JP2009048296A - Factor analyzing device, factor analyzing system, factor analyzing method, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a factor analyzing device for analyzing a factor of variation of population density. <P>SOLUTION: This factor analyzing device 100 is provided with an area information acquisition part 102 for acquiring information of an area where variation of population density exceeds a prescribed range; and an event occurrence decision part 104 for deciding whether or not an event has been held inside the area at the point of time of the acquisition of the information of the area on the basis of the information of the area. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a factor analysis device, a factor analysis system, a factor analysis method, and a program, and more particularly to a factor analysis technique for analyzing a factor whose population density has changed.

  In recent years, portable information terminals represented by mobile phones and the like have come into widespread use. Recently, along with the remarkable development of wireless communication technology and information processing technology, the functions of these information terminals have become very advanced, and various information can be added in addition to normal data communication and call functions. Service has been provided. One of them is location information service. For example, the location information of the user holding the mobile terminal 10 is displayed on a map, or a store close to the current location of the user is extracted based on the location information, and the information is displayed on the screen. To do. For grasping such location information, location information of the base station 20 with which the mobile terminal 10 communicates is used, or location information of the mobile terminal 10 itself obtained by GPS (Global Positioning System) or the like is used.

  On the other hand, attention has been focused on a technique for analyzing the dynamic distribution variation of the population density by applying the position information acquired from the mobile terminal 10 as described above. This is based on the current situation in which the majority of the population is a user of some mobile terminal 10, and the situation in which local population density fluctuations can be recognized by grasping the movement information of each mobile terminal 10 is reversed. It was used for. For example, the following Patent Document 1 discloses a technique for observing fluctuations in population distribution based on position information distributed from the mobile terminal 10 to the base station 20 and statistically processing the observation results to make a short-term future prediction. Is disclosed.

JP 2002-342557 A

  However, no technique for analyzing the fluctuation factors of population density is disclosed. In other words, even if a situation in which the population density has greatly fluctuated is detected, it is currently impossible to determine whether the fluctuation is a sudden event or due to some event occurrence. In response to this situation, for example, event organizers can easily observe the population distribution of the area where the event is held using the location information of the mobile terminal 10 or the like, and see the effect of attracting customers. They have a desire to analyze objectively.

  Therefore, the present invention has been made in view of the above problems, and an object of the present invention is to analyze the factors in association with events when the population density fluctuates relatively greatly. To provide a new and improved factor analysis apparatus, factor analysis system, factor analysis method, and program.

  In order to solve the above-described problem, according to an aspect of the present invention, an area information acquisition unit that acquires information on an area in which a fluctuation in population density exceeds a predetermined range, and information on the area based on the information on the area An event occurrence determination unit that determines whether or not an event has been held in the area at the time of acquisition is provided.

  The factor analysis apparatus may further include a storage unit having an event database in which information indicating an event holding period and information indicating an event holding position are described in association with each other. Furthermore, the event occurrence determination unit may determine whether an event has been held in the area based on a description in the event database.

  The event database may store event information for identifying individual events. The factor analysis apparatus may further include a reputation information acquisition unit that acquires the event information as a keyword and acquires the reputation information of the event from a predetermined or arbitrary information source.

  The reputation information acquisition unit may acquire the event reputation information from a predetermined or arbitrary information source using the event information and the area information as keywords.

  In addition, the reputation information acquisition unit uses one or both of an event name included in the event information and an area name included in the area information as a keyword, and the reputation information of the event is predetermined or arbitrary information. It may be obtained from a source.

  Further, the factor analysis device extracts a phrase that matches a predetermined phrase assigned a score from each of the reputation information, and totals the scores of the extracted phrases, thereby obtaining a score of the reputation information. An evaluation value calculation unit for calculating

  Further, the factor analysis device compares a deviation amount between an expected value of population density and an actually detected population density value with a range of deviation amount set according to the score of the reputation information, Based on the comparison result, a goodness degree determination unit for determining whether the event is good or bad may be further provided.

Moreover, in order to solve the said subject, according to another viewpoint of this invention, the terminal device which each person hold | maintains, the base station which acquires the positional information on the said terminal device, and the positional information which the said base station acquired A factor analysis system including a factor analysis device that analyzes a change factor of population density based on the above is proposed.
However, the terminal device includes a communication unit that communicates with the base station. The base station includes a communication unit that communicates with the terminal device located in the area of the local station, and an area information transmission unit that transmits information on the terminal device located in the area of the local station to the factor analysis device. Prepare. Then, the factor analysis device includes an area information acquisition unit that acquires information of an area where the population density fluctuation exceeds a predetermined range, and an event within the area at the time of acquisition of the area information based on the area information. An event occurrence determination unit that determines whether or not the event has been held.

  Moreover, in order to solve the said subject, according to another viewpoint of this invention, based on the area information acquisition step from which the information of the area where the fluctuation of population density exceeds a predetermined range is acquired, and the information of the said area, And an event occurrence determination step of determining whether or not an event has been held in the area at the time of acquisition of the area information.

  In order to solve the above problems, according to another aspect of the present invention, there is provided a program for causing a computer to realize the function of each component included in the factor analysis apparatus. Furthermore, a recording medium on which the program is recorded is provided.

  As described above, according to the present invention, when the population density fluctuates relatively greatly, it is possible to analyze the factor in association with the event.

  Exemplary embodiments of the present invention will be described below in detail with reference to the accompanying drawings. In addition, in this specification and drawing, about the component which has the substantially same function structure, duplication description is abbreviate | omitted by attaching | subjecting the same code | symbol.

<One Embodiment of the Present Invention>
First, a preferred embodiment of the present invention will be described in detail. One of the objectives of this embodiment is to determine whether the increase is a sudden phenomenon or due to the occurrence of an event or the like when the population density in a certain region changes relatively greatly. There is. Another object is to determine whether the event is favorable or not when it is determined that the change in population density is caused by an event or the like.

  Therefore, in order to achieve the above object, the present embodiment collects information from a predetermined or arbitrary information source based on information on a region or a spatial region where the population density has changed relatively greatly, and analyzes the variation factor. Provide technology to do. Hereinafter, a configuration example of an apparatus and a system for realizing this technique will be described in detail.

[System configuration of factor analysis system 1000]
First, the system configuration of the factor analysis system 1000 according to the present embodiment will be described with reference to FIG. FIG. 1 is an explanatory diagram showing a system configuration of a factor analysis system 1000 according to the present embodiment.

  As shown in FIG. 1, the factor analysis system 1000 mainly includes a mobile terminal 10, a base station 20, a storage device 30, a display device 40, and a factor analysis device 100.

(Portable terminal 10, base station 20)
The mobile terminal 10 is a user terminal held by each person (hereinafter referred to as a user) constituting the population distribution. The mobile terminal 10 provides location information of each user. Note that the mobile terminal 10 according to the present embodiment only needs to have a function of providing the location information of the user to the factor analysis device 100 directly or indirectly.

  Therefore, the mobile terminal 10 may be, for example, a mobile phone, a PHS (Personal Handy-phone System), a PDA (Personal Digital Assistant) having a communication function, or an in-vehicle navigation system. Alternatively, it may be a ticket having an IC card function. In the case of a ticket for a predetermined transportation system having an IC card function, the mobile terminal 10 uses at least information on a boarding section relating to the predetermined transportation system and time information passed through the ticket gate to a ticket gate (IC card reader / writer). Therefore, the user's location information can be transmitted indirectly via the ticket gate.

  The base station 20 relays information transmitted from the mobile terminal 10 located in the area of the local station to other base stations 20 and mobile terminals 10, and automatically acquires information acquired from the other base stations 20 and mobile terminals 10. The data is transmitted to the mobile terminal 10 located in the station area. Therefore, the base station 20 can acquire the information of the mobile terminal 10 located in the area of the own station constantly or at predetermined time intervals.

  For example, in FIG. 1, three mobile terminals 10 are located in the area A1. Therefore, the base station 20 having jurisdiction over the area A1 can grasp that these three mobile terminals 10 are located in the area A1. When the mobile terminal 10 located in the area A1 at a certain time moves to the area A2 at another time, the base station 20 that detects information of the mobile terminal 10 changes for each time. As a result, the movement information of the mobile terminal 10 can be grasped from the information of the mobile terminal 10 detected by the base station 20.

  In the above method, the position information of the mobile terminal 10 is grasped by the base station 20 unit. For example, the position information is grasped by the individual mobile terminal unit 10 by using the GPS function provided in the mobile terminal 10. Is also possible. Moreover, when the portable terminal 10 is an in-vehicle navigation system, it is grasped in units of spots such as interchanges and parking areas. Further, in the case where the mobile terminal 10 is a boarding ticket or the like having an IC card function, the position information is grasped in units of boarding sections starting from the bid station. In this manner, position information having different reference units is grasped according to various embodiments of the mobile terminal 10. It should be noted that the form of the base station 20 varies depending on the embodiment of the mobile terminal 10.

  Each base station 20 included in the factor analysis system 1000 provides the factor analysis apparatus 100 with position information of the mobile terminal 10 located in the area of the own station. At this time, for example, the base station 20 may provide the factor analysis apparatus 100 with information (time) when the position information is acquired and information on the area covered by the base station 20.

(Factor analysis device 100)
The factor analysis device 100 can identify a region or a spatial region where the population density has fluctuated based on information acquired from the base station 20, and can analyze the variation factor based on the identified information. At this time, the factor analysis device 100 acquires information from the storage device 30 directly connected, or acquires information from a predetermined or arbitrary information source connected via the network 932, and performs the above analysis. It is possible to use. Furthermore, the factor analysis device 100 is connected to the display device 40, and can output an analysis result relating to the fluctuation factor of the population density to the display device 40.

  The system configuration of the factor analysis system 1000 according to this embodiment has been described above. As described above, the factor analysis system 1000 aggregates the position information acquired from the base station 20 and the information acquired from other information sources in the factor analysis device 100, detects the distribution variation of the population density, The fluctuation factor can be analyzed. That is, the feature of this embodiment is the functional configuration of the factor analysis device 100.

[Functional configuration of factor analysis apparatus 100]
Therefore, the functional configuration of the factor analysis device 100 according to the present embodiment will be described in detail with reference to FIG. FIG. 2 is an explanatory diagram illustrating a functional configuration of the factor analysis device 100 according to the present embodiment.

  As shown in FIG. 2, the factor analysis device 100 mainly includes an area information acquisition unit 102, an event occurrence determination unit 104, a storage unit 106, a reputation information acquisition unit 108, an evaluation value calculation unit 110, and a strong performance. The degree determination unit 112 and the result output unit 114 are configured.

(Area information acquisition unit 102)
The area information acquisition unit 102 acquires position information of each terminal device 10 from the base station 20. The area information acquisition unit 102 may acquire time information indicating the time point when the position information is acquired, in addition to the position information of each terminal device 10. Further, the area information acquisition unit 102 calculates the population density based on the position information acquired from the base station 20. In order to realize these functions, the area information acquisition unit 102 includes a position information collection unit 122 and a distribution analysis unit 124.

(Location information collection unit 122)
The location information collection unit 122 collects user location information provided directly or indirectly by the mobile terminal 10. For example, the position information collection unit 122 acquires the position information collected in the base station 20 from the mobile terminal 10 of each user. Or the positional information collection part 122 acquires the positional information collected via the ticket gate from each user's IC card function-equipped ticket. Of course, the position information collection unit 122 may collect position information directly from the mobile terminal 10 held by each user. Depending on the technically feasible accuracy, the collected location information may be, for example, information on the latitude / longitude of the location, information on the area where the user is located, information on the ride section, or the nearest interchange. And information on parking areas, etc.

(Distribution analysis unit 124)
The distribution analysis unit 124 calculates the population density based on the location information collected by the location information collection unit 122. For example, the distribution analysis unit 124 can calculate the population density by calculating the number of users per unit area based on the number of mobile terminals 10 collected for each area. In addition, the distribution analysis unit 124 may calculate the number of users located in a predetermined area as the population density per area. Note that the distribution analysis unit 124 may calculate the population density every predetermined time, or may calculate the population density every time position information is collected.

  Then, when the calculation result exceeds the upper limit of the predetermined range centered on the predetermined expected value or falls below the lower limit, the distribution analysis unit 124 detects position information corresponding to the population density (hereinafter, specific position information). ). For example, the distribution analysis unit 124 extracts the latitude / longitude of the point as the specific position information. Note that the predetermined range described above may be, for example, a range of ± 30% of the predetermined predicted value in consideration of accidental fluctuations of the predetermined predicted value. As described above, the position information provided from the position information collection unit 122 may be provided in various forms other than latitude and longitude. Therefore, the distribution analysis unit 124 may have a function of converting the specific position information into a predetermined form (for example, latitude / longitude).

  In addition, said predicted value is a population density normally observed in the point or area. For example, the distribution analysis unit 124 may use a statistical value such as an average value or an intermediate value of population density observed during a sufficiently long predetermined period (for example, several years) as the predicted value. In addition, the distribution analysis unit 124 may use the population density observed during a time period or a time period when an event or the like that may be a population fluctuation factor is not held as the predicted value. For example, in addition to the above method, various statistical methods using a weighted average or a least square method can be applied to determine the predicted value.

(Event occurrence determination unit 104, storage unit 106)
The storage unit 106 holds an event database 142. In the event database 142, for example, an event name and a time and place where the event is held are recorded in association with each other. In addition, in the event database 142, for example, information such as an organizer name, performer name, planned number of visitors, plan type, or target age of the event may be described in association with the event name.

  The event occurrence determination unit 104 determines whether an event has occurred or held at the time when the specific position information is acquired in the region indicated by the specific position information extracted by the area information acquisition unit 102. At this time, the event occurrence determination unit 104 refers to the event database 142 to determine whether an event has occurred or held in the area indicated by the specific position information. The event occurrence determination unit 104 searches the event database 142 using time information related to the point in time when the specific position information is acquired and information on the area indicated by the specific position information as key information, and determines whether there is event information. When event information exists, the event occurrence determination unit 104 extracts part or all of the event information.

  The event database 142 may be stored in the storage device 30 outside the factor analysis device 100. In this case, the event occurrence determination unit 104 accesses the storage device 30 and refers to the event database 142 to search for event information corresponding to the specific position information. Of course, the event occurrence determination unit 104 may refer to both the event database 142 stored in the storage unit 106 in the factor analysis device 100 and the event database 142 stored in the external storage device 30.

(Reputation information acquisition unit 108)
The reputation information acquisition unit 108 designates the event information extracted by the event occurrence determination unit 104 or the specific position information acquired by the distribution analysis unit 124 as key information, and sets reputation information related to the key information as predetermined or Obtain from reputation information included in any information source. However, the reputation information acquisition unit 108 may specify both the event information and the specific position information as key information and acquire reputation information corresponding to the key information. The reputation information acquisition unit 108 may select reputation information corresponding to the key information using a search server or the like existing on a predetermined network.

  Examples of the information source include a website on the Internet, a bulletin board site, a blog site, an event information site, and the like. In addition, the information source includes, for example, reputation information of events held by a server device or a factor analysis device 100 on a LAN (Local Area Network). The reputation information is, for example, information related to a reputation including an opinion, a criticism, and the like transmitted by an individual, an organization / organization, or the like regarding an event before or after the event. Of course, the reputation information may include an impression of a user who participated in the event, a commentary on the event, and the like.

  By the way, when specifying the specific position information as the key information, the reputation information acquisition unit 108 converts the specific position information into an expression format that can be used for keyword search. This conversion process is realized by the area / name conversion unit 132 included in the reputation information acquisition unit 108. For example, the area / name conversion unit 132 converts the specific position information expressed by latitude / longitude into an expression format (for example, place name, interchange name, parking area name, station name, route name, etc.) that can be used for keyword search. Can be converted. Further, the area / name conversion unit 132 may have a function of converting a place name on the map into a common name or facility name of the area.

(Evaluation Value Calculation Unit 110)
The evaluation value calculation unit 110 analyzes the reputation information extracted by the reputation information acquisition unit 108, and analyzes the factors that cause the population density to fluctuate in the area corresponding to the specific position information extracted by the distribution analysis unit 124. For example, the evaluation value calculation unit 110 detects a predetermined phrase (hereinafter referred to as an evaluation target phrase) included in the reputation information and calculates an evaluation value (hereinafter referred to as a score) based on the appearance frequency of each evaluation target phrase. To do. At this time, the evaluation value calculation unit 110 calculates a score of reputation information with reference to a database (for example, FIG. 4) in which the evaluation target words and scores are described in association with each other. Further, when a plurality of pieces of reputation information are extracted for one specific position information, the evaluation value calculation unit 110 calculates a score for some or all pieces of reputation information, and the total value is analyzed as a factor of population variation. To use.

(About scoring method)
Here, a reputation information scoring method by the evaluation value calculation unit 110 will be briefly described with reference to FIGS. 4 to 6. FIG. 4 is an explanatory diagram showing an example of a score table T100 that associates evaluation target phrases with scores. FIG. 5 is an example of reputation information K100. FIG. 6 is an example of a score table T200 indicating the total score calculated for each piece of reputation information.

  First, referring to FIG. The score table T100 describes a plurality of evaluation target words and scores corresponding to each evaluation target word. In the example of FIG. 4, “Good”, “Bad”, “Excellent”, and “Very easy” are explicitly described as evaluation target phrases. The score value is +0.8 for “good”, −0.8 for “bad”, +1.0 for “great”, and −0.9 for “noisy”.

  Reference is now made to FIG. The reputation information K100 includes the evaluation target words “noisy” K102, “good” K104, and “bad” K106 described in the score table T100. Therefore, the evaluation value calculation unit 110 refers to the score table T100, and the score of “noisy” K102 is −0.9, the score of “good” K104 is +0.8, and the score of “bad” K106 is −0.8. Are totaled to calculate a total score of -0.9 of the reputation information K100. When multiple pieces of reputation information exist for certain event information, the evaluation value calculation unit 110 calculates individual total scores for each piece of reputation information.

  Reference is now made to FIG. The score table T200 describes the total score calculated by the evaluation value calculation unit 110 for each of a plurality of pieces of reputation information (sentences No. 1 to No. 7). As shown in the score table T200, when the total score is calculated for all reputation information, the evaluation value calculation unit 110 further sums the total score calculated for each reputation information, and calculates the total score for the event. To do. In the case of the score table T200, the total score for the event is -3.4.

  The scoring method by the evaluation value calculation unit 110 has been specifically described above. As described above, the evaluation value calculation unit 110 can calculate a score for each event.

(Goodness degree determination unit 112)
Based on the score calculated for each event by the evaluation value calculation unit 110, the goodness degree determination unit 112 determines whether the event is good or bad. For example, the favorable degree determination unit 112 determines that the favorable score is obtained when the total score for a plurality of reputation information detected using the event information as the key information is high, and determines that the favorable condition is indicated when the total score is low. However, the favorable degree determination unit 112 determines a determination criterion according to the amount of deviation between the actually detected population density value and the predicted population density value. For example, the favorable degree determination unit 112 has a score determination table T300 that represents the correspondence between the above-described deviation amount and the determination criterion, and determines whether the event is good or bad based on the score determination table T300.

(About good / bad judgment criteria)
Here, with reference to FIG. 7, the good / bad judgment criterion of the event by the good degree judgment unit 112 will be described. FIG. 7 is an explanatory diagram showing a score determination table T300 used for determining whether an event is good or bad.

  As shown in FIG. 7, the score determination table T300 describes the amount of deviation (deviation amount) between the actual population density value and the predicted population density value in correspondence with the criterion for determining the score range. For example, when the total score of the event is −3.4 (see the score table T200), the total score is included in the score range −4 ≦ score <−1 corresponding to the deviation amount −30% to −10%. It is. Therefore, the favorable degree determination unit 112 determines that the difference is between the actual population density value and the expected value when it is less than −30%, and determines that it is favorable when it exceeds −10%. Further, when the amount of deviation between the actual population density value and the predicted value is included in the range of −30% to −10%, the favorable degree determination unit 112 determines that the customer acquisition rate (population density) is the same as the previous reputation. To do.

  In the above, the favorable / unsatisfactory determination criterion by the favorable degree determination unit 112 has been described. As described above, the favorable degree determination unit 112 can determine whether the event is good or bad by using the total score calculated for each event and the amount of deviation of the population density as determination materials.

(Result output unit 114)
The result output unit 114 outputs the determination result by the favorable degree determination unit 112 to the display device 40. Further, the result output unit 114 may output the notification to the display device 40 when the event occurrence determination unit 104 notifies that the event information corresponding to the specific position information does not exist. Furthermore, when the reputation information acquisition unit 108 notifies that the reputation information corresponding to the event information does not exist, the result output unit 114 may output the notification to the display device 40.

  Heretofore, the functional configuration of the factor analysis device 100 according to the present embodiment has been described in detail. When the factor analysis apparatus 100 is used, it can be determined whether the detected variation in population distribution is caused by the occurrence of an event or suddenly. In addition, when the change in the population distribution is caused by the occurrence of an event, the event is identified, and then whether the event is good or bad is determined based on information acquired from a predetermined or arbitrary information source. It becomes possible. As a result, it becomes possible for event organizers to easily determine whether or not the held event has attracted customers according to the previous reputation, and more accurate statistical information can be obtained. It will be possible to more accurately estimate the effect of attracting customers at the event.

[Factor analysis method]
Next, a factor analysis method by the factor analysis apparatus 100 will be described with reference to FIG. FIG. 3 is an explanatory diagram showing a factor analysis method according to the present embodiment.

  First, the location information collection unit 122 acquires location information of each mobile terminal 10 (S102). Next, the distribution analysis unit 124 identifies an area having a population density that exceeds or falls below a predetermined expected range, and extracts position information (specific position information) corresponding to the area (S104). Next, the area / name conversion unit 132 converts the specific position information expressed by latitude / longitude into an expression format (for example, place name) that can be used for keyword search (S106).

  In addition, the event occurrence determination unit 104 refers to the event database 142 to determine whether there is an event held at the time when the specific position information is acquired. At this time, if there is an event, the event occurrence determination unit 104 extracts event information (for example, the name of the event) related to the event from the event database 142 and generates a list.

  Next, the reputation information acquisition unit 108 performs a keyword search using the specific position information converted into a place name or the like and the event information extracted by the event occurrence determination unit 104 as key information, and receives the reputation information from a predetermined or arbitrary information source. Is acquired (S108). Next, the evaluation value calculation unit 110 extracts a predetermined evaluation target phrase from the reputation information (S110). Furthermore, the evaluation value calculation unit 110 scores reputation information based on the evaluation target words.

  Next, the favorable degree determination unit 112 determines whether or not the evaluation target word / phrase is included in the reputation information corresponding to the specific position information, and whether or not the population density corresponding to the specific position information is high. When the event does not exist, the number of evaluation target words is not (ie, “0”), and the AND condition (S112) that the population density is irregularly high is satisfied, the result output unit 114 displays the specific position. The fact that the fluctuation factor of the population density corresponding to the information is a sudden event is output to the display device 40 (S114). At this time, the result output unit 114 may output both the name and time information of the area to the display device 40. In the above example and the example shown in FIG. 3, “one of the evaluation target words is“ 0 ”” as one of the AND conditions in step S112, but instead of this, “the number of evaluation target words is extremely high. Or less than a predetermined number ”. The predetermined number can be, for example, the number of reputation information.

  On the other hand, when the AND condition of step S112 is not satisfied, the factor analysis device 100 proceeds to the process of step S116. In step S116, the favorable degree determination unit 112, based on the score determination table T300 (see FIG. 7), the score calculated for each piece of reputation information by the evaluation value calculation unit 110, the actual population density, and the estimated population density It is determined whether or not the amount of deviation between the two corresponds to (S116). If it corresponds, the factor analysis apparatus 100 ends the factor analysis process. On the other hand, if not corresponding, the factor analysis device 100 proceeds to the process of step S118.

  In step S118, the factor analysis apparatus 100 determines whether or not the event occurrence determination unit 104 determines that an event exists, and determines whether or not the current stage process is related to the event (S118). When related to the event, the result output unit 114 outputs the event name and time information to the display device 40 together with the result of the good / not good event determined by the good degree determination unit 112 (S120). On the other hand, when not related to the event, the factor analysis device 100 ends the factor analysis processing.

  The factor analysis method according to the present embodiment has been described above. When the above method is applied, it can be determined whether the increase factor of the population density is abrupt or due to the occurrence of an event. Further, when it is determined that the change in population density is caused by an event, it can be determined whether the event is favorable, unsatisfactory, or within an expected range. As a result, it is possible to easily determine whether or not the event has attracted customers according to the previous reputation.

  As described above, according to the apparatus and method according to the present embodiment, predetermined or arbitrary information is obtained by using information on an area where the population distribution has irregularly changed or information on events held in the area. Based on the reputation information extracted from the source, it becomes possible to analyze the relationship between fluctuations in population distribution and events. Furthermore, since the reputation of the event can be evaluated by comparing the score of reputation information with the estimated value of population density, it is possible to objectively recognize the gap between the previous reputation and reality.

[Hardware configuration]
The function of each component included in the above-described device can be realized by, for example, an information processing device having a hardware configuration illustrated in FIG. FIG. 8 is an explanatory diagram showing a hardware configuration of an information processing apparatus capable of realizing the functions of each component of the apparatus apparatus, device, or terminal.

  As shown in FIG. 8, the information processing apparatus mainly includes a CPU (Central Processing Unit) 902, a ROM (Read Only Memory) 904, a RAM (Random Access Memory) 906, a host bus 908, a bridge. 910, an external bus 912, an interface 914, an input unit 916, an output unit 918, a storage unit 920, a drive 922, a connection port 924, and a communication unit 926.

  The CPU 902 functions as, for example, an arithmetic processing unit or a control unit, and controls the overall operation of each component or a part thereof based on various programs recorded in the ROM 904, the RAM 906, the storage unit 920, or the removable recording medium 928. . The ROM 904 stores, for example, a program read by the CPU 902 and data used for calculation. The RAM 906 temporarily or permanently stores, for example, a program that is read into the CPU 902 and various parameters that change as appropriate when the program is executed. These components are connected to each other by, for example, a host bus 908 capable of high-speed data transmission. The host bus 908 is connected to an external bus 912 having a relatively low data transmission speed via a bridge 910, for example.

  The input unit 916 is an operation unit such as a mouse, a keyboard, a touch panel, a button, a switch, and a lever. The input unit 916 may be remote control means (so-called remote controller) capable of transmitting a control signal using infrared rays or other radio waves. Note that the input unit 916 includes an input control circuit for transmitting information input using the above-described operation means to the CPU 902 as an input signal.

  The output unit 918 is, for example, a display device such as a CRT (Cathode Ray Tube), an LCD (Liquid Crystal Display), a PDP (Plasma Display Panel), or an ELD (Electro-Luminescence Display), an audio device such as a speaker, headphones, etc. It is a device capable of visually or audibly notifying acquired information to a user, such as a printer, a mobile phone, or a facsimile.

  The storage unit 920 is a device for storing various data, and includes, for example, a magnetic storage device such as a hard disk drive (HDD), a semiconductor storage device, an optical storage device, or a magneto-optical storage device. Is done.

  The drive 922 is a device that reads information recorded on a removable recording medium 928 such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, or writes information to the removable recording medium 928. The removable recording medium 928 is, for example, a DVD medium, a Blu-ray medium, an HD-DVD medium, a compact flash (CF) (registered trademark), a memory stick, or an SD memory card (Secure Digital memory card). Of course, the removable recording medium 928 may be, for example, an IC card (Integrated Circuit Card) on which a non-contact IC chip is mounted, an electronic device, or the like.

  The connection port 924 is a port for connecting an external connection device 930 such as a USB (Universal Serial Bus) port, an IEEE 1394 port, a SCSI (Small Computer System Interface), an RS-232C port, or an optical audio terminal. is there. The external connection device 930 is, for example, a printer, a portable music player, a digital camera, a digital video camera, or an IC recorder.

  The communication unit 926 is a communication device for connecting to the network 932. For example, a communication card for wired or wireless LAN (Local Area Network), Bluetooth (registered trademark), or WUSB (Wireless USB), optical communication A router, a router for ADSL (Asymmetric Digital Subscriber Line), or a modem for various communications. The network 932 connected to the communication unit 926 is configured by a wired or wireless network, such as the Internet, home LAN, infrared communication, visible light communication, broadcast, or satellite communication.

  As mentioned above, although preferred embodiment of this invention was described referring an accompanying drawing, it cannot be overemphasized that this invention is not limited to the example which concerns. It will be apparent to those skilled in the art that various changes and modifications can be made within the scope of the claims, and these are naturally within the technical scope of the present invention. Understood.

It is explanatory drawing which shows the structure of the factor analysis system which concerns on one Embodiment of this invention. It is explanatory drawing which shows the function structure of the factor analyzer which concerns on the same embodiment. It is explanatory drawing which shows the factor analysis method which concerns on the same embodiment. It is explanatory drawing which shows an example of the score table which matches an evaluation object word and a score. It is explanatory drawing which shows an example of reputation information. It is explanatory drawing which shows an example of the total score calculated for every reputation information. It is explanatory drawing which shows an example of the score determination table which prescribes | regulates the criterion of a score range. It is explanatory drawing which shows the hardware structural example of the factor analyzer which concerns on the same embodiment.

Explanation of symbols

1000 factor analysis system 100 factor analysis device 102 area information acquisition unit 104 event occurrence determination unit 106 storage unit 108 reputation information acquisition unit 110 evaluation value calculation unit 112 favorable degree determination unit 114 result output unit 122 position information collection unit 124 distribution analysis unit 132 Area / name conversion unit 142 Event database T100, T200 Score table T300 Score determination table K100 Reputation information K102, K104, K106 Evaluation target phrases

Claims (10)

An area information acquisition unit for acquiring information of an area where the population density fluctuation exceeds a predetermined range;
Based on the information on the area, an event occurrence determination unit that determines whether an event has occurred in the area at the acquisition time of the area information,
A factor analysis device comprising: A storage unit having an event database in which information indicating an event holding period and information indicating a holding position of the event are described in association with each other;
The factor analysis apparatus according to claim 1, wherein the event occurrence determination unit determines whether an event has occurred in the area based on a description in the event database. The event database stores event information for identifying individual events,
The factor analyzer is
The factor analysis apparatus according to claim 1, further comprising a reputation information acquisition unit that acquires the event information as a keyword and acquires the reputation information of the event from a predetermined or arbitrary information source.   The factor analysis according to claim 3, wherein the reputation information acquisition unit acquires the event information and the area information as keywords, and acquires the reputation information of the event from a predetermined or arbitrary information source. apparatus.   The reputation information acquisition unit uses one or both of an event name included in the event information and an area name included in the area information as a keyword, and obtains reputation information of the event from a predetermined or arbitrary information source. The factor analysis device according to claim 3, wherein the factor analysis device is acquired.   An evaluation value calculation unit that calculates a score of the reputation information by extracting a phrase that matches a predetermined phrase assigned a score from each of the reputation information and summing the scores of the extracted phrases The factor analysis device according to claim 3, further comprising:   Compare the amount of divergence between the expected value of population density and the actually detected population density value with the range of divergence amount set according to the score of the reputation information, and based on the comparison result, The factor analysis apparatus according to claim 6, further comprising a favorable degree determination unit that determines whether the event is good or bad. Factor analysis including a terminal device held by each person, a base station that acquires location information of the terminal device, and a factor analysis device that analyzes a change factor of population density based on the location information acquired by the base station A system,
The terminal device includes a communication unit that communicates with the base station,
The base station
A communication unit that communicates with the terminal device located in the area of the own station;
An area information transmission unit for transmitting information of a terminal device located in the area of the local station to the factor analysis device;
With
The factor analyzer is
An area information acquisition unit for acquiring information of an area where the population density fluctuation exceeds a predetermined range;
Based on the information on the area, an event occurrence determination unit that determines whether an event has occurred in the area at the acquisition time of the area information,
A factor analysis system characterized by comprising: An area information acquisition step in which information on an area where the population density fluctuation exceeds a predetermined range is acquired;
An event occurrence determination step for determining whether an event has occurred in the area at the time of acquisition of the area information based on the area information;
The factor analysis method characterized by including.   The program for making a computer implement | achieve the function of each component with which the factor analysis apparatus in any one of Claims 1-7 is provided.

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