates that the current context of the user U1 is different from the normal contexts CN11 and CN12. In the example of FIG. 1, the extraction device 100 estimates that the current context of the user U1 is a context CN100 different from the normal contexts CN11 and CN12, as shown in the current context information CC11. Hereinafter, the context CN100 may be referred to as the current context CN100. Although not shown in the example of FIG. 1, the extraction device 100 may also estimate the current context for other users.

Then, the extraction device 100 extracts the target user (step S18). For example, the extraction device 100 extracts a target user from a large number of users who have estimated the current context. In the example of FIG. 1, the extraction device 100 extracts a user whose current context is different from the normal context as a target user among a plurality of users stored in the user information storage unit 121. For example, as shown in the target user list UL11, the extraction device 100 extracts the user U1 whose current context CN100 is different from the normal contexts CN11 and CN12 as the target user.

Then, the extraction device 100 determines the recommended information to be provided to the user extracted as the target user (step S19). For example, the extraction device 100 determines, for each user extracted as a target user, information about a target that each user is interested in as recommended information. For example, when the extraction device 100 is searching for an area different from the area corresponding to the normal context (hereinafter, also referred to as “target area”), the extraction device 100 is the target that the user is interested in. , Determine information about the target related to the target area as recommended information.

For example, the extraction device 100 determines the content related to the target "gourmet" that the user U1 who is the target user is interested in as the recommended information. Further, the extraction device 100 is a position used for the search by the user U1 who is the target user at the time of estimating the current context CN100, and the content related to the position "area K" different from the area A corresponding to the normal contexts CN11 and CN12 is obtained. Decide on recommended information. In the example of FIG. 1, the extraction device 100 determines the content CT11 whose content is "gourmet" and whose target area is "area K" as recommended information to be provided to the user U1.

Then, the extraction device 100 provides recommended information to the target user (step S20). In the example of FIG. 1, the extraction device 100 provides the user U1 with the content CT11 whose content is “gourmet” and whose target area is “area K” as recommended information.

In this way, the extraction device 100 can appropriately extract the target user in a context different from the usual one. Therefore, since the extraction device 100 can appropriately extract the target user who performs the predetermined process, it is possible to provide appropriate recommended information to the extracted target user.

[1-1. Recommended information]
In the above-mentioned example, the case where the extraction device 100 provides the user U1 extracted as the target user with the recommended information regarding the target in which the user U1 is interested has been shown, but the extraction device 100 provides various information as the recommended information. May be provided as. The details of this point will be described in detail in FIG.

[1-2. context〕
Further, in the above-described example, the case where the extraction device 100 estimates the user's context based on the information about the user's position and the query used for the search is shown, but the extraction device 100 shows the case where the extraction device 100 estimates the user's context based on various information. You may infer the user's context.

Further, in the above-mentioned example, when the extraction device 100 estimates the user's context based on the information about the user's position and the query used for the search for the context corresponding to the combination of the user's position and the category related to the search query. However, the extraction device 100 may estimate the user's context based on various information.

[2. Extractor configuration]
Next, the configuration of the extraction device 100 according to the embodiment will be described with reference to FIG. FIG. 3 is a diagram showing a configuration example of the extraction device 100 according to the embodiment. As shown in FIG. 3, the extraction device 100 includes a communication unit 110, a storage unit 120, and a control unit 130. The extraction device 100 has an input unit (for example, a keyboard, a mouse, etc.) that receives various operations from the administrator of the extraction device 100, and a display unit (for example, a liquid crystal display, etc.) for displaying various information. You may.

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. Then, the communication unit 110 is connected to the network N by wire or wirelessly, and transmits / receives information to / from the terminal device 10.

(Memory unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as a hard disk or an optical disk. As shown in FIG. 3, the storage unit 120 according to the embodiment includes a user information storage unit 121, an action information storage unit 122, and a context information storage unit 123.

(User information storage unit 121)
The user information storage unit 121 according to the embodiment stores various information about the user. For example, the user information storage unit 121 stores various information related to user attributes. FIG. 4 is a diagram showing an example of a user information storage unit according to the embodiment. The user information storage unit 121 shown in FIG. 4 includes items such as "user ID", "age", "gender", and "interest".

The "user ID" indicates identification information for identifying a user. Further, "age" indicates the age of the user identified by the user ID. The "age" may be the specific age of the user identified by the user ID, such as 35 years old. Further, "gender" indicates the gender of the user identified by the user ID.

Further, "interest" indicates the interest of the user identified by the user ID. That is, "interest" indicates an object that the user identified by the user ID is highly interested in. In the example shown in FIG. 4, one "interest" is shown for each user, but there may be a plurality of "interests".

For example, in the example of FIG. 4, the age of the user (user U1) identified by the user ID "U1" is "20's", and the gender is "female". Also, for example, user U1 indicates that he is interested in "gourmet". Further, for example, in the example of FIG. 4, the age of the user (user U2) identified by the user ID "U2" is "30's", and the gender is "male". Also, for example, user U1 indicates that he is interested in "sports".

The user information storage unit 121 is not limited to the above, and may store various information depending on the purpose. For example, the user information storage unit 121 may store various information such as demographic attribute information and psychographic attribute information. For example, the user information storage unit 121 may store information such as a name, family structure, and income.

(Behavior information storage unit 122)
The behavior information storage unit 122 according to the embodiment stores various information regarding the behavior information regarding the user's environment. FIG. 5 is a diagram showing an example of the behavior information storage unit according to the embodiment. For example, the action information storage unit 122 stores information about the environment in which the user is placed at the position of the user at a certain time point (time) as the action information. For example, the action information storage unit 122 stores the weather information at the position of the user at a certain time point (time) as the action information. The action information storage unit 122 shown in FIG. 5 includes items such as "user ID", "action ID", "type", "content", "date and time", and "position".

The "user ID" indicates identification information for identifying a user. For example, the user identified by the user ID "U1" corresponds to the user U1 shown in the example of FIG. Further, the "behavior ID" indicates information that identifies the user's behavior. Further, "type" indicates information regarding the type of action of the corresponding user. In addition, "content" indicates the content targeted in the corresponding user's behavior. The "date and time" indicates the date and time when the corresponding user action was performed. Although the "date and time" is abstractly illustrated as "dt11" or the like, a specific date and time such as "January 25, 2017 19:31:52" may be stored. Further, the "position" indicates the position of the user when the corresponding action is performed. In the example of FIG. 5, for the sake of simplicity, the "position" is shown as an abstract symbol such as "area A", but information indicating latitude and longitude and "Z town, Y city, X prefecture" are shown. It may be information indicating an address such as.

For example, in the example shown in FIG. 5, the user (user U1) identified by the user ID “U1” is an action identified by the action ID “AC11” (behavior AC11) or an action identified by the action ID “AC12”. (Action AC12) etc. is shown. Specifically, the user U1 indicates that the search (action AC11) using the search queries "gourmet" and "area A" was performed in the area A at the date and time dt11. For example, the action AC11 indicates that the search using the search queries "gourmet" and "area A" was performed on the terminal device 10 used by the user U1 at the date and time dt11. Further, the user U1 indicates that the settlement was made at the date and time dt12 at the restaurant A located in the area A. For example, the action AC12 indicates that the user U1 ate at the restaurant A at the date and time dt12 and made a payment using the terminal device 10 or the like.

For example, the user U1 indicates that the content C related to the gourmet site is browsed (behavior AC15) at the date and time dt15 in the area B. For example, the user U1 indicates that the search (action AC51) using the search queries "lunch" and "area A" was performed in the area A at the date and time dt51. Further, for example, the user U1 indicates that the payment was made at the date and time dt52 at the restaurant B located in the area A.

The behavior information storage unit 122 is not limited to the above, and may store various information depending on the purpose. Further, although FIG. 5 shows a case where the action information is stored in the action information storage unit 122 for each user ID, the action information is not limited to each user ID and may be stored, for example, in chronological order.

(Context information storage unit 123)
The context information storage unit 123 according to the embodiment stores various information related to the user's context information. FIG. 6 is a diagram showing an example of the context information storage unit according to the embodiment. For example, the context information storage unit 123 stores information about the user's position at a certain time point (time) and the query used for the search as context information in association with the context ID at that time point. The context information storage unit 123 shown in FIG. 6 includes items such as "user ID" and "context information". Further, the "context information" includes items such as "date and time", "context ID", "location", and "search query". Further, the "search query" includes items such as "query Q1" and "query Q2".

The "user ID" indicates identification information for identifying a user. For example, the user identified by the user ID "U1" corresponds to the user U1 shown in the example of FIG. The "date and time" indicates the date and time when the corresponding user action was performed. Although the "date and time" is abstractly illustrated as "dt11" or the like, a specific date and time such as "January 25, 2017 19:31:52" may be stored. Further, the "context ID" indicates information for identifying the user's context. The "position" indicates the position of the user in the corresponding context. In the example of FIG. 5, for the sake of simplicity, the "position" is shown as an abstract symbol such as "area A", but information indicating latitude and longitude and "Z town, Y city, X prefecture" are shown. It may be information indicating an address such as. Further, the "search query" indicates a search query used by the user in the corresponding context. "Query Q1" and "query Q2" in the "search query" indicate each search query used in combination by the user in the corresponding context.

For example, in the example shown in FIG. 5, a user (user U1) identified by the user ID “U1” searches in area A using the search queries “gourmet” and “area A” (for example, corresponding to action AC11). The context at the time of execution (date and time dt11) indicates that the context is identified by the context ID “CN11” (context CN11). Further, for example, the context when the user U1 performs a predetermined action (for example, payment at the restaurant A corresponding to the action AC12) in the area A (date and time dt12) is a context (context) identified by the context ID “CN12”. It indicates that it is CN12).

Further, for example, the context when the user U1 performs a predetermined action (for example, viewing the content C corresponding to the action AC15) in the area B (date and time dt15) is a context identified by the context ID “CN15” (context CN15). ).

Further, for example, when the user U1 performs a search (for example, corresponding to the action AC51) using the search queries "lunch" and "area A" in the area A, the context (date and time dt51) is determined by the context ID "CN11". Indicates that the context is identified (context CN11). Further, for example, the context when the user U1 performs a predetermined action (for example, payment at the restaurant B corresponding to the action AC52) in the area A (date and time dt52) is a context (context) identified by the context ID “CN12”. It indicates that it is CN12).

The context information storage unit 123 is not limited to the above, and may store various information depending on the purpose. Further, although FIG. 5 shows a case where the action information is stored in the context information storage unit 123 for each user ID, the action information is not limited to each user ID and may be stored, for example, in chronological order.

(Control unit 130)
Returning to the description of FIG. 3, the control unit 130 is a controller, and is stored in a storage device inside the extraction device 100 by, for example, a CPU (Central Processing Unit) or an MPU (Micro Processing Unit). It is realized by executing various programs (corresponding to an example of an extraction program) using the RAM as a work area. Further, the control unit 130 is a controller, and is realized by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 3, the control unit 130 includes an acquisition unit 131, an estimation unit 132, an extraction unit 133, and a provision unit 134, and realizes or executes an information processing function or operation described below. .. The internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 3, and may be another configuration as long as it is a configuration for performing information processing described later. Further, the connection relationship of each processing unit included in the control unit 130 is not limited to the connection relationship shown in FIG. 3, and may be another connection relationship.

(Acquisition unit 131)
The acquisition unit 131 acquires various information. The acquisition unit 131 acquires various information from an external device such as the terminal device 10. Further, the acquisition unit 131 acquires various information from the user information storage unit 121, the action information storage unit 122, the context information storage unit 123, and the like.

For example, the acquisition unit 131 acquires the user's behavior information. For example, the acquisition unit 131 acquires economic status information regarding the user's economic status.

In the example of FIG. 1, the acquisition unit 131 acquires the action information of the user U1 from the terminal device 10 used by the user U1. In the example of FIG. 1, the acquisition unit 131 acquires the action information of the user U1 from the terminal device 10 during the normal life (daily life) of the user U1 as shown in the map information MP1-1. In the example of FIG. 1, the acquisition unit 131 acquires the action information of the user U1 at the date and time dt11 to dt52 and the like.

In the example of FIG. 1, the acquisition unit 131 acquires the action information of the user U1 from the terminal device 10 used by the user U1. In the example of FIG. 1, when the user U1 is extracted, the acquisition unit 131 acquires the action information of the user U1 from the terminal device 10 as shown in the map information MP1-2. In the example of FIG. 1, the acquisition unit 131 acquires the action information of the user U1 after the date and time dt52. In the example of FIG. 1, the acquisition unit 131 acquires the action information related to the search using the search queries “business trip” and “area K” from the terminal device 10.

(Estimation unit 132)
The estimation unit 132 generates various information. For example, the estimation unit 132 estimates various types of information based on the information acquired from the terminal device 10. For example, the estimation unit 132 estimates various types of information based on the user information storage unit 121, the behavior information storage unit 122, the context information storage unit 123, and the like.

For example, the estimation unit 132 estimates the user's context based on the behavior information acquired by the acquisition unit 131. For example, the estimation unit 132 estimates the user's interests based on the behavior information acquired by the acquisition unit 131.

In the example of FIG. 1, the estimation unit 132 estimates the user's context. In the example of FIG. 1, the estimation unit 132 estimates the context at the time of each action AC of the user U1. In the example of FIG. 1, the estimation unit 132 estimates the user's context based on the action history of the user U1 stored in the action information storage unit 122. In the example of FIG. 1, the estimation unit 132 estimates the user's context information as shown in the context information storage unit 123.

In the example of FIG. 1, the estimation unit 132 estimates that the context at the time of the action AC11 corresponding to the search using the search queries “gourmet” and “area A” in the area A is the context CN11. In the example of FIG. 1, the estimation unit 132 estimates that the context at the time of the action AC12 corresponding to the settlement at the restaurant A in the area A is the context CN12. In the example of FIG. 1, the estimation unit 132 estimates that the context at the time of the action AC15 corresponding to the viewing of the content C in the area B is the context CN15.

Further, in the example of FIG. 1, the estimation unit 132 estimates that the context at the time of the action AC51 corresponding to the search using the search queries "lunch" and "area A" is the context CN11. In the example of FIG. 1, the estimation unit 132 estimates that the context at the time of action AC51 is the same context CN11 as the context of action AC11.

Further, in the example of FIG. 1, the estimation unit 132 estimates that the context at the time of the action AC52 corresponding to the settlement at the restaurant B in the area A is the context CN12. In the example of FIG. 1, at the time of action AC52, the action AC12 and the position "area A" are common, and the action is settlement and is common. Therefore, the estimation unit 132 estimates that the context of the action AC52 is the same context CN12 as the context of the action AC12.

Further, in the example of FIG. 1, the estimation unit 132 estimates the normal context of the user. In the example of FIG. 1, the estimation unit 132 estimates the normal context of the user U1 based on the context at the time of each action AC of the user U1. In the example of FIG. 1, the estimation unit 132 estimates the normal context of the user based on the context information of the user U1 stored in the context information storage unit 123.

In the example of FIG. 1, it is estimated that the estimation unit 132 is often a context CN corresponding to a situation in which the user U1 searches for gourmet food in area A and makes a payment at a restaurant in area A. In the example of FIG. 1, the estimation unit 132 estimates that the normal context of the user U1 is the contexts CN11 and CN12 corresponding to the situation located in the area A.

In the example of FIG. 1, the estimation unit 132 estimates the interest of the user U1 based on the action history of the user U1. In the example of FIG. 1, the estimation unit 132 estimates the interest of the user U1 as the target "gourmet" based on the behavior history of the user U1.

In the example of FIG. 1, the estimation unit 132 estimates the current context of the user. In the example of FIG. 1, the estimation unit 132 estimates the current context of the user U1 at the time of search based on the search queries “business trip” and “area K” and the position “area A”. In the example of FIG. 1, the estimation unit 132 estimates that the current context of the user U1 is different from the normal contexts CN11 and CN12. In the example of FIG. 1, the estimation unit 132 estimates that the current context of the user U1 is a context CN100 different from the normal contexts CN11 and CN12, as shown in the current context information CC11.

(Extractor 133)
The extraction unit 133 extracts various information. For example, the extraction unit 133 extracts various information from the user information storage unit 121, the behavior information storage unit 122, the context information storage unit 123, and the like. For example, the extraction unit 133 extracts various information based on the information estimated by the estimation unit 132.

For example, in the extraction unit 133, the current context, which is the user's context based on the behavior information acquired by the acquisition unit 131, is the user's daily life among the user's past contexts based on the user's past behavior history. If it is different from the normal context, which is the context corresponding to, the user is extracted as the target user to perform a predetermined process.

For example, when the current context of the user based on the information about the search query used by the user is different from the normal context based on the information about the search query used by the user in the past, the extraction unit 133 extracts the user as the target user. .. For example, when the current context of the user based on the user's position information is different from the normal context based on the user's past position information, the extraction unit 133 extracts the user as the target user.

For example, when the current context regarding the position of the user is different from the normal context regarding the position of the user in daily life, the extraction unit 133 extracts the user as the target user. For example, when the current context of the user is different from the normal context of the user, the extraction unit 133 extracts the user as a target user corresponding to the interest of the user. For example, when the current context of the user is different from the normal context of the user, the extraction unit 133 extracts the user as a target user who provides a service corresponding to the economic situation estimated based on the economic situation information of the user. To do.

In the example of FIG. 1, the extraction unit 133 extracts the target user. In the example of FIG. 1, the extraction unit 133 extracts the target user from a large number of users whose current context is estimated. In the example of FIG. 1, the extraction unit 133 extracts a user whose current context is different from the normal context as a target user among a plurality of users stored in the user information storage unit 121. In the example of FIG. 1, the extraction unit 133 extracts the user U1 whose current context CN100 is different from the normal contexts CN11 and CN12 as the target user, as shown in the target user list UL11.

In the example of FIG. 1, the extraction unit 133 determines the recommended information to be provided to the user extracted as the target user. In the example of FIG. 1, the extraction unit 133 determines, for each user extracted as the target user, information about the target that each user is interested in as recommended information. In the example of FIG. 1, when the user extracted as the target user is searching for an area (target area) different from the area corresponding to the normal context, the extraction unit 133 is a target that the user is interested in. Determine information about the target related to the target area as recommended information.

In the example of FIG. 1, the extraction unit 133 determines the content related to the target “gourmet” that the user U1 who is the target user is interested in as the recommended information. Further, in the example of FIG. 1, the extraction unit 133 is a position used for the search by the user U1 who is the target user at the time of estimating the current context CN100, and is a position different from the area A corresponding to the normal contexts CN11 and CN12. Determine the content related to "Area K" as recommended information. In the example of FIG. 1, the extraction unit 133 determines the content CT11 whose content is "gourmet" and whose target area is "area K" as recommended information to be provided to the user U1.

(Providing section 134)
The providing unit 134 provides various information to an external device such as the terminal device 10. For example, the providing unit 134 may provide various information estimated by the estimating unit 132 to the external device. In addition, the providing unit 134 may provide various types of information extracted by the extracting unit 133 to the external device.

For example, the providing unit 134 provides the target user extracted by the extracting unit 133 with recommended information that is information according to the current context and prompts the target user to perform a predetermined action. For example, the providing unit 134 provides a user with a service corresponding to an economic situation estimated based on the user's economic situation information.

In the example of FIG. 1, the providing unit 134 provides recommended information to the target user. In the example of FIG. 1, the providing unit 134 provides the user U1 with the content CT11 whose content is “gourmet” and whose target area is “area K” as recommended information.

[3. Extraction process flow]
Next, the procedure of the extraction process by the extraction system 1 according to the embodiment will be described with reference to FIG. 7. FIG. 7 is a flowchart showing an example of the extraction process according to the embodiment.

As shown in FIG. 7, when the extraction device 100 acquires the behavior information (step S101: Yes), the extraction device 100 estimates the context based on the behavior information (step S102). For example, the extraction device 100 acquires information about the user's position information, a query used by the user for searching, and the like as action information from the terminal device 10 used by the user. Further, for example, the extraction device 100 acquires user behavior information from the user information storage unit 121 (see FIG. 4). For example, the extraction device 100 estimates the user's context based on the action information acquired from the terminal device 10 used by the user and the user's action information stored in the user information storage unit 121 (see FIG. 4). Further, when the extraction device 100 does not acquire the action information (step S101: No), the extraction device 100 repeats the process of step S101.

Then, when the estimated context is different from the normal context (step S103: Yes), the extraction device 100 determines whether or not the context satisfies a predetermined condition (step S104).

When the context satisfies a predetermined condition (step S104: Yes), the extraction device 100 provides a predetermined service (step S105).

Further, when the estimated context does not differ from the normal context (step S103: No) or when the context does not satisfy a predetermined condition (step S104: No), the extraction device 100 returns to step S101 and repeats the process.

[4. Providing other recommended information]
In the example of FIG. 1, the case where the recommended information according to the interest of the user is provided is shown, but the extraction device 100 may provide various recommended information. This point will be described with reference to FIG. FIG. 8 is a diagram showing an example of the extraction process according to the embodiment. Specifically, FIG. 8 is an example showing a case where recommended information is provided according to the economic situation of the user. The same points as in FIG. 1 will be omitted as appropriate.

From here, the flow of the extraction process will be described with reference to FIG. In the example shown in FIG. 8, the processing of steps S11 to S13 shown in FIG. 1 and the processing after the context estimation of the actions AC11, AC12, AC15, AC51, AC52 and the like will be described. Further, in the example shown in FIG. 8, it is assumed that the user information storage unit 121A includes an item "status" in which information indicating the financial status of the user is stored.

Further, the map information MP1-1 and MP1-2 shown in FIG. 8 are diagrams schematically showing the position of the user U1 and the position of the user U1's home HM and office OF. The map information MP1-1 and the map information MP1-2 shown in FIG. 8 are for showing the difference at the time when the user's action information is acquired, and the range shown in the map information MP1-1 and the map information MP1-2. (Area) is the same area. Further, in the following, when the map information MP1-1 and MP1-2 will be described without particular distinction, the map information MP1 will be described. In the map information MP1 shown in FIG. 8, only the area A identified by the area ID “AR11” and the area L identified by the area ID “AR200” are shown, but the map information MP1 shows other areas. May also be included.

In FIG. 8, the extraction device 100 acquires the action information of the user U1 from the terminal device 10 used by the user U1 (step S51). For example, the extraction device 100 acquires the behavior information of the user U1 from the terminal device 10 as shown in the map information MP1-1 during the normal life of the user U1. In the example of FIG. 1, it is assumed that the extraction device 100 acquires the action information of the user U1 after the date and time dt52. Specifically, the extraction device 100 acquires behavioral information related to a search using the search queries "borrowing" and "interest" from the terminal device 10.

Then, the extraction device 100 stores the action information of the user U1 as an action history (step S52). In the example of FIG. 8, the extraction device 100 stores the action information regarding the action AC200 of the user U1 as the action history in the action information storage unit 122. In the example of FIG. 8, the extraction device 100 stores in the action information storage unit 122 the information that the user U1 has performed a search (action AC200) using the search queries “borrowing” and “interest” in the area A at the date and time dt200. To do.

Then, the extraction device 100 estimates the user's context (step S53). In the example of FIG. 8, the extraction device 100 estimates the context of the user U1 at the time of the action AC200. For example, the extraction device 100 estimates the user's context based on the action history of the user U1 stored in the action information storage unit 122. In the example of FIG. 8, the extraction device 100 estimates the context information of the user U1 at the date and time dt200 when the action AC200 is performed, as shown in the context information storage unit 123.

In the example of FIG. 8, the extraction device 100 estimates that the context at the time of the action AC200 corresponding to the search using the search queries “borrowing” and “interest” in the area A is the context CN200. For example, the position "Area A" searched by the user U1 matches the context CN11, but the query used for the search is "borrowing" or "interest" not related to gourmet, so the extraction device 100 uses the date and time dt200. The context of user U1 in is estimated to be context CN200. The extraction device 100 may extract the user U1 as the target user at the date and time dt200 and provide the recommended information, but the extraction device 100 does not provide the recommended information because the user U1 is located in the area A. And.

Then, the extraction device 100 estimates the normal context of the user (step S54). In the example of FIG. 8, the extraction device 100 estimates the normal context of the user U1 based on the context at the time of each action AC of the user U1. For example, the extraction device 100 estimates the normal context of the user based on the context information of the user U1 stored in the context information storage unit 123. In the example of FIG. 8, similarly to FIG. 1, the extraction device 100 estimates that the normal context of the user U1 is the normal contexts CN11 and CN12.

Further, the extraction device 100 estimates the user's status (economic status) based on various information of the user (step S55). In the example of FIG. 8, in order to simplify the explanation, a case where the user's status (economic situation) is estimated based on the user's action history stored in the action information storage unit 122 is shown, but the extraction device 100 May use any information to estimate the user's status (economic status). In the example of FIG. 8, as shown in the action information storage unit 122, the user U1 performs a search (behavior AC200) using the query “borrowing” and the query “interest” at the date and time dt200. Therefore, the extraction device 100 estimates the status of the user U1 as "out of money" based on the action history of the user U1. The estimation of the user status is an example, and the extraction device 100 may estimate the user status in any way.

From here, a case where the user U1 is extracted as the target user will be described. In FIG. 8, the extraction device 100 acquires the action information of the user U1 from the terminal device 10 used by the user U1 (step S56). For example, the extraction device 100 acquires the action information of the user U1 from the terminal device 10 as shown in the map information MP1-2 at the time of extracting the user U1. In the example of FIG. 8, it is assumed that the extraction device 100 acquires the action information of the user U1 after the date and time dt200. Specifically, the extraction device 100 acquires action information indicating that the user U1 is located in the area L from the terminal device 10.

Then, the extraction device 100 estimates the current context of the user (step S57). In the example of FIG. 8, the extraction device 100 estimates the current context of the user U1 at the time of acquiring the action information based on the position “area L” of the user U1. For example, since the position "area L" of the user U1 at the time of acquiring the action information is different from the position "area A" corresponding to the normal contexts CN11 and CN12 of the user U1, the extraction device 100 sets the current context of the user U1. It is presumed that it is different from the normal contexts CN11 and CN12. In the example of FIG. 8, the extraction device 100 estimates that the current context of the user U1 is a context CN201 different from the normal contexts CN11 and CN12, as shown in the current context information CC51. Hereinafter, the context CN201 may be referred to as the current context CN201. Although not shown in the example of FIG. 8, the extraction device 100 may estimate the current context for other users as well.

Then, the extraction device 100 extracts the target user (step S58). For example, the extraction device 100 extracts a target user from a large number of users who have estimated the current context. In the example of FIG. 8, the extraction device 100 extracts a user whose current context is different from the normal context as a target user among a plurality of users stored in the user information storage unit 121A. For example, as shown in the target user list UL51, the extraction device 100 extracts the user U1 whose current context CN201 is different from the normal contexts CN11 and CN12 as the target user.

Then, the extraction device 100 determines the recommended information to be provided to the user extracted as the target user (step S59). For example, the extraction device 100 determines as recommended information for each user extracted as a target user, according to the status of each user. For example, when the user extracted as the target user is located in an area different from the area corresponding to the normal context (hereinafter, also referred to as “target area”), the extraction device 100 can handle the status of the user. Determine information about stores located in the area as recommended information.

For example, since the status of the user U1 who is the target user is "lack of money", the extraction device 100 determines the content related to the store capable of providing the service to the user whose economic situation is severe as the recommended information. Further, the extraction device 100 determines the content related to the store located in the position "area L" of the user U1 at the time of estimating the current context CN201 as the recommended information. In the example of FIG. 8, the extraction device 100 determines the content CT 51 whose content is “caching” and whose target area is “area L” as recommended information to be provided to the user U1. Specifically, the extraction device 100 determines the content CT 51 indicating the cashing store CF located in the area L as recommended information to be provided to the user U1.

Then, the extraction device 100 provides recommended information to the target user (step S60). In the example of FIG. 8, the extraction device 100 provides the content CT51 indicating the cashing store CF located in the area L to the user U1 as recommended information because the content is “caching”.

In this way, the extraction device 100 can appropriately extract the target user in a context different from the usual one. Therefore, since the extraction device 100 can appropriately extract the target user who performs the predetermined process, it is possible to provide appropriate recommended information to the extracted target user.

[4-1. status〕
In the above-mentioned example, the case where the extraction device 100 estimates whether or not the user's status is "lack of money" is shown, but the extraction device 100 may estimate various statuses of the user. For example, the extraction device 100 may estimate whether or not the user has sufficient money as the status, that is, whether or not the user is "rich". In this case, when the target user includes a user whose status is presumed to be "rich", the extraction device 100 provides the target user with content related to a service that spends money, such as a high-class restaurant, as recommended information. You may.

[5. effect〕
As described above, the extraction device 100 according to the embodiment has an acquisition unit 131 and an extraction unit 133. The acquisition unit 131 acquires the user's behavior information. In the extraction unit 133, the current context, which is the user's context based on the behavior information acquired by the acquisition unit 131, corresponds to the daily life of the user among the past contexts of the user based on the past behavior history of the user. If the context is different from the normal context, the user is extracted as the target user to perform a predetermined process.

As a result, when the current context is different from the normal context, the extraction device 100 according to the embodiment appropriately extracts the target user to perform the predetermined process by extracting the user as the target user to perform the predetermined process. can do.

Further, in the extraction device 100 according to the embodiment, the extraction unit 133 indicates that the current context of the user based on the information about the search query used by the user is different from the normal context based on the information about the search query used by the user in the past. , The user is extracted as the target user.

As a result, when the current context based on the information about the search query used by the user is different from the normal context based on the information about the search query used by the user in the past, the extraction device 100 according to the embodiment performs a predetermined process for the user. By extracting as the target user to perform the predetermined process, the target user to perform the predetermined process can be appropriately extracted.

Further, in the extraction device 100 according to the embodiment, when the current context of the user based on the user's position information is different from the normal context based on the user's past position information, the extraction unit 133 extracts the user as the target user. To do.

As a result, when the current context based on the user's position information is different from the normal context based on the user's past position information, the extraction device 100 according to the embodiment extracts the user as a target user to perform a predetermined process. Therefore, it is possible to appropriately extract the target user to perform a predetermined process.

Further, the extraction device 100 according to the embodiment has a providing unit 134. The providing unit 134 provides the target user extracted by the extracting unit 133 with recommended information that is information according to the current context and prompts the target user to perform a predetermined action.

As a result, the extraction device 100 according to the embodiment provides the target user with information according to the current context and recommended information for urging the target user to perform a predetermined action, so that the target user is in a different context from the usual one. Appropriate information can be provided to.

Further, in the extraction device 100 according to the embodiment, when the current context regarding the position of the user is different from the normal context regarding the position of the user in daily life, the extraction unit 133 extracts the user as the target user.

As a result, when the current context regarding the position of the user is different from the normal context regarding the position in the daily life of the user, the extraction device 100 according to the embodiment determines the user by extracting the user as a target user to perform a predetermined process. It is possible to appropriately extract the users to be processed.

Further, the extraction device 100 according to the embodiment has an estimation unit 132. The estimation unit 132 estimates the user's interests based on the behavior information acquired by the acquisition unit 131. When the current context of the user is different from the normal context of the user, the extraction unit 133 extracts the user as a target user corresponding to the interest of the user.

As a result, when the current context of the user is different from the normal context of the user, the extraction device 100 according to the embodiment performs a predetermined process by extracting the user as a target user corresponding to the interest of the user. It is possible to appropriately extract the users to be performed.

Further, in the extraction device 100 according to the embodiment, the acquisition unit 131 acquires economic status information regarding the economic status of the user. When the current context of the user is different from the normal context of the user, the extraction unit 133 extracts the user as a target user who provides a service corresponding to the economic situation estimated based on the economic situation information of the user.

As a result, the extraction device 100 according to the embodiment estimates the economic situation based on the user's economic situation information when the current context based on the user's economic situation information is different from the normal context based on the user's economic situation information. By extracting as the target user who provides the service corresponding to the above, the target user who performs a predetermined process can be appropriately extracted.

[6. Hardware configuration]
The extraction device 100 according to the above-described embodiment is realized by, for example, a computer 1000 having a configuration as shown in FIG. FIG. 9 is a hardware configuration diagram showing an example of a computer that realizes the function of the extraction device. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, an HDD (Hard Disk Drive) 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400, and controls each part. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started, a program that depends on the hardware of the computer 1000, and the like.

The HDD 1400 stores a program executed by the CPU 1100, data used by such a program, and the like. The communication interface 1500 receives data from another device via the network N and sends it to the CPU 1100, and transmits the data generated by the CPU 1100 to the other device via the network N.

The CPU 1100 controls an output device such as a display or a printer, and an input device such as a keyboard or a mouse via the input / output interface 1600. The CPU 1100 acquires data from the input device via the input / output interface 1600. Further, the CPU 1100 outputs the generated data to the output device via the input / output interface 1600.

The media interface 1700 reads a program or data stored in the recording medium 1800 and provides the program or data to the CPU 1100 via the RAM 1200. The CPU 1100 loads the program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase change rewritable Disk), a magneto-optical recording medium such as MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. And so on.

For example, when the computer 1000 functions as the extraction device 100 according to the embodiment, the CPU 1100 of the computer 1000 realizes the function of the control unit 130 by executing the program loaded on the RAM 1200. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, these programs may be acquired from another device via the network N.

Although some of the embodiments and modifications of the present application have been described in detail with reference to the drawings, these are examples and vary based on the knowledge of those skilled in the art, including the embodiments described in the disclosure line of the invention. It is possible to carry out the present invention in another form obtained by modifying or improving the above.

[7. Others]
Further, among the processes described in the above-described embodiments and modifications, all or part of the processes described as being automatically performed can be manually performed, or the processes described as being manually performed. It is also possible to automatically perform all or part of the processed processing by a known method. In addition, the processing procedure, specific name, and information including various data and parameters shown in the above document and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

Further, each component of each of the illustrated devices is a functional concept, and does not necessarily have to be physically configured as shown in the figure. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or part of the device is functionally or physically distributed / physically in any unit according to various loads and usage conditions. It can be integrated and configured.

In addition, the above-described embodiments and modifications can be appropriately combined as long as the processing contents do not contradict each other.

In addition, the above-mentioned "section, module, unit" can be read as "means" or "circuit". For example, the acquisition unit can be read as an acquisition means or an acquisition circuit.

1 Extraction system 100 Extractor 121 User information storage unit 122 Action information storage unit 123 Context information storage unit 130 Control unit 131 Acquisition unit 132 Estimating unit 133 Extraction unit 134 Providing unit 10 Terminal device N network

Claims (12)

An acquisition unit that acquires user behavior information,
The current context, which is the context of the user based on the behavior information acquired by the acquisition unit, is the context corresponding to the daily life of the user among the past contexts of the user based on the past behavior history of the user. When different from the normal context, an extraction unit that extracts the user as a target user who provides information about a different area indicated by a character string input by the user in an area different from the area corresponding to the normal context.
An extraction device characterized by comprising. An acquisition unit that acquires user behavior information,
The current context, which is the context of the user based on the behavior information acquired by the acquisition unit, is the context corresponding to the daily life of the user among the past contexts of the user based on the past behavior history of the user. When different from the normal context, the target user performs a predetermined process related to the user's behavior in the area different from the area corresponding to the normal context and in the different area indicated by the character string input by the user. Extraction part to extract as
An extraction device characterized by comprising. The extraction unit
If the current context of the user based on the information about the search query used by the user is different from the normal context based on the information about the search query used by the user in the past, the user is extracted as the target user. The extraction device according to claim 1 or 2. The extraction unit
Claims 1 to 3 include extracting the user as the target user when the current context of the user based on the location information of the user is different from the normal context based on the past location information of the user. The extraction device according to any one of the above. A providing unit that provides the target user extracted by the extracting unit with recommended information that is information according to the current context and prompts the target user to perform a predetermined action.
The extraction device according to any one of claims 1 to 4, further comprising. The extraction unit
According to any one of claims 1 to 5, when the current context regarding the position of the user is different from the normal context regarding the position of the user in daily life, the user is extracted as the target user. The extraction device described. An estimation unit that estimates the user's interests based on the behavior information acquired by the acquisition unit,
With more
The extraction unit
One of claims 1 to 6, wherein when the current context of the user is different from the normal context of the user, the user is extracted as the target user corresponding to the interest of the user. The extraction device described in. The acquisition unit
Acquire economic situation information about the user's economic situation,
The extraction unit
When the current context of the user is different from the normal context of the user, the user is extracted as the target user who provides the service corresponding to the economic situation estimated based on the economic situation information of the user. The extraction device according to any one of claims 1 to 7. An extraction method performed by a computer
The acquisition process to acquire user behavior information and
The current context, which is the context of the user based on the behavior information acquired by the acquisition process, is the context corresponding to the daily life of the user among the past contexts of the user based on the past behavior history of the user. When different from the normal context, the extraction step of extracting the user as a target user who provides information about the different area indicated by the character string input by the user in an area different from the area corresponding to the normal context.
An extraction method characterized by containing. Acquisition procedure to acquire user behavior information and
The current context, which is the context of the user based on the behavior information acquired by the acquisition procedure, is the context corresponding to the daily life of the user among the past contexts of the user based on the past behavior history of the user. When different from the normal context, the extraction procedure for extracting the user as a target user who provides information about the different area indicated by the character string entered by the user in an area different from the area corresponding to the normal context.
An extraction program characterized by having a computer execute. An extraction method performed by a computer
The acquisition process to acquire user behavior information and
The current context, which is the context of the user based on the behavior information acquired by the acquisition process, is the context corresponding to the daily life of the user among the past contexts of the user based on the past behavior history of the user. When different from the normal context, the target user performs a predetermined process related to the user's behavior in the area different from the area corresponding to the normal context and in the different area indicated by the character string input by the user. Extraction process to extract as
An extraction method characterized by containing. Acquisition procedure to acquire user behavior information and
The current context, which is the context of the user based on the behavior information acquired by the acquisition procedure, is the context corresponding to the daily life of the user among the past contexts of the user based on the past behavior history of the user. When different from the normal context, the target user performs a predetermined process related to the user's behavior in the area different from the area corresponding to the normal context and in the different area indicated by the character string input by the user. Extraction procedure to extract as
An extraction program characterized by having a computer execute.

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