JP7634431B2 - Guidance information providing device, guidance information providing system, and guidance information providing method - Google Patents

Description

The present invention relates to a guidance information providing device, a guidance information providing system, and a guidance information providing method.

In urban development, control of citizens' travel demand is being considered to revitalize cities. The background to this is that facilities and transportation that tend to be easily congested place a heavy burden on securing resources to meet peak demand, while facilities and transportation with few users are experiencing various problems due to low sales efficiency.

To enable efficient and sustainable management of facilities and transportation throughout the city, it is necessary to reduce excessive bias in the travel demand of citizens. In doing so, it is important to appropriately control the travel demand of citizens, taking into account the management resources and urban development policies of the operators of the facilities and transportation.

An urban development policy here could be, for example, a congestion adjustment policy that would reduce the number of passengers on trains on specific lines or sections during specific times of day when congestion needs to be alleviated. This is a policy for managing the travel demand of citizens, which not only aims to alleviate congestion and attract customers to individual transportation facilities and facilities, but also includes guiding people to travel along desirable travel routes and at desirable times throughout the city as a whole.

By the way, geotargeting technology is used as a method of controlling travel demand by using data to encourage citizens to visit stores. As a conventional technology related to this concept, for example, a location-linked coupon distribution system (see Patent Document 1) has been proposed that encourages store visits by exciting consumers, while providing coupons for products that consumers are interested in at times when they are most motivated to purchase.

This location-linked coupon distribution system includes an input unit for inputting the consumer attributes of the user, a coupon registration unit for allowing manufacturers of products sold in the store to register coupon information related to the products, a store visit determination unit for determining whether the user has visited the store, a product selection unit for selecting multiple products as candidates for coupon distribution from among products sold in the store that are presumed to be of interest to the user based on the consumer attributes of the user, and a distribution unit for distributing to a mobile terminal a coupon related to a product randomly selected from the multiple products selected at the time the user visited the store.

A store support system (see Patent Document 2) has also been proposed that aims to increase the number of users visiting a store by providing sales information suited to specific future time periods.

This store support system includes a time zone setting unit that sets a time zone, a user extraction unit that extracts users who are likely to visit a store during the time zone set by the time zone setting unit, and a provision unit that provides sales information, including benefits that are granted on the condition that the user uses the store, to a terminal device used by the user extracted by the user extraction unit.

Also, an advertising system that enables events such as stamp rallies to be held has been proposed (see Patent Document 3). This advertising system is an advertising method carried out in an advertising system equipped with an advertising management server that manages events in which users of mobile terminals are participants, in which the advertising management server determines whether the access is valid or invalid when the advertising management server is accessed by a mobile terminal based on an information code, the information code being included in an advertisement (hereinafter referred to as an event advertisement) that is displayed together with a notice indicating that the event is the subject of the event at a plurality of predetermined locations, the information code including a location code assigned to the display location of each event advertisement, an advertising code, and URL information of the advertising management server, the advertising management server registers the location code and the corresponding information of the display location of the event advertisement, advertising information including the advertising code and the corresponding advertising information that is information of an advertisement displayed on the mobile terminal, the event holding period, the event benefits, and benefit granting rules, and when the advertising management server determines that the access is valid, it associates the access with the display location of the event advertisement for each mobile terminal and registers the access as a recipient of a benefit, determines a benefit for the access registered as a recipient of a benefit for each mobile terminal based on the benefit granting rules, transmits information of the determined benefit to the mobile terminal, and counts and outputs the number of accesses to the advertising management server during the event holding period for each display location of the event advertisement.

JP 2019-102053 A JP 2018-101270 A JP 2019-114289 A

The system disclosed in Patent Document 1, which is one of the conventional technologies, does not assume cooperation between stores, and is therefore unable to guide consumer movement behavior. In addition, when such a system is used, it is anticipated that customers will be concentrated in certain facilities, etc., and there is a concern that unintended congestion will occur. Furthermore, since it is not possible to control the use of public transportation when visiting a store, there is a possibility that congested public transportation will be used.

The system disclosed in Patent Document 2 also does not assume cooperation between stores, and is therefore unable to induce consumer shopping behavior. In addition, this system determines the timing of limited-time sales and the products that are the target of each store, so there is a concern that if multiple stores hold sales simultaneously, they may compete for profits. Furthermore, even if information about limited-time sales is provided in advance to consumers who are not in the vicinity of a store and who do not have a strong purchasing motivation, it may not lead to purchasing behavior. Also, like Patent Document 1 mentioned above, the use of public transportation is not taken into consideration.

In addition, because the optimal route depends heavily on real-time data such as congestion conditions that are difficult to predict and changes in transportation schedules, the checkpoints or stores that define the optimal route should change each time in response to real-time data. However, the system disclosed in Patent Document 3 cannot take real-time data into account, and there is a concern that a route different from the optimal route may be selected.

In addition, consumers will move along a route that has been planned and prepared in advance by the time stamp provider, after knowing that route in advance. Naturally, consumers are constantly thinking while they are moving, and their thoughts at any given time have a significant impact on their purchasing motivations and consumption behavior. The advertising system of Patent Document 3 cannot take into account the thoughts of consumers while they are moving, which further increases the concern that a different route from the optimal one will be selected.

The object of the present invention is to provide technology that makes it possible to provide guidance information that matches the behavioral patterns and service preferences of users, taking into account the travel demand control policies of transportation operators, developers, local governments, etc.

The guidance information providing device of the present invention that solves the above-mentioned problems is characterized by having a memory unit that retains at least each piece of information: a congestion adjustment policy that specifies a service that is subject to congestion adjustment at a business operator and a desired number of customers; a behavior pattern that specifies the occurrence probability of each behavior performed before and after a specific behavior in a series of behaviors that are highly likely to be performed consecutively by a user of the service provided by the business operator; and a provision status of the service that indicates characteristics of each of the services; and a calculation unit that executes a process of identifying a user who is expected to use a service that is subject to congestion adjustment specified in the congestion adjustment policy, based on usage reservation information for the service obtained from a terminal of the corresponding business operator, a process of referring to the behavior pattern for the user and identifying an behavior that has a high occurrence probability between before and after use of the service that is subject to congestion adjustment in the series of behaviors indicated by the behavior pattern, a process of identifying other services that have characteristics that are identical or similar to the characteristics of the service used in the identified behavior, based on information on the provision status, and a process of searching for detour route candidates for avoiding use of the service that is subject to congestion adjustment and encouraging use of the other service, and generating guidance information that includes information on the detour route candidates .

The guidance information providing system of the present invention is characterized in that it includes a guidance information providing device having: a memory unit that holds at least each piece of information: a congestion adjustment policy that defines a service that is subject to congestion adjustment at a business operator and a desirable number of customers; a behavior pattern that defines the occurrence probability of each behavior performed before and after a specific behavior in a series of behaviors that are likely to be performed consecutively by a user of the service provided by the business operator; and a provision status of the service that indicates characteristics of each of the services; and a calculation unit that executes a process of identifying a user who is expected to use a service that is subject to congestion adjustment defined in the congestion adjustment policy, based on usage reservation information for the service obtained from a terminal of the corresponding business operator, a process of referring to the behavior pattern for the user and identifying an behavior that is highly likely to occur before or after use of the service that is subject to congestion adjustment in the series of behaviors indicated by the behavior pattern, a process of identifying another service that has characteristics that are identical or similar to the characteristics of the service used in the identified behavior, based on information on the provision status, and a process of searching for detour route candidates for avoiding use of the service that is subject to congestion adjustment and encouraging use of the other service, and generating guidance information including information on the detour route candidates .

Furthermore, the guidance information providing method of the present invention is characterized in that an information processing device includes a memory unit that retains at least each piece of information: a congestion adjustment policy that specifies a service that is subject to congestion adjustment at a business operator and a desired number of customers; a behavior pattern that specifies the occurrence probability of each behavior performed before and after a specific behavior in a series of behaviors that are likely to be performed consecutively by a user of the service provided by the business operator; and a provision status of the service that indicates characteristics of each of the services, and executes a process of identifying a user who is expected to use a service that is subject to congestion adjustment specified in the congestion adjustment policy, based on usage reservation information for the service obtained from a terminal of the corresponding business operator; a process of referring to the behavior pattern for the user and identifying an behavior that is highly likely to occur before or after use of the service that is subject to congestion adjustment in the series of behaviors indicated by the behavior pattern; a process of identifying other services that have characteristics that are identical or similar to the characteristics of the service used in the identified behavior, based on information on the provision status; and a process of searching for detour route candidates for avoiding use of the service that is subject to congestion adjustment and encouraging use of the other service, and generating guidance information that includes information on the detour route candidates .

According to the present invention, it is possible to provide guidance information that matches the behavioral patterns and service preferences of users, taking into account the travel demand control policies of transportation operators, developers, local governments, etc.

1 is a diagram showing an overall configuration of a guide information providing system according to an embodiment of the present invention; FIG. 2 is a diagram illustrating an example of a customer number adjustment standard DB in the present embodiment. FIG. 2 is a diagram illustrating an example of a user behavior information DB in the present embodiment. FIG. 2 is a diagram illustrating an example of a behavior pattern DB in the present embodiment. FIG. 2 is a diagram showing an example of an item basic information DB in the present embodiment. FIG. 2 is a diagram showing an example of an item evaluation DB in the present embodiment. FIG. 2 is a diagram illustrating an example of a service evaluation DB in the present embodiment. FIG. 4 is a diagram showing an example of a flow of a guide information providing method according to the present embodiment. FIG. 4 is a diagram showing an example of a flow of a guide information providing method according to the present embodiment. FIG. 4 is a diagram showing an example of a flow of a guide information providing method according to the present embodiment. FIG. 4 is a diagram showing an example of a flow of a guide information providing method according to the present embodiment. FIG. 4 is a diagram showing an example of a screen in the present embodiment.

<System Configuration>
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described in detail below with reference to the accompanying drawings. Fig. 1 is a diagram showing an example of the configuration of a guide information providing system 10 including a guide information providing device 1 according to the present embodiment.

The guidance information providing system 10 analyzes the behavioral history of users and the connections between services, and provides guidance information that induces behavioral changes in line with the operator's customer number adjustment criteria.

The guidance information providing system 10 is, for example, an information processing system configured by connecting a guidance information providing device 1, a user terminal 3, a store terminal 4, a transportation business operator terminal 5, and an SNS information extractor 6 via a network 2.

The guidance information providing device 1 has, as hardware, a memory unit 11 that stores programs and various data, a CPU (Central Processing Unit) that is a calculation unit that executes the programs, and a communication I/F 13 that communicates via the network 2. The same hardware configuration is also provided for the other devices that make up the guidance information providing system 10, that is, the user terminal 3, the store terminal 4, the transportation business operator terminal 5, and the SNS information extractor 6. However, each of the user terminal 3, the store terminal 4, and the transportation business operator terminal 5 further has a display unit.

The user terminal 3 is a mobile terminal such as a smartphone held by the user. The store terminal 4 and the transportation company terminal 5 can be assumed to be a PC (Personal Computer) or a mobile terminal.

The guidance information providing device 1 is an information processing device that performs human behavior analysis, service connection analysis, and guidance information generation. The memory unit 11 of the guidance information providing device 1 stores an analysis program 100 and a database 110.

The database 110 includes a customer number adjustment criteria DB 200, a user behavior information DB 300, a behavior pattern DB 400, a basic item information DB 500, an item evaluation DB 600, and a service evaluation DB 700. Examples of the configuration of these databases will be described later (Note that in the following explanation, the reference numerals attached to each database may refer to the DB or information in that DB. For example, they may be written as customer number adjustment criteria information 200, user behavior information 300, etc.).

The analysis program 100 also implements the functions of a behavior pattern analysis unit 101, a service information analysis unit 102, a user provision selection unit 103, and a guidance information selection unit 104. The above-mentioned functions 101 to 104 are realized by the analysis program 100 being executed by the CPU 12. Note that the analysis program 100 does not need to implement the above six functions simultaneously, and may be a collection of programs for each function.

The user terminal 3 is a communication device owned by the user. The user terminal 3 may be capable of data communication with the store terminal 4 via short-range wireless communication such as a wireless LAN (Local Area Network) or Bluetooth (registered trademark).

The user terminal 3 may have a positioning function that receives signals from a satellite using a satellite positioning system to determine the current location. The user terminal 3 provides the thus acquired location information 810 and purchase history information 820 of products and services purchased by the user using the user terminal 3 to the guidance information providing device 1. The user terminal 3 displays the guidance information distributed from the guidance information providing device 1 on a display means such as a display to allow the user to view it, and provides feedback to the guidance information providing device 1 regarding the guidance information selected by the user, i.e., the guidance information used for adoption and behavioral modification.

The store terminal 4 is a computer used in the store, and appropriately provides various business data, such as reservation information 830, POS data 850, and purchase record information 840, used in the management and operation of the store, to the guidance information providing device 1.

The store terminal 4 may also have a short-range wireless communication module such as a wireless LAN or Bluetooth (registered trademark). In that case, the store terminal 4 may communicate with the user terminal 3 and record the history of store usage by the user who operates the user terminal 3.

The transportation company terminal 5 is a computer used by the transportation company, and provides, for example, ticket gate entry/exit record information 860 and passenger number statistics information 870 from a station management system or the like to the guidance information providing device 1. The passenger number statistics information 870 indicates the average number of passengers on the train, calculated based on observation data from weight sensors on vehicles such as trains. The ticket gate entry/exit record information 860 is data that records information when a user enters or exits a station ticket gate using a transportation IC card or the like.

The SNS information extractor 6 is an information processing device that acquires information published on a social network system (SNS) or information on various services managed by a user terminal 3, i.e., SNS information, and provides this to the guidance information providing device 1.

This SNS information extractor 6 stores in its storage unit an information extraction program 60 having the functions of an information extraction unit 61 and a service reputation DB 880. These functions are realized by the information extraction program 60 being executed by the CPU, and the SNS information described above is extracted and provided to the guidance information providing device 1.

<Functions of the guidance information providing device>
Next, a description will be given of each functional unit of the guide information providing device 1. First, the behavior pattern analysis unit 101 of the analysis program 100 acquires the location information 810 and the purchase history 820 from the user terminal 3 via the communication I/F 13.

The behavior pattern analysis unit 101 also acquires reservation information 830 and POS data 850 from the store terminal 4. The behavior pattern analysis unit 101 also acquires ticket gate entry/exit records 860 from the transportation company terminal 5.

Then, the behavior pattern analysis unit 1010 arranges the location information 810, purchase history 820, reservation information 830, POS data 850, and ticket gate entry/exit record 860 acquired as described above in chronological order for each user to create user behavior information 300 (Figure 3).

The behavior pattern analysis unit 101 also analyzes preceding and dependent behaviors for a certain behavior from the user behavior information 300, evaluates the occurrence probability, and registers it in the behavior pattern DB 400.

The service information analysis unit 102 receives the purchase record 8 from the store terminal 4 via the communication I/F 13.
The service information analysis unit 102 acquires the service reputation 880 from the SNS information extractor 6.

The service information analysis unit 102 registers the information acquired as described above for each item in the item basic information 500 (Figure 5).

Then, the service information analysis unit 102 uses the data in the basic item information 500 to quantify each item, such as the locality and popularity of each item, based on evaluation criteria that it has set, and records the numerical values in the item evaluation DB 600 (Figure 6).

Next, for each product or service, such as an omelet rice, that is generated and configured from the above-mentioned products, the service information analysis unit 102 calculates the average value of the evaluations of that product recorded in the product evaluation DB 600, and records this in the service evaluation 700. When identifying related products for a certain product or service, the service information analysis unit 102 may, for example, obtain information for creating the product or service (e.g., cooking recipe information) from the store terminal 4 and refer to this. This makes it possible to quantify the characteristics of the product back to the characteristics of the related products.

The provided user selection unit 103 also obtains information on the route search performed by the user (e.g., information on the route planned to be used, etc.) from the user terminal 3 via the communication I/F 13, and determines whether the information corresponds to a route to be adjusted that is registered in the passenger number adjustment criteria 200 (Figure 2). Note that in addition to cases where the transportation facility planned to be used is identified based on the information on the route search performed by the user, the user's behavior may also be predicted based on information held in the behavior pattern DB 400, for example.

If the result of the above-mentioned judgment is "applicable," the user selection unit 103 determines that the user is a target user for providing guidance information. The number of users who plan to use one of the routes to be adjusted, to whom guidance information is provided, is the difference between the average value indicated by the passenger number statistics value 870 obtained from the transportation business operator terminal 5 and the minimum or maximum number registered in the passenger number adjustment standard 200.

If the average number of passengers is greater than the maximum number registered in the passenger number adjustment standard 200, a guide will be provided to encourage users to use other lines. This makes it possible to adjust the number of passengers to within the target number range.

Furthermore, if the average number of passengers is smaller than the minimum number registered in the passenger number adjustment standard 200, it is possible to guide people to a route with fewer passengers by providing users of other lines with guidance to encourage them to use that line. The line that a user plans to use may be estimated from reservations for use of the facility. Furthermore, the present invention can be applied not only to adjusting the number of passengers on transportation facilities, but also to adjusting the number of users at facilities. In other words, the present invention can be applied not only to easing congestion on transportation facilities, but also to promoting the use of transportation facilities with fewer passengers, attracting customers to facilities, and adjusting congestion.

The guidance information selection unit 104 also extracts from the behavior pattern DB 400 the behavior with the highest probability of occurrence before and after using the route to be adjusted for the user determined by the provision user selection unit 103 to be a target user, and proposes an alternative facility that can achieve the purpose of that behavior. The alternative facility is selected by referring to the service evaluation DB 700, and a service with characteristics closest to those of the service related to the behavior with the highest probability of occurrence is set as the alternative.

Comparison of service features is performed, for example, in the following manner. First, the guidance information selection unit 104 creates a regular polygonal figure (for example, a regular hexagon if there are six evaluation items) with the evaluation items in the service evaluation DB 700 as its vertices, and creates an axis with the vertices as the maximum evaluation value and the center of the figure as the minimum evaluation value.

Then, the guidance information selection unit 104 plots the evaluation value of each service on the above-mentioned figure, and sets the polygon surrounded by the straight lines connecting the plots as the graph type of that service. The guidance information selection unit 104 evaluates the similarity by matching this graph with the graphs of other services. In addition, the proposed alternative service is of the same service type as the service of the behavior with a high occurrence probability extracted from the behavior pattern DB 400.

The similarity is evaluated, for example, by calculating the Euclidean distance between the vertices of the above-mentioned figures, i.e., polygons, and taking the sum of these distances as the similarity between the charts. However, this method is not limited to this.

This will provide users with guidance that maintains their preferences and behavioral connections, i.e. alternative options, increasing users' acceptance of those alternative options and helping them avoid using the adjusted routes, such as trains and facilities.

Multiple alternatives may be offered to the user in order of the highest matching rate of the service's features. The order of the suggestions may be determined by taking into account the selection architecture from the user's graph type selection history. Since people are influenced by the behavior of others, for example, the number of people responding to the guidance information provided may be shown to each user in order to increase the acceptance rate of alternatives. Note that if only services with a high degree of similarity are suggested, users may tire of being presented with services with the same features over and over again, so it is more preferable to insert services with a low degree of similarity as noise.

If the number of people planning to use the service subject to adjustment is greater than the maximum number, the service will be provided to the users with the greatest change in the number of people (e.g., the difference between the average number of passengers and the minimum number of passengers) in order of the probability of occurrence of the extracted behavior before and after the use that is subject to adjustment. The generated guidance information is transmitted to the user terminal 3 via the communication I/F 13.

<Data composition>
Next, configuration examples of each DB (or DB information) will be described with reference to Fig. 2 to Fig. 7. Fig. 2 shows an example of a customer number adjustment standard DB 200. The customer number adjustment standard DB 200 is a database that manages congestion adjustment policies of transportation companies and facility managers such as stores.

This customer number adjustment standard DB200 stores information on routes and stores for which customer numbers are to be adjusted, and the desired number of users, which information is acquired or received from an appropriate operator's terminal, such as a transportation operator terminal 5 or a store terminal 4.

The customer number adjustment criteria DB200 is composed of the following values: ID211 that uniquely identifies a business operator, such as a transportation business operator or a store operator; the business operator's business name 212; the time period to be adjusted 213; adjustment targets 214, such as individual stations or stores; minimum number of people 215, which indicates the desired minimum number of users for the target; and maximum number of people 216, which indicates the desired maximum number of users.

Figure 3 shows an example of user behavior information DB300. User behavior information DB300 is a database that manages user behavior by time and type.

This user behavior information DB300 is composed of the following values: ID311 that identifies the user behavior information, time 312 that indicates the time of the behavior, facility 313 that indicates the location where the behavior was performed, behavior content 314 that indicates the content of the behavior, and service used 315 that indicates the service used or item related to the behavior.

Among these, the behavior details 314 may be classified and registered as purchase, visit, boarding, etc. The service used 315 is acquired from the purchase history 820, the reservation information 830, the POS data 850, the ticket gate entry/exit record 860, and the like.

Figure 4 shows an example of a behavior pattern DB 400. The behavior pattern DB 400 is a database that manages a series of actions that a user is likely to perform consecutively, i.e., behavior patterns.

This behavior pattern DB 400 is composed of the following values: ID 411 for identifying a behavior pattern, behavior 412 indicating a specific behavior content, time 413 indicating the time period or day of the week when the behavior is performed, preceding behavior 414 indicating an behavior performed prior to behavior 412, preceding behavior probability 415 indicating the probability of performing the behavior prior to behavior 412, dependent behavior 416 indicating an behavior performed dependent on behavior 412, and dependent behavior probability 417 indicating the probability of performing the behavior dependently. Note that preceding behavior 414 and dependent behavior 416 may be registered separately according to the behavior content and related items such as purchased products.

Figure 5 shows an example of an item basic information DB 500. The item basic information DB 500 is a database that manages basic information about items.

This item basic information DB 500 is composed of an item common ID 511 that uniquely identifies item information, item 512 indicating the item name, producer 513 indicating the producer's name, place of origin 514 indicating the place of origin, storage period 515 to indicate freshness, product sales continuation period 516 indicating new products or long-selling products, and industry sales 517 based on POS data 850 and service reputation 880 extracted from SNS. Other items may be used as basic information items.

Figure 6 shows an example of an item evaluation DB 600. The item evaluation DB 600 is a database showing the evaluation values of items. This item evaluation DB 600 is composed of the following values: a common ID 611 for the item, an item 612 indicating the name of the item, a region 613 indicating the evaluation value of the locality, a safety 614 indicating the evaluation value of the safety, a newness 615 indicating the evaluation value of the newness, and a popularity 616 indicating the popularity. Other items may be used based on the items in the item basic information DB 500. The evaluation value is, for example, a five-point scale, and the criteria are set individually for each item.

Figure 7 shows an example of a service evaluation DB 700. The service evaluation DB 700 is composed of the following values: ID 711 that identifies the service evaluation, service 712 that indicates the service name, related item list 713 that indicates the common ID 611 of related items, locality 714 that indicates the locality evaluation value, safety 715 that indicates the safety level, newness 716 that indicates the newness of the service, and popularity 717 that indicates the popularity level.

Of these, services 712 are various services used by the user, such as product names and facilities used. The evaluation value for each item is the average of the item evaluation values recorded in the item evaluation DB 600 for the items with the item common ID 611 included in the related item list 713. In addition to the evaluation for each service, for example, a facility evaluation table may be created, and an evaluation for each facility may be performed based on the evaluation values of the services provided at the facility.

Note that location information 810 and purchase history 820 are not shown in the figure, but this is information about the user's behavioral history obtained from the user's smartphone or IC card.

Also, although usage reservations 830, purchase records 840, and POS data 850 are not shown, these are information related to the store's services that are registered by the store staff.

Also, although not shown in the figure, the ticket gate entry/exit record 860 and passenger number statistics 870 are information regarding the number of passengers based on ticket gate entry/exit information recorded in the user's IC card usage history held by the transportation company, and data obtained from the vehicle's weight sensor, etc.

In addition, service reputation 880 is not shown, but this is information about the reputation of each service extracted by the information extraction unit 61.

<Flow example: Guidance information generation>
The actual procedure of the method for providing guide information in this embodiment will be described below with reference to the drawings. The various operations corresponding to the method for providing guide information described below are mainly realized by a program that is read into a memory or the like and executed by the guide information providing device 1. This program is composed of codes for performing the various operations described below.

Figure 8 is a diagram showing an example of the flow of the guidance information providing method in this embodiment, specifically, an example of the flow showing the guidance information generating operation. This flow is processed by implementing the provision user selection unit 103 and the guidance information selection unit 104 as the analysis program 100 is executed by the CPU 12.

First, the user selection unit 103 obtains information on the route (or store, etc.) that will be relieved from congestion after, for example, three hours from the passenger number adjustment standard 200, and calculates the change in the number of passengers by comparing it with the average value of the passenger number statistics 870 (S1001). The timing of performing this process can be changed, and an effective time can be set based on the track record of the proposed user behavior change rate.

Next, the provision user selection unit 103 identifies users who plan to use the route in question based on the user's route search results and facility reservation information 830 (S1002).

Then, the guidance information selection unit 104 extracts behavior patterns from the behavior pattern DB 400 for the user identified in S1002, and identifies the behavior with the highest occurrence probability by referring to the occurrence probability of the behavior before and after using the relevant line (S1003).

In addition, in step S1003, the guidance information selection unit 104 selects (other) services with ratings that are closest to the characteristics of the service ratings of the identified behavior by graph matching based on the service rating DB 700. The services selected at this time may be those whose service locations can be reached without using the relevant route, and may be those located within a travel time defined as a criterion.

The guidance information selection unit 104 then selects the user with the maximum change in number (the difference between the average number of passengers and the minimum number) from among the users who plan to use the target route (S1004). The priority order for selection is determined by the highest probability of occurrence of behavior before and after using the extracted route to be adjusted. The guidance information selection unit 104 then transmits the generated guidance information to the user terminal 3 via the communication I/F 13 (S1005).

Next, the provision user selection unit 104 counts the number of times the suggested guidance information has been registered by users every 30 minutes (S1006). The presence or absence of registration is counted from the log registered by the user operating the user terminal 3. It may also be determined from cancellations of plans to use facilities or new reservation information. Alternatively, it may be confirmed from location information whether registered users are actually acting in accordance with the registered information. The time interval for counting can be changed.

Then, as a result of the above-mentioned tallying, if the "number of registered passengers" reaches the minimum number of passengers (the difference between the average number of passengers and the maximum number of passengers) (S1007: Y), the provided user selection unit 103 ends the process. On the other hand, if the number of registered passengers does not reach the minimum number of passengers (S1007: N), the provided user selection unit 103 identifies the target users again in S1002. Following this, the guidance information selection unit 104 provides guidance information. Thereafter, the provided user selection unit 103 repeats the process in the same manner until the number of registered passengers reaches the minimum number of passengers (S1007: Y) or until the departure time of the relevant train, and ends the process.

<Flow example: Behavioral pattern analysis>
Next, the processing operation by the behavior pattern analysis unit 101 will be described with reference to Fig. 9. In this case, the behavior pattern analysis unit 101 periodically (for example, once every three months) acquires location information 810 and purchase history 820 from the user terminal 3, acquires usage reservation information 830 and POS data 850 from the store terminal 4, and further acquires ticket gate entrance/exit record 860 from the transportation company terminal 5 (S1101). Then, the behavior pattern analysis unit 101 arranges the acquired information in chronological order for each user, and creates the user behavior information DB 300 (S1101).

Next, the behavior pattern analysis unit 101 calculates the probability of consecutive actions for each action (preceding action and dependent action) that occurred before and after each action (S1102). Then, the preceding action and dependent action with the highest occurrence probability are registered in the behavior pattern DB 400 (S1103). Note that if it is desired to provide guidance information for three or more alternative actions, preceding actions and dependent actions with second or lower occurrence probabilities may also be registered and used.

<Flow example: Service information analysis>
Next, the processing operation by the service information analysis unit 102 will be described with reference to Fig. 10. In this case, the service information analysis unit 102 acquires, as information on the items handled at the facility, the purchase record 840 and the POS data 850 from the store terminal 4, and acquires the service reputation 880 from the SNS information extractor 6. Then, the service information analysis unit 102 registers the acquired information for each item in the item basic information DB 500 (S1201).

Next, the service information analysis unit 102 evaluates the characteristics of each item based on the item basic information DB 500. Evaluation items include regionality and popularity, and a five-point evaluation is performed by setting criteria, for example (S1202). The service information analysis unit 102 also registers the five-point evaluation value obtained here, i.e., the evaluation value, in the item evaluation DB 600.

Then, the service information analysis unit 102 evaluates the characteristics of each service based on the product evaluations of related products, registers this in the service evaluation DB 700 (S1203), and ends the process.

The evaluation value of a service is calculated by calculating the average evaluation value of related items for each feature item in the item evaluation DB 600. For example, if the service is cooking, related items are linked to a service by having the store register the recipe.

<Flow example: Guidance information selection process>
Next, a processing operation by the guidance information selection unit 104 will be described with reference to Fig. 11. As one example of the guidance information selection process, for example, selection of guidance information is performed in a case where a route change is encouraged to avoid using a crowded train.

When the provision user selection unit 103 determines the target user and the behavior to be changed, the guidance information selection unit 104 extracts the behavior preceding the target behavior from the behavior pattern DB 400 (S1301). This extracted behavior is the behavior with the highest occurrence probability as the preceding behavior of the behavior to be changed.

Next, the guidance information selection unit 104 selects another service having characteristics most similar to the service used in the preceding action extracted in S1301 (S1302).
A graph created from the evaluation values of each item in the service evaluation DB 700 is matched, and services with a high matching rate and the same service type are extracted.

Then, the guidance information selection unit 104 searches for candidates for a detour route to the destination that passes through the facility that provides the service selected in S1302 (S1303). The service selected at this time may be a service that can be accessed without using the route that is desired to be relieved of congestion, and may be located within a travel time that is set as a criterion. In addition to proposing an alternative to the preceding action, a proposal to encourage a route change may also be a proposal of another destination where the planned action at the destination can be achieved. In this case, alternative destinations that are close to the characteristics of the original destination are extracted from the service evaluation DB 700, and are proposed as a set together with the alternative to the preceding action. An example of such a proposal may be a proposal of a set of "coffee shop C" and "satellite office B" that can be accessed via an uncrowded route instead of "satellite office A".

Then, the guidance information selection unit 104 selects a route from the above-mentioned detour route candidates that has a smaller increase in travel time than the originally planned route, and provides this to the user terminal 3 as guidance information together with alternative service proposals (S1304), and ends the process.

Figure 12 shows an example of a guidance information screen displayed on the display unit 31 of the user terminal 3. The guidance information screen 32 displays recommended routes and stopovers for the user as a sequence of actions, as a result of creating alternative plans to avoid congestion (S1003).

For example, when a user searches for a route to "satellite office A," the shortest train route is crowded. If it is determined from the user's behavior pattern in behavior pattern DB400 that there is a high probability that the user will visit "coffee shop B" immediately before visiting the satellite office, then "coffee shop A," which has characteristics similar to those of "coffee shop B," is selected from service evaluation DB700 and proposed as recommended guidance information. This "coffee shop A" is located in a place that can be reached by an uncrowded train.

Providing this type of guidance information will help ease congestion on public transport and attract more customers to stores. Users can achieve their goals without changing the flow of their movements, and can obtain information on services that match their preferences and comfortable travel routes.

As described above, according to this embodiment, the behavioral change rate can be improved by analyzing the connections between users' behavior and the services they use, and providing guidance information that maintains the connections. Furthermore, according to this embodiment, guidance information can be provided to users for whom behavioral change is desired, in line with the operator's congestion adjustment policy. This allows users who plan to use highly congested routes to avoid congested routes by being suggested alternative actions that maintain the connection with the purpose of the action, and the number of people who are to undergo behavioral change can also be managed. It is also possible to guide users to routes with fewer users and control the number of users at facilities.

The above describes in detail the best mode for carrying out the present invention, but the present invention is not limited to this, and various modifications are possible without departing from the spirit of the present invention.

For example, the configuration of each database in the above embodiment is merely an example, and some data may not be registered, or other related data may be added and registered.

In addition, in the guidance information providing system of the above embodiment, the SNS information extractor 6 is configured to be separate from the guidance information providing device 1, but according to another example, it may be configured to be included in the guidance information providing device 1. In addition, in the guidance information providing system of the above embodiment, the function configured to be included in the guidance information providing device 1 may be separated and included in an external computer.

The present invention can also be understood as an analysis program executed by the guidance information providing device 1, and a guidance information providing program executed by the guidance information providing system 10.

According to this embodiment, it is possible to provide guidance information that matches the behavioral patterns and service preferences of users, taking into account the travel demand control policies of transportation operators, developers, local governments, etc.

The description in this specification makes clear at least the following. That is, in the guidance information providing device of this embodiment, the calculation unit may further execute a process of selecting a user who may be a target for using the congestion adjustment target as a guidance information providing target based on the event of a service search or service reservation by the user, and may refer to the behavioral pattern of the guidance information providing target to identify the connection of a series of behaviors indicated by the behavioral pattern.

This makes it possible to select users involved in congestion adjustment based on their specific prior actions and make them the targets of subsequent processing. Ultimately, it becomes possible to more efficiently provide guidance information that matches users' behavioral patterns and service preferences, taking into account the travel demand control policies of transportation operators, developers, local governments, etc.

In addition, in the guidance information providing device of this embodiment, the calculation unit may acquire the behavioral information of the user from the terminal of the user or a specified device that manages the behavioral information, store the behavioral information in the memory unit, identify a preceding behavior and a dependent behavior of a specified behavior for each user from the behavioral information, calculate the occurrence probability of the preceding behavior and the dependent behavior, respectively, and store them in the memory unit as evaluation information of the connection of the series of behaviors.When identifying a service that is to be used in either the previous or next behavior, the calculation unit may identify the service that is to be used in the behavior with the highest occurrence probability.

This makes it possible to efficiently identify alternatives by using information on actions that users tend to take and the services they use when doing so. This in turn makes it possible to more efficiently provide guidance information that matches users' behavioral patterns and service preferences, taking into account the travel demand control policies of transportation operators, developers, local governments, and so on.

In addition, in the guidance information providing device of this embodiment, the calculation unit may identify the service that is the target of the behavior with the highest occurrence probability, and generate the guidance information that includes, as an alternative, the use of another service that can achieve the purpose of the behavior and has the same or similar characteristics as the characteristics of the identified service.

This makes it possible to efficiently identify alternatives by using information on the actions that users are most likely to perform and the services they use when performing those actions. Ultimately, it will be possible to more efficiently provide guidance information that matches users' behavioral patterns and service preferences, taking into account the travel demand control policies of transportation operators, developers, local governments, etc.

Furthermore, in the guidance information providing device of this embodiment, the memory unit may have a basic item information database storing attribute information of each item related to the service, and the calculation unit may evaluate attribute information for each of predetermined evaluation items for each item based on the basic item information database, store the evaluation value for each of the evaluation items for each item in the memory unit to generate an item evaluation database, calculate, for each service, an average of the evaluation values of items related to the service for each item based on the item evaluation database, and store the calculated averages as service evaluations for each item to generate a service evaluation database, and when generating the alternatives, refer to the service evaluations and select, as the alternative, the use of another service having characteristics closest to those of the identified service in the evaluation value for each evaluation item.

This makes it possible to efficiently identify information about alternative services that provide items with similar attribute trends to the items provided by the service (e.g., food and drink). This in turn makes it possible to more efficiently provide guidance information that matches the behavioral patterns and service preferences of users, taking into account the travel demand control policies of transportation operators, developers, local governments, etc.

In addition, in the guidance information providing device of this embodiment, the storage unit stores customer number adjustment criteria in the congestion adjustment policy information, which specify the congestion adjustment targets for which the operator wishes to adjust the number of customers and values related to the minimum and maximum number of users desired for the congestion adjustment targets, and the calculation unit may determine the number of people to be provided with the guidance information based on the difference between the average number of customers indicated by the provision status information and the minimum or maximum number of users specified by the customer number adjustment criteria.

This will enable the generation of alternative plans that efficiently adjust passenger numbers to meet operator needs. This will in turn enable transportation operators, developers, local governments, and other parties to more efficiently provide guidance information that matches users' behavioral patterns and service preferences, based on their travel demand control policies.

In addition, in the guidance information providing device of this embodiment, the calculation unit may be configured to tally up the number of people among the guidance information recipients who have accepted behavior in accordance with the guidance information at regular intervals, and repeat the selection of the guidance information recipients and subsequent processes until the minimum number of users is achieved.

This makes it possible to streamline processing by taking into account the actual changes in behavior in response to guidance information. Ultimately, it will be possible to provide more efficiently guidance information that matches users' behavioral patterns and service preferences, taking into account the travel demand control policies of transportation operators, developers, local governments, and so on.

Reference Signs List 1 Guide information providing device 2 Network 3 User terminal 4 Shop terminal 5 Transportation company terminal 6 SNS information extractor 10 Guide information providing system 60 Information extraction program 61 Information extraction unit 11 Storage unit 12 CPU (calculation unit)
13 Communication I/F
100 Analysis Program
101 Behavioral Pattern Analysis Department
102 Service information analysis unit 103 User selection unit 104 Guide information selection unit 110 Database 200 Customer number adjustment standard DB
300 User behavior information DB
400 Action Pattern DB
500 Goods basic information DB
600 Product Evaluation DB
700 Service evaluation DB
810 Location information 820 Purchase history 830 Reservation 840 Purchase record 850 POS data 860 Ticket gate entry/exit record 870 Customer number statistics 880 Service reputation

Claims (6)

a storage unit that holds at least each piece of information: a congestion adjustment policy that specifies the service to be subject to congestion adjustment and the desired number of customers at the operator ; a behavior pattern that specifies the occurrence probability of each behavior performed before and after a specific behavior in a series of behaviors that are likely to be performed consecutively by a user of the service provided by the operator; and a provision status of the service that indicates the characteristics of each of the services;
a calculation unit that executes a process of identifying a user who is expected to use a service that is a congestion adjustment target defined in the congestion adjustment policy , based on reservation information for the service obtained from a terminal of a corresponding business operator , a process of referring to the behavioral pattern for the user and identifying an action that is likely to occur before or after the use of the service that is a congestion adjustment target in a series of actions indicated by the behavioral pattern, a process of identifying another service that has characteristics identical or similar to characteristics of the service used in the identified action, based on the information on the provision status, a process of searching for detour route candidates for avoiding the use of the service that is the congestion adjustment target and encouraging the use of the other service, and generating guidance information including information on the detour route candidates ;
A guide information providing device comprising: The storage unit is
a basic item information database for storing attribute information of each item related to the service;
The calculation unit is
evaluating attribute information for each of predetermined evaluation items for each item based on the item basic information database, and storing the evaluation values for each of the evaluation items for each item in the storage unit to generate an item evaluation database;
calculating, for each service, an average of the evaluation values of the products related to the service for each item based on the product evaluation database, and storing the average calculation results as service evaluations for each item to generate a service evaluation database;
When generating the guidance information , the service evaluation is referred to, and the service used in the action with a high occurrence probability and the use of the other service having the closest characteristics of the evaluation value for each of the evaluation items are selected as an alternative.
2. The guide information providing device according to claim 1 . The storage unit is
The congestion adjustment policy information stores a customer number adjustment standard that specifies a congestion adjustment target for which the business operator wishes to adjust the number of customers and values related to the minimum and maximum number of users desired for the congestion adjustment target,
The calculation unit is
The number of people to whom the guidance information is to be provided is determined based on the difference between the average number of customers indicated by the information on the provision status and the minimum number of users or the maximum number of users specified by the customer number adjustment standard.
2. The guide information providing device according to claim 1 . The calculation unit is
a counting unit that counts the number of people who have acted in accordance with the guidance information among the people to whom the guidance information is to be provided at regular intervals, and repeats the selection of the people to whom the guidance information is to be provided and subsequent processes until the minimum number of users is achieved;
4. The guide information providing device according to claim 3 . a storage unit that holds at least each piece of information: a congestion adjustment policy that specifies the service to be subject to congestion adjustment and the desired number of customers at the operator ; a behavior pattern that specifies the occurrence probability of each behavior performed before and after a specific behavior in a series of behaviors that are likely to be performed consecutively by a user of the service provided by the operator; and a provision status of the service that indicates the characteristics of each of the services;
a calculation unit that executes a process of identifying a user who is expected to use a service that is a congestion adjustment target defined in the congestion adjustment policy , based on reservation information for the service obtained from a terminal of a corresponding business operator , a process of referring to the behavioral pattern for the user and identifying an action that is likely to occur before or after the use of the service that is a congestion adjustment target in a series of actions indicated by the behavioral pattern, a process of identifying another service that has characteristics identical or similar to characteristics of the service used in the identified action, based on the information on the provision status, a process of searching for detour route candidates for avoiding the use of the service that is the congestion adjustment target and encouraging the use of the other service, and generating guidance information including information on the detour route candidates ;
A guide information providing system comprising a guide information providing device having the above-mentioned configuration. An information processing device,
a memory unit for storing at least each piece of information: a congestion adjustment policy that specifies a service to be subject to congestion adjustment and a desired number of customers at a business operator ; a behavior pattern that specifies the occurrence probability of each behavior performed before and after a specific behavior in a series of behaviors that are likely to be performed consecutively by a user of the service provided by the business operator; and a provision status of the service that indicates the characteristics of each of the services,
a process of identifying a user who is expected to use a service that is a target of congestion adjustment defined in the congestion adjustment policy , based on reservation information for the service obtained from a terminal of a corresponding business operator ; a process of referring to the behavioral pattern for the user and identifying an action that is likely to occur before or after the use of the service that is a target of congestion adjustment in a series of actions indicated by the behavioral pattern; a process of identifying other services that have characteristics that are identical or similar to the characteristics of the service used in the identified action, based on the information on the provision status; a process of searching for detour route candidates for avoiding the use of the service that is a target of congestion adjustment and encouraging the use of the other service, and generating guidance information including information on the detour route candidates ;
A method for providing guidance information comprising the steps of:

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