JP2022069198A - Behavior analysis apparatus, guidance information provision system, and method of the same - Google Patents

Abstract

To analyze human behavior using movement histories of users who use public transportation and provide guidance information that suits individual characteristics.SOLUTION: A behavior analysis apparatus 1 that analyzes information on movement of people who use public transportation using a computer including a processing unit and a storage unit, comprises: a behavior history creation unit 101 for creating user behavior history using public transportation boarding/alighting information of users who get on and off using electronic media and each user's payment information or reservation information handled when purchasing products or providing services at stores; a route estimation unit 102 for estimating a destination that the user goes to and a route that the user takes based on the behavior history; a purpose estimation unit 104 for estimating the purpose of the user's movement based on the behavior history; and a diversity calculation unit 105 for calculating user's destination diversity, route diversity, or movement diversity for each purpose based on the estimated destination, route, or purpose.SELECTED DRAWING: Figure 1

Description

The present invention relates to a behavior analysis device, a guidance information providing system and its method, and a guidance information providing program, and in particular, analyzes behavior characteristics based on a person's movement history and provides guidance information suitable for individual characteristics. It's about technology.

Various studies have been conducted on avoiding congestion of users in public transportation. By measuring and distributing the congestion status of their own flights, transportation companies are encouraging users to voluntarily change their behavior so as to avoid using them during busy hours. However, in urban areas, congestion during commuting has not been resolved, and transportation companies are demanding more effective congestion mitigation measures. On the other hand, maintaining the number of users by encouraging people to go out and migrate in anticipation of future population decline is also an important issue for maintaining the transportation business.

Recently, with the spread of electronic tickets and electronic payment technologies that can be used with transportation IC cards and mobile terminals, efforts to acquire data on the movement and purchase of people and analyze them for marketing purposes have expanded. ing. A code that identifies the user is attached to the electronic ticket that can be used with the transportation IC card or mobile terminal, and the location of the ticket gate that the owner of the transportation IC card or electronic ticket has passed through and the location of the ticket gate are used. It is possible to keep track of the services reserved and the stores where shopping was done.

For example, in Patent Document 1, a behavior pattern indicating a user's behavior is analyzed based on a past position information history collected from a mobile terminal, and the movement with a high possibility that the user moves from the behavior pattern and the current position information. A recommendation information distribution system that estimates an area, selects recommended information about the estimated moving area, and presents it to a user via a mobile phone terminal is disclosed.

Further, in Patent Document 2, in a navigation system provided with a destination recommendation function, data of movement history between points of a plurality of users is associated with an action pattern, an action pattern matching the action tendency of the target user is determined, and an action is taken. A navigation system is disclosed that preferentially proposes a point (a place of the user's preference) that is likely to be beneficial to each user based on a pattern as a recommended point.

Japanese Unexamined Patent Publication No. 2011-100182 Japanese Unexamined Patent Publication No. 2014-199212 (Patent No. 6098302)

The technique disclosed in Patent Document 1 uses the destination and the direction of movement as the positional relationship pattern, and does not consider the means of movement or the route. Furthermore, the acceptability of the subject's recommendations is not taken into consideration.

Therefore, an object of the present invention is to analyze behavior using the behavior history of a user who uses public transportation and to provide guidance information suitable for individual characteristics.
In particular, the present invention focuses on the diversity of individual movements in which individual tastes and behavioral characteristics appear, selects a subject, and provides guidance information.

A preferable example of the behavior analysis device according to the present invention is a behavior analysis device that analyzes information on the movement of a person using public transportation by using a computer having a processing unit and a storage unit.
User behavior history using public transportation boarding / alighting information of users who get on and off using electronic media, and payment information or reservation information for each user handled when purchasing products or providing services at stores. With the action history creation department to create
Based on the behavior history, a route estimation unit that estimates the destination and route to which the user goes, and a route estimation unit.
A purpose estimation unit that estimates the purpose of the user's movement based on the behavior history,
An action having the estimated destination, the route, or a diversity calculation unit that calculates the destination diversity, the route diversity, or the movement diversity for each purpose of the user based on the purpose. It is an analyzer.

A preferred example of the guidance information providing system according to the present invention is a guidance information providing system that provides guidance information to a user who uses public transportation using an electronic medium.
(1) The first computer that analyzes information about the movement of users,
(2) It has a second computer that provides guidance information to the mobile terminal owned by the user according to the analysis by the first computer.
(1) The first computer is
User behavior history using public transportation boarding / alighting information of users who get on and off using electronic media, and payment information or reservation information for each user handled when purchasing products or providing services at stores. With the action history creation department to create
Based on the behavior history, a route estimation unit that estimates the destination and route to which the user goes, and a route estimation unit.
A purpose estimation unit that estimates the purpose of the user's movement based on the behavior history,
It has a destination diversity, a route diversity, or a diversity calculation unit for calculating a travel diversity for each purpose based on the estimated destination, the route, or the purpose. ,
(2) The second computer is
A recommendation condition setting unit that presets the conditions for recommendations that provide guidance information to users, and a recommendation condition setting unit.
Using the information on getting on and off the public transportation of the user who gets on and off using electronic media, and the payment information or reservation information for each user handled when purchasing goods or providing services at the store, the user's destination and Estimate the route,
Among the estimated users in the route, the destination diversity, route diversity, or movement diversity for each purpose of the user calculated by the diversity calculation unit of the first computer is determined. It is a guidance information providing system characterized in that a target person who satisfies the conditions set in the recommendation condition setting unit is selected and guidance information is sent to the target person.

The present invention is also grasped as a behavior analysis method executed by the behavior analysis device and a guidance information providing method executed by the guidance information providing system.

According to the present invention, it is possible to analyze behavior using the behavior history of a user who uses public transportation and provide guidance information suitable for individual characteristics. In particular, it is possible to select a target person and provide guidance information by paying attention to the diversity of individual movements in which individual tastes and behavioral characteristics appear.

It is a figure which shows the whole structure of the guidance information provision system by one Example. It is a figure which shows the example of the ticket gate entry / exit history DB 210. It is a figure which shows the example of the reservation / settlement record DB 300. It is a figure which shows the example of the store information DB 400. It is a figure which shows the example of the user information DB 500. It is a figure which shows the example of the action history DB 600. It is a figure which shows the example of the moving summary DB 700. It is a figure which shows the example of the movement diversity finger DB 800. It is a figure which shows the example of the position information DB 900. It is a figure which shows the behavior analysis processing flow. It is a figure which shows the movement diversity calculation processing flow. It is a figure which shows the recommendation processing flow. It is a figure which shows the example of the recommendation screen of a user terminal 6. It is a figure which shows the example of the recommendation sending condition specification screen of an administrator terminal 7.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

FIG. 1 is a diagram showing an overall configuration of a guidance information providing system according to an embodiment.
The guidance information provision system analyzes human behavior using the movement history of users who use public transportation using electronic media such as transportation IC cards and mobile terminals, and provides guidance that suits the characteristics of the user. It is a system that provides information. The guidance information providing system includes, for example, an analysis computer 1, a recommendation computer 3, a user information management computer 4, a movement record management computer 5, a user terminal 6, and an administrator terminal 7 via a network 2. It is an information processing system configured by connecting.

The analysis computer 1, the recommendation computer 3, the user information management computer 4, and the movement record management computer 5 all have a storage unit for storing programs and various data as hardware, a CPU (processor) for executing the program, and a CPU (processor) for executing the program. It has a communication I / F that communicates via the network 2. The user terminal 6 is a mobile terminal such as a smartphone held by the user, and the administrator terminal 7 is a PC (personal computer) or a mobile terminal. Both the user terminal 6 and the administrator terminal 7 input, as hardware, a storage unit for storing a program and various data, a CPU for executing the program, and a communication I / F for communicating with the network 2. It has a unit and a display unit. Note that FIG. 1 illustrates only the display unit 61 of the user terminal 6 and the input unit / display unit 71 of the administrator terminal 7 for convenience of explanation.

The analysis computer 1 has a storage unit 11, a CPU 12, and a communication I / F 13, and analyzes human behavior. The storage unit 11 stores the behavior analysis program 100 and the database (DB) 110. The DB 110 includes a store information DB 400, an action history DB 600, a movement summary DB 700, a location information DB 900, a map information DB 920, and a movement diversity DB 800. A configuration example of each DB will be described later. (In the following description, the reference numeral attached to each DB may refer to the DB or the information of the DB. For example, the action history information 600, the position information 900, etc. may be referred to.)
The behavior analysis program 100 has the functions of the behavior history creation unit 101, the movement route estimation unit 102, the movement purpose estimation unit 104, and the movement diversity calculation unit 105. When this program 100 is executed by the CPU 12, each function is performed. Is realized. The behavior analysis program 100 does not need to include the above four functions at the same time, and may be a collection of programs for each function.

The recommendation computer 3 is an information processing device that generates guidance information for each user and provides it to the user terminal 6 by using the analysis result for each user by the analysis computer 1. The computer 3 stores the recommendation program 30 having the functions of the recommendation control unit 31 and the recommendation condition setting unit 32 in the storage unit. When the recommendation program 30 is executed by the CPU, these functions are realized, and guidance information is generated and provided.

The user information management computer 4 is an information processing device that acquires and manages user purchase information and store reservation information at a store. The user information management computer 4 can collect purchase information and reservation information recorded in a store by payment using an electronic medium such as a transportation IC card or a mobile terminal possessed by the user, for example. The user information management computer 4 is an information processing device that has a user information DB 500 and a reservation / payment record DB 300 in a storage unit and manages user information. By executing the program on the CPU, it manages recording and reading of information in each DB.

The movement record management computer 5 is an information processing device that collects and manages entry / exit information when a user enters / exits a ticket gate of a station using a transportation IC card or the like. The movement record management computer 5 stores the ticket gate entry / exit history DB 210 and the entry / exit record management program 230 acquired from the ticket gates installed at the station in the storage unit. By executing the entry / exit record management program 22 on the CPU, the ticket gate entry / exit history information (which may be called boarding / alighting information) is collected and the user's movement record information is managed.

Next, each functional part of the analysis computer 1 will be described.
The behavior history creation unit 101 of the behavior analysis program 100 acquires the user information 500 and the reservation / settlement record information 300 from the user information management computer 4 via the communication I / F 13, and further, the movement record management computer 5. Obtain the ticket gate entry / exit history 210 from. Then, the action history creating unit 101 creates the action history 600 by arranging the acquired user information 500, the reservation / settlement record 300, and the ticket gate entry / exit history 210 in chronological order for each user.

The movement route estimation unit 102 maps the position information included in the action history 600 of each user to the map information 920, and identifies the route that each user has taken. As a process for specifying a route, a method generally called map matching can be used.

The movement purpose estimation unit 104 estimates the purpose of the user's movement from the ticket gate entry / exit history 210 and the reservation / settlement record 300, and records it in the action history 600. For example, in the movement history of a certain user, when a record of using an entertainment facility such as a movie is obtained after arriving at the destination, the purpose of the movement is recorded as entertainment. If a regular movement pattern is obtained, such as arriving at the destination at 9 am and returning home on the same route at 5 pm, it is recorded as commuting to work or school.

The movement diversity calculation unit 105 estimated the purpose, destination, and route of the movement that occurred within an arbitrary period based on the target person's ticket gate entry / exit history 210 and reservation / settlement record 300, and visited the site. Calculate the diversity index of the destination used by the target person from the destination, calculate the diversity index of the route used by the target person from the route used, and calculate the diversity index related to the time the user travels from the travel time. And record in the mobile diversity DB900. Here, the movement diversity represents a large number of destinations, movement times, and movement route choices, and the index means an evaluation value such as a numerical value indicating the large number.

Next, a configuration example of each DB (or DB information) will be described with reference to FIGS. 2 to 8.

FIG. 2 shows an example of the ticket gate entry / exit history DB 210. The ticket gate entry / exit history DB 210 records information when a user enters / exits a station ticket gate using a transportation IC card or the like. The ticket gate entry / exit history DB 210 is, for example, a user ID 211 that identifies a user, a ticket gate ID 212 that identifies a ticket gate, an entry / exit category 213 that distinguishes entry or exit, a station ID 214 that identifies a station, and the date and time of entry or exit of the ticket gate. It is composed of the date and time 215 indicating.

FIG. 3 shows an example of the reservation / settlement record DB 300. The reservation / settlement record is composed of the settlement record DB 310 and the reservation record 320. The payment record is the information collected by the user information management computer 4 as a record in the store when the payment is made using an electronic medium such as a mobile terminal owned by the user. The reservation record is the information collected by the user information management computer 4 as a record in the store when the user makes a reservation using a mobile terminal or the like possessed by the user.

The payment record DB 310 shown in FIG. 3A is composed of a user ID 311, a purchased item 312, a purchase amount 313, a store ID 314 which is a store identifier, and a usage date / time 315.

The reservation record 320 shown in FIG. 3B is composed of a user ID 321, a store ID 322 which is an identifier of the store that reserved the service, a service type 323 used, a use start time 324, and a use end time 325. To.

FIG. 4 shows an example of the store information 400.
The store information DB 400 includes a store ID 421 that is a store identifier, a store name 422, a latitude 423 and a longitude 424 that indicate the location of the store, a category 425 that identifies products and services handled by the store, and a station where the store is located. It is composed of the station ID 426 to be identified and the service information 427 of the store. The service information 427 of a store means coupons, service tickets, and discount information specially provided by the store. The service information 427 is updated one after another and the latest information is managed.

FIG. 5 shows an example of the user information DB 500.
The user information DB 500 is composed of a user basic information DB 510 and a user ID management information DB 520.

The user basic information DB 510 shown in FIG. 5A manages the personal information of the user, and corresponds to the common ID 511 that uniquely identifies the user, and has a name 512, a gender 513, and a date of birth. Register the day 514 and the address 515. The common ID 511 and 521 associate the user basic information DB 510 and the user ID management information DB 520.

The user ID management information DB 520 shown in FIG. 5B manages a plurality of user IDs used by the same user as one, and corresponds to a plurality of individual user IDs 521. Register user IDs 522 to 525. The individual user IDs 522 to 525 include, for example, a plurality of different transportation ID cards, credit cards, and terminal numbers 525 such as mobile numbers. The user uses public transportation using the user ID of the transportation IC card, credit card, mobile terminal, etc. registered in the user ID management information 520, and purchases products and receives services at the store. At that time, these individual IDs 522 to 525 are recorded in the ticket gate entry / exit history and the reservation / settlement record.

FIG. 6 shows an example of the action history DB 600.
The action history DB 600 includes an action history DB 610 (FIG. 6 (a)) and a route 620 ((FIG. 6 (b)). The route DB 620 manages route information referred to from the action history 600. , The route DB 620 is not necessarily included in the action history DB 600, and may be another independent DB.
The action history DB 610 shown in FIG. 6A is created for each user ID based on the ticket gate entry / exit history 210 and the reservation / settlement record 300. The action history DB 600 includes a date and time 611 when an action such as movement or purchase is detected, a station ID 612, a store ID or ticket gate ID 613, an action type 614 indicating a distinction between movement, purchase, and service use, and purchase or service use is performed. It is composed of position information 615 indicating the location, trip ID 616 indicating a series of collective actions, route ID 617 used for the movement, and purpose 618 of the movement. The user's action history 611 to 618 is recorded in chronological order for each user ID.

Here, the action type 614 is from the ticket gate entry / exit category 213 when it is created from the movement history 210, from the purchased item 312 when it is created from the settlement record 310, and the usage service type 323 when it is created from the reservation record 320. Apply the values from. In other cases, there is no value. The position information 615 is the value of the latitude 223 and the longitude 224 of the position information 900. Alternatively, when creating an action history entry from the reservation / payment record 300, the store used is specified from the store ID 322 of the payment record 310 or the reservation record 320 and the store information 400, and the latitude 423 and the longitude 424 thereof are specified. Is acquired and recorded as position information 615. In other cases, there is no value.

The route DB 620 shown in FIG. 6B is from route ID 621, route ID 622, flight ID 623, departure station ID 624, departure time 625, arrival station ID 626, arrival time 627, and standard transfer time 628. It is composed. Route 620 corresponds to information provided by a general transfer guidance service (service information presented by public transportation). The movement route estimation unit 102 in this embodiment specifies a departure point and an arrival point, a waypoint, and an estimated use route, acquires route information from the transfer guidance service, and uses the route for movement by the target person. To get.

FIG. 7 shows an example of the mobile summary DB 700.
The movement summary 700 is information obtained by extracting the history related to the movement from the action history 600 for each purpose and destination of the movement. The movement summary DB 700 is composed of a common ID 711 for registering a user ID, a movement purpose 712, a departure place 713, a destination 714, and a route list 715.
In the movement summary 700, the movement diversity calculation unit 105 searches the behavior history for each user, for example, for 3 months, and calculates (totals) the number of departure points and destinations (number of destinations) for each purpose. demand.

FIG. 8 shows an example of the mobile diversity DB 800. The mobile diversity DB 800 includes a mobile diversity DB 810 and a purpose-specific mobile diversity DB 820.
The movement diversity DB 810 shown in FIG. 8A is composed of a common ID 811 for registering a user ID, a destination diversity 812, a route diversity 813, an arrival time diversity 814, and a travel time diversity 815. .. Destination diversity 812 is an indicator of the large number of daily destination choices. The route diversity 813 is an index showing the number of choices of routes to the same destination. The arrival time diversity 814 is an index showing the number of choices of time to arrive at the same destination. Travel time diversity 815 is an index showing the number of travel time options for going to the same destination. In the illustrated example, a destination diversity 812 "4" indicates that there are four destinations on a daily basis. A route diversity 813 "2" indicates that two routes are used to reach the same destination. The arrival time variety 814 indicates that "30" has a time variation of ± 30 minutes to reach the same destination. Travel time diversity 815 "15" also indicates that there is a time variation of ± 15 minutes.

The purpose-specific movement diversity 820 shown in FIG. 8B is composed of a common ID 821, a purpose 822, a destination diversity 823, a route diversity 824, an arrival time diversity 825, and a travel time diversity 826. Will be done. The purpose 822 is the same as the moving purpose 712 of the moving summary 700.
For example, even if you go to the same destination, you usually use the conventional line when you go for work, and use the Shinkansen when you hurry, but when you go for entertainment, you only use the conventional line. Diversity is thought to change depending on the purpose. Therefore, instead of the movement diversity 810, the movement diversity 820 for each purpose may be used.

FIG. 9 shows an example of the position information DB 900.
The location information 900 is location information acquired by the Wi-Fi connection of the mobile terminal possessed by the user or the application possessed by the mobile terminal. The location information DB 900 is composed of, for example, a user ID 221, a Wi-Fi station ID 222, a latitude 223 indicating the position of the Wi-Fi station, a longitude 224, and a date and time 225 when a connection is detected to the Wi-Fi station. When acquired by an application possessed by a mobile terminal, it is location information acquired by GPS.

Although the map information DB 920 is not shown, it is well-known map information that can be viewed on a mobile terminal such as a smartphone.

Next, the behavior analysis processing operation will be described with reference to FIG.
This processing is related to the processing by the behavior history creation unit 101, the movement route creation unit 102, and the movement purpose estimation unit 104 of the behavior analysis program 100.
When the behavior analysis program 100 is executed by the CPU 12, the behavior history creation unit 101 periodically (for example, once a week or once a month) from the user information management computer 4, user information 500. , And the reservation / settlement record 300 is acquired, and the ticket gate entry / exit history 210 is further acquired from the movement record management computer 5 (S1001).

Then, the action history creating unit 101 sorts the acquired user information 500, the reservation / settlement record 300, and the ticket gate entry / exit history 210 in chronological order for each user, and creates the action history 610 (S1002). Here, the action history creation unit 101 determines the elapsed time from entry to entry and the standard time required for transfer when the entry record of a different station or the same station continues after the entry record of any station. Compare. As a result, if the elapsed time is longer than the standard time required for transfer, the station where the entry record occurred is specified as the destination, and the entry record is defined as one trip to create a trip ID. (S1003).

Next, the movement route estimation unit 102 maps the position information 615 included in the action history 610 for each user to the map information 920, and estimates the route used by each user. As a process for estimating the route used, a method generally called map matching can be used to collate the position information 900 with the position of the route on the map and estimate which route was used. Then, the departure point (entrance station) and the destination (entrance station) specified in S1003 and the estimated route are specified, and the movement route is acquired from the transfer guidance service (S1004).

Next, the movement purpose estimation unit 104 estimates the purpose of the movement of the target person from the reservation / settlement record 300, and records it in the purpose 618 of the action history 610. For example, at the trip destination defined in S1003, it is confirmed whether there is a purchased item or a service type used after arriving at the destination with reference to the reservation / settlement record 300 (S1005), and as a result, the reservation / payment is made. When the payment record (for example, reservation of entertainment facility such as a movie or payment record) is obtained, the purpose of the trip is estimated from the category of the obtained reservation / payment record. As described above, the trip ID, the travel route, and the purpose created, acquired, and estimated are recorded in the trip 616, the route 617, and the purpose 618 corresponding to the date and time 611 to the position information 615 of the action history 610 (. S1006).

On the other hand, as a result of the above confirmation, if there is no reservation / settlement record at the destination, it is checked whether or not there is a trip with the same arrival time or the same departure time for the same destination as the trip. Here, the same arrival time zone and the same departure time zone are time zones defined in the range of one hour to several hours. For example, if you get a regular pattern of travel, such as arriving at your destination from 9am to 10am and following the reverse route between 5pm and 8pm and back to your starting point, then the trip It is estimated that the purpose 618 is commuting to work or school, and it is recorded in the action history 610 (S1007).

Next, the movement diversity calculation processing operation will be described with reference to FIG.
The movement diversity calculation process is a process in which the movement diversity calculation unit 105 searches the action history 600 and creates the movement diversity 810 for each user and the movement diversity 820 for each purpose.
The movement diversity calculation unit 105 periodically calculates the number of destinations (number of destinations) for each purpose for the behavior history of the user for three months, and creates the movement summary 700. Therefore, the movement diversity calculation unit 105 refers to the movement summary 700, obtains the number of destinations for each purpose for each user, and uses the number as an index to correspond to the purpose 822 of the movement diversity 820 for each purpose. Record in the destination diversity 823 (S1101). Next, for each destination obtained in S1101, the number of routes used to reach each destination is obtained, and the number is used as an index to obtain the movement diversity 824 corresponding to the purpose 822 of the purpose-specific movement diversity 820. (S1102).

Subsequently, the movement diversity calculation unit 105 obtains the travel time standard deviation and the arrival time standard deviation for each purpose and destination for the user with reference to the behavior history 610, and obtains these indexes, respectively. Record in the purpose-specific movement diversity 820 (S1103, S1104). Here, the arrival time standard deviation is the standard deviation of the value obtained by converting the time (minutes) arriving at the same purpose and the same destination into the cumulative number of minutes from midnight. For example, if the standard deviation value is 30 minutes, the subject has arrived at the destination with a variation of about ± 30 minutes, and the arrival time of about 30 minutes is advanced or backward within the permissible range. It is presumed that there is. However, if this variation is several hundred minutes, it is assumed that the scheduled time of the activity to be moved will be different, so it will not be used as a variety of arrival times.

Further, the travel time standard deviation is a standard deviation of a value obtained by converting the travel time required for traveling to the same purpose and the same destination within an arbitrary period into a cumulative fraction. If this value is 15 minutes, it is presumed that the subject has moved to the destination with a variation of about ± 15 minutes, and that the extension of the travel time of about 15 minutes and the stop-by are within the permissible range. To travel. In particular, if the standard deviation of the travel time is more than a certain time, it is highly likely that the service of station Naka is used frequently, and it is not possible to send information on the service of station Naka based on the index. Considered appropriate.

As described above, after obtaining the destination diversity for each purpose, the route diversity for each destination, the standard deviation of the travel time for each purpose / destination, and the standard deviation of the arrival time for each purpose / destination, the movement is not due to the purpose. The index of diversity 810 is calculated (S1105). This calculation is an index of destination diversity 812 that does not depend on the purpose by obtaining the total value or the average value (value divided by the total value of all the destinations that can use the above total value) of the total number of destinations of all purposes. And. In addition, the index of route diversity 813 regardless of the purpose / destination is obtained by obtaining the total value or the average value (value divided by the total value of all the routes that can use the above total value) of the route diversity of all destinations. And. In addition, the standard deviation of the value obtained by converting the arrival time arriving at the same destination within an arbitrary period into a cumulative fraction is used as an index of the arrival time diversity 814. In addition, the standard deviation of the value obtained by converting the travel time required to move to the same destination within an arbitrary period into a cumulative fraction is used as an index of the travel time diversity 815.

When deciding to send a recommendation, the movement diversity 810 that does not depend on the purpose / destination, which is obtained as described above, may be used, or if the number of data is sufficient, the movement diversity 820 for each purpose is used. May be good. For example, even if you go to the same destination, you usually use the conventional line when you go for work, and use the Shinkansen when you hurry, but when you go for entertainment, you only use the conventional line. It is thought that diversity will change depending on the purpose. In such a case, it is considered more appropriate to use the movement diversity 820 for each purpose instead of the movement diversity 810 that does not depend on the purpose / destination.

Next, with reference to FIG. 12, the processing operation by the recommendation control unit 31 of the recommendation computer 3 will be described. As one of the recommendation processing, for example, the recommendation is carried out to alleviate the congestion of public transportation.

The recommendation control unit 31 receives the card ID of the transportation IC card of the user who entered from the ticket gate of a certain station from the movement record management computer 5 (S1201).

Next, the recommendation control unit 31 estimates the destination and route of the user who holds the transportation IC card of the card ID (S1202).
First, the destination is estimated. That is, the recommendation control unit 31 refers to the reservation / payment information 300, and if there is a reservation / payment record of the service scheduled to be received within a certain time from the current time, the recommendation control unit 31 acquires the location of the service providing facility from the map information 920. , Estimate the nearest station of the provided facility as the destination to be disembarked. Here, if there is no reservation / payment record for the corresponding service, the destination station and its destination by a method such as Bayesian estimation based on the trip history included in the action history 610 and the station where the ticket gate has entered. The probability of getting off at a station is calculated, and the station with the highest probability of getting off is estimated as the destination.

Next, the route is estimated. The recommendation control unit 31 acquires the route between the station where the ticket gate has entered and the station estimated as the destination by using the transfer guidance service. If there are multiple routes, select the shortest route, or if there is location information 615 recorded between the entrance and exit of the ticket gate, compare the location information 615 with the map information 920, and the location information 615 is the most. Select a close route.

Then, the recommendation control unit 31 acquires the congestion information of the route estimated to be used by the target person from the congestion information distribution service, and determines whether or not congestion avoidance is necessary (S1203). That is, if the congestion rate is above a certain level, it is determined that a congestion avoidance request is necessary. On the other hand, if the congestion rate is smaller than a certain value, it is determined that the congestion avoidance request is unnecessary (S1203: N), and the process is terminated. Congestion information is acquired by using a congestion information distribution service provided by public transportation such as a railway company.

Next, the recommendation control unit 31 acquires the recommendation sending condition defined by the administrator in the recommendation condition setting unit 32, and if the user satisfies the recommendation sending condition, selects the recommendation target person (S1204). The setting of the recommendation from the administrator terminal 7 to the recommendation condition setting unit 32 will be described later with reference to FIG.

The recommendation control unit 31 transmits to the user terminal 6 the guidance information for avoiding congestion associated with the conditions to the selected recommendation target person according to the conditions of the recommendation condition setting unit 32 (. S1205). For example, as an example for avoiding congestion, the recommendation sending condition is a route that does not use a route that is expected to be congested for a target person whose purpose of travel is entertainment and whose destination diversity index is above a certain value. And destination information shall be provided. Further, the user terminal is specified based on the user ID management information 520.

FIG. 13 shows an example of a recommendation screen displayed on the display unit 61 of the user terminal 6.
As a result of the congestion avoidance process (S1205), the recommendation screen 62 includes the display of the congestion avoidance recommendation guidance information 622 in addition to the usual shortest route guidance information 621 for the user.
For example, the guidance information 622 of the congestion avoidance recommendation presents the congestion status of the line and the service information of the cafe that can be stopped by, thereby urging the user to stop by the cafe at the station and avoid the peak of congestion. Such recommendations will contribute to attracting customers to commercial facilities around the station and in the station Naka, and to alleviate train congestion. As for the service information, the service information 427 can be acquired by referring to the store information 400 of the store on the congestion avoidance route.

FIG. 14 shows an example of a screen 72 in which the recommendation sending condition is specified by the input unit / display unit 71 of the administrator terminal 7 for the recommendation condition setting unit 32 of the recommendation computer 3. The recommendation sending condition specification screen 72 displays the lower limit of destination diversity, the lower limit of route diversity, the lower limit of arrival time diversity, the lower limit of travel time diversity, and the purpose as conditions for the user to send the recommendation. Has an input item to input. The administrator inputs conditions from the input unit for the items of the screen 72 displayed on the display unit 71 of the administrator terminal 7. Then, the recommendation condition setting unit 32 of the recommendation computer 3 sets the above-mentioned diversity and purpose for the conditions of the input items. The recommendation control unit 31 sends a recommendation to a user who satisfies all the conditions of the above-mentioned items set in the recommendation processing operation (FIG. 12). If the purpose is specified by the administrator, the condition is determined by the purpose-specific movement diversity 820. On the other hand, when the purpose is not specified, the condition is determined by the movement diversity 810.

As described above, according to this embodiment, it is possible to quantify the diversity of the movement behavior of the target person by utilizing the entry / exit history of the ticket gate and the reservation / settlement record, and to select the target person who is likely to accept the recommendation. can. As a result, you can select a target person with high route diversity from users of any route and send a route change recommendation, or send a destination change recommendation to a person with high destination diversity for entertainment purposes. Time change recommendations can be sent to people with high time diversity on the move for entertainment purposes. On the other hand, it becomes possible to control not to send the travel time change recommendation to a person who does not have diversity of travel, for example, a person who has inflexible time such as bank counter work.

Although one embodiment of the present invention has been described above, the present invention is not limited to the above embodiment and can be implemented in various modifications.
For example, the configuration of each database in the above embodiment is an example, and some data may not be registered, or other related data may be added and registered.

Further, in the guidance information providing system of the above embodiment, the functions of the recommendation computer 3, the user information management computer 4, and the movement record management computer 5 are configured by being separated from the analysis computer 1, respectively. According to this, a part or all of the functions of these computers 3, 4, and 5 may be configured to be provided in the analysis computer 1. For example, the analysis computer 1 may have some data selected from the reservation / settlement record 300 and the ticket gate entry / exit history 210.

The present invention can also be grasped as a behavior analysis program executed by the behavior analysis device and a guidance information providing program executed by the guidance information providing system.

1: Analytical calculator 2: Network 100: Behavior analysis program 3: Recommendation computer
4: User information management computer 5: Movement record management computer 6: User terminal 7: Administrator terminal 11: Storage unit 12: CPU 13: Communication I / F 101: Action history creation unit 102: Movement route estimation unit 103: Transportation means estimation unit 104: Movement purpose estimation unit 105: Movement diversity calculation unit 110: Database
210: Ticket gate entry / exit history 230: Entrance / exit record management program 300: Reservation / payment record 400: Store information 500: User information 600: Behavior history 700: Movement summary 800: Movement diversity 900: Location information 920: Map information 30 : Recommendation program 31: Recommendation control unit, 32: Recommendation condition setting unit

Claims (10)

It is a behavior analysis device that analyzes information on the movement of people using public transportation using a computer that has a processing unit and a storage unit.
User behavior history using public transportation boarding / alighting information of users who get on and off using electronic media, and payment information or reservation information for each user handled when purchasing products or providing services at stores. With the action history creation department to create
Based on the behavior history, a route estimation unit that estimates the destination and route to which the user goes, and a route estimation unit.
A purpose estimation unit that estimates the purpose of the user's movement based on the behavior history,
A diversity calculation unit that calculates the destination diversity, route diversity, or travel diversity for each purpose of the user based on the estimated destination, route, or purpose.
Behavioral analytics device with. The diversity calculation unit calculates an index indicating the number of choices for the destination diversity, the route diversity, or the movement diversity for each purpose.
The behavior analysis device according to claim 1, wherein the storage unit has a movement diversity database that stores the calculated index of the destination diversity, the index of the route diversity, or the index of the movement diversity for each purpose. .. The action history is, for each user, the station of the public transportation system where the user got on and off, the store, the product purchased at the store or the service provided, the route estimated by the route estimation unit, and the purpose. Includes data about the purpose estimated by the estimation unit
The behavior analysis device according to claim 1, wherein the storage unit has a behavior history database for storing the behavior history. The behavior analysis device according to claim 1, wherein the diversity calculation unit uses the total value of destinations visited for the same purpose within an arbitrary period as a destination diversity index. The diversity calculation unit is the total value of the number of routes used to move to the same purpose and the same destination within an arbitrary period, or the total value of all the routes that can use the total value. The behavioral analyzer according to claim 1, wherein the divided value is used as a route diversity index. The diversity calculation unit claims that the standard deviation of the value obtained by converting the time of arrival at the same purpose and the same destination into the cumulative fraction from midnight within an arbitrary period is used as the arrival time diversity index. Behavior analysis device of 1. The diversity calculation unit claims that the standard deviation of the value obtained by converting the travel time required for traveling to the same purpose and the same destination within an arbitrary period into cumulative minutes is used as the travel time diversity index. Behavior analyzer. It is a guidance information providing system that provides guidance information to users who use public transportation using electronic media.
(1) The first computer that analyzes information about the movement of users,
(2) It has a second computer that provides guidance information to the mobile terminal owned by the user according to the analysis by the first computer.
(1) The first computer is
User behavior history using public transportation boarding / alighting information of users who get on and off using electronic media, and payment information or reservation information for each user handled when purchasing products or providing services at stores. With the action history creation department to create
Based on the behavior history, a route estimation unit that estimates the destination and route to which the user goes, and a route estimation unit.
A purpose estimation unit that estimates the purpose of the user's movement based on the behavior history,
It has a destination diversity, a route diversity, or a diversity calculation unit for calculating a travel diversity for each purpose based on the estimated destination, the route, or the purpose. ,
(2) The second computer is
A recommendation condition setting unit that presets the conditions for recommendations that provide guidance information to users, and a recommendation condition setting unit.
Using the information on getting on and off the public transportation of the user who gets on and off using electronic media, and the payment information or reservation information for each user handled when purchasing goods or providing services at the store, the user's destination and Estimate the route,
Among the estimated users in the route, the destination diversity, route diversity, or movement diversity for each purpose of the user calculated by the diversity calculation unit of the first computer is determined. A guidance information providing system characterized in that a target person who satisfies the conditions set in the recommendation condition setting unit is selected and guidance information is sent to the target person. The second computer has a terminal connected via the network 2.
The terminal is a condition set in the recommendation condition setting unit.
The guidance information according to claim 8, further comprising a display unit for displaying a screen including an item for inputting the destination diversity, the route diversity, or the purpose, and an input unit for inputting a condition in the item on the screen. Offering system. It is a guidance information providing method that provides guidance information to users who use public transportation using electronic media.
It has a first computer that analyzes information related to the movement of the user, and a second computer that provides guidance information to the mobile terminal owned by the user according to the analysis by the first computer.
(1) The first computer is
User behavior history using public transportation boarding / alighting information of users who get on and off using electronic media, and payment information or reservation information for each user handled when purchasing products or providing services at stores. And the action history creation step to create
A route estimation step for estimating the destination and route to which the user goes based on the behavior history, and
A purpose estimation step for estimating the purpose of the user's movement based on the behavior history, and
It has a diversity calculation step for calculating the destination diversity, the route diversity, or the movement diversity for each purpose of the user based on the estimated destination, the route, or the purpose. ,
(2) The second computer is
The recommendation condition setting step for presetting the recommendation conditions for providing guidance information to the user, and the recommendation condition setting step.
Using the information on getting on and off the public transportation of the user who gets on and off using electronic media, and the payment information or reservation information for each user handled when purchasing goods or providing services at the store, the user's destination and Estimate the route,
Among the estimated users in the route, the destination diversity, route diversity, or movement diversity for each purpose of the user calculated by the diversity calculation step of the first computer is determined. A method for providing guidance information, which comprises selecting a target person who satisfies the conditions set in the recommendation condition setting step and sending guidance information to the target person.

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