Computer system and processing method

Abstract

To allow for utilizing a travel history of a user.SOLUTION: A computer system according to an aspect of the present disclosure comprises a processor configured to use map data indicative of correspondence between a geographical position of a POI and a POI tag showing an attribute of the POI to associate travel data representing a travel route of a user with at least one POI tag.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] One aspect of the present disclosure relates to a computer system, a processing method, a program, and / or a data structure. [Background technology]

[0002] Patent Document 1 describes a cluster generation device that classifies users based on the user's location information and information on spots visited by the users. This cluster generation device includes a user information acquisition unit that acquires location information and time information of multiple users, a cluster generation unit that uses the user's location information to generate clusters that are classifications of users based on the spots visited by the users, and a route generation unit that generates, for each cluster, a travel route based on the travel history between the spots of the cluster from the time information and location information of users belonging to the cluster. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6810978 Summary of the Invention [Problem to be solved by the invention]

[0004] One aspect of the present disclosure aims to utilize a user's movement history. [Means for solving the problem]

[0005] A computer system according to an aspect of the present disclosure includes a processor that associates at least one POI tag with travel data indicating a user's travel route based on map data indicating a correspondence between a geographical position of a POI and a POI tag indicating an attribute of the POI. The processor sets a user tag indicating an attribute of a user to be analyzed based on a POI tag associated with the movement data of the user, and sets a POI tag for the POI to be analyzed based on the user tag set for the user of the movement data associated with the POI. The processor identifies a user type indicating a classification of the target user based on at least one POI tag associated with the movement data, and presents to the target user a visiting order from the reference POI corresponding to the identified user type based on visit candidate data indicating a correspondence between the user type and a visiting order from the reference POI to at least one visiting destination POI. [Brief description of the drawings]

[0006] [Figure 1] FIG. 1 is a diagram illustrating an example of an application of an information management system according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of a hardware configuration of a computer used in the information management system according to the embodiment. [Diagram 3] FIG. 2 is a diagram illustrating an example of a functional configuration of an information management system according to an embodiment. [Figure 4] FIG. 2 is a diagram illustrating an example of a data structure of map data. [Diagram 5] FIG. 4 is a diagram illustrating an example of a data structure of user data. [Figure 6] FIG. 4 is a diagram illustrating an example of a data structure of movement data. [Figure 7] FIG. 2 is a diagram illustrating an example of a data structure of visit candidate data. [Figure 8] FIG. 2 is a diagram illustrating an example of a data structure of visit history data. [Figure 9] 11 is a flowchart showing an example of tagging movement data. [Figure 10] 1 illustrates the concept of tagging movement data. [Figure 11] 13 is a flowchart showing an example of a user analysis. [Figure 12] 13 is a flowchart showing an example of POI analysis. [Figure 13] 11 is a flowchart illustrating an example of a visiting order recommendation. [Figure 14] FIG. 13 is a diagram illustrating the concept of visiting order recommendations. [Figure 15] 13 is a flowchart showing an example of charging for a POI. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In the description of the drawings, the same or equivalent elements are designated by the same reference numerals, and duplicated explanations will be omitted.

[0008] [System Overview] The information management system 1 according to the embodiment is a computer system that executes processing related to a user's travel route. A travel route refers to information about travel from one point to another point in the real world, typically information about travel from a starting point to a destination. A starting point refers to a location set as a starting point for searching for a travel route, and a destination refers to a location set as an ending point for the search.

[0009] In one example, the information management system 1 associates a tag, which is information indicating a POI (Point of Interest) or an attribute of a user, with movement data indicating a movement route actually taken by a user. The actual movement route can also be called a movement history or a movement log. In this disclosure, a tag indicating an attribute of a POI is also called a "POI tag," and a tag indicating an attribute of a user is also called a "user tag." A POI refers to a specific point on a map, and typically corresponds to a specific feature. Any point or feature, such as a house or a public facility, can be a POI. The attribute of a POI is information that indicates the nature, characteristics, or situation of the POI. More specifically, POI attributes (information representing a nature, characteristic, or situation) include the name and / or content of the object and / or information present at the POI, the name and / or content of the object and / or information provided at the POI, the name and / or content of the service provided at the POI, the tendency of users visiting the POI (visiting alone, with family, friends, and / or business, age group, occupation, etc.), and the purpose (a purpose other than the purpose of receiving the service provided at the POI, such as reading a book at a POI that provides coffee service). User attributes are information representing the nature, characteristic, or situation of a user. In this disclosure, the process of associating a tag with movement data is also referred to as tagging.

[0010] A feature is any tangible or intangible object that exists on the ground. A feature may be natural or man-made. For example, features may include mountains, farmland, residential areas, vacant lots, rivers, lakes, oceans, tourist sites, roads, railways, buildings, parks, towers, traffic lights, railroad crossings, pedestrian crossings, footbridges, buoys, etc. Examples of intangible features include areas set up for any purpose (e.g., no-photography areas, temporary no-entry areas, etc.), areas where events are held, gathering places, photo spots, etc.

[0011] By associating a tag with a user's movement history, various analyses of the user, the movement route, or the POI become possible. For example, by tagging multiple movement histories of multiple users, it becomes possible to find movement trends according to the classification of the users. Here, the movement trend typically indicates which POI is popular. In addition, when there are multiple popular POIs, the visiting order can also be said to be a movement trend. Then, by classifying the popular POIs or the visiting order for each user, it becomes possible to prepare for recommendation to a user type indicating a specific classification. In one example, the information management system 1 recommends a visiting order from a starting point to a user according to a user type indicating the classification of the user. In this disclosure, the visiting order refers to information indicating in what order at least one visiting destination is visited. In this disclosure, a user to whom the information management system 1 recommends a visiting order is also referred to as a "target user". In addition, a starting point used as a criterion for recommendation is also referred to as a "reference POI", and a place set as a visiting destination is also referred to as a "visiting POI". In one example, the destination POI is a POI that the user can reach from the reference POI in a relatively short time. For example, when a target user staying at a hotel inquires about nearby POIs using a user terminal, the information management system 1 responds to the inquiry and recommends a visiting order for the destination POIs that can be reached from the hotel, which is the reference POI (starting point).

[0012] In one example, a POI tag (for example, "single person", "family") is registered by a manager of the POI (typically, the owner of the store if the POI is a store). The information management system 1 may transmit advertising information of the POI based on the POI tag to a user terminal approaching the POI. The timing of transmission may be left to the discretion of the manager of the information management system 1, or may be set in consideration of the request of the POI manager (time period, frequency, etc.). Furthermore, the information management system 1 may execute a charge to the manager of the POI in response to a user who has acquired the advertising information via a user terminal visiting the POI. This charge can be said to be a mechanism in which the manager of the information management system 1 receives a success fee or advertising fee from the manager of the POI for matching the POI with the user (visitor). In the case of a success fee type, the charge may be proportional to the number of matches between the POI and the user (visitor), or may be changed according to the request of the POI manager (time period, frequency, etc.). The advertising information refers to information intended to arouse the user's interest in the POI. If the POI is a store, the advertising information may include information such as business hours, regular holidays, and temporary closures. For example, the advertising information is generated to inform the user of the existence of the POI and to guide the user to the POI. The above-mentioned visiting order can be said to be information for informing the user of the existence of the POI and to guide the user to the POI. Therefore, the visiting order is an example of advertising information.

[0013] [System configuration] 1 is a diagram showing an example of an application of an information management system 1. In one example, the information management system 1 includes a server 10. The server 10 can access a database group 20 via a communication network NW to read and write data. The server 10 can transmit and receive data to and from one or more user terminals 30 and one or more facility terminals 40 via the communication network NW.

[0014] The server 10 is a computer that executes processes related to a user's travel route. In one example, the server 10 is configured by a large computer such as a business server. The server 10 may be configured by one or more computers. When multiple computers are used, a single server 10 is logically configured by connecting these computers to each other via a communication network.

[0015] The database group 20 is a collection of databases that store data used in the information management system 1. A database is a non-transitory storage medium or storage device that permanently stores electronic data. Each database may be constructed as a part of the information management system 1, or may be provided in a computer system separate from the information management system 1.

[0016] The user terminal 30 is a computer operated by a user. In one example, the user terminal 30 is a mobile terminal such as a mobile phone, a smartphone, a tablet terminal, a wearable terminal, or a laptop computer. The user terminal 30 may be a device configured by a single housing, or may be configured by multiple devices. For example, the user terminal 30 may be a combination of a wearable terminal and a smartphone.

[0017] Facility terminal 40 is a computer managed or operated by a facility, which is an example of a POI. The facility may be, for example, any type of store. Facility terminal 40 may be configured by a large computer such as a business server, a personal computer, or any type of mobile terminal.

[0018] FIG. 2 is a diagram showing an example of a hardware configuration of a computer 110 used in the information management system 1. For example, the computer 110 has a control circuit 100. In one example, the control circuit 100 has one or more processors 101, a memory 102, a storage 103, a communication port 104, and an input / output port 105. The processor 101 executes an operating system and an application program. The storage 103 is composed of a storage medium such as a hard disk, a non-volatile semiconductor memory, or a removable medium (e.g., a magnetic disk, an optical disk, etc.), and stores the operating system and the application program. The memory 102 temporarily stores a program loaded from the storage 103, or a calculation result by the processor 101. The processor 101 functions as an individual functional module by executing a program in cooperation with the memory 102. The communication port 104 performs data communication with other devices via the communication network NW according to instructions from the processor 101. The input / output port 105 performs input / output of electric signals between the input / output device (user interface) such as a keyboard, a mouse, a monitor, and a touch panel according to instructions from the processor 101.

[0019] FIG. 3 is a diagram showing an example of the functional configuration of the information management system 1 (server 10). In one example, the server 10 includes a tagging unit 11, an analysis unit 12, a recommendation unit 13, and a billing unit 14 as functional modules. The tagging unit 11 is a functional module that associates tags with movement data. The analysis unit 12 is a functional module that processes the tagged movement data and analyzes at least one of the user and the POI. "Analyzing the user (or POI)" refers to a process of estimating the characteristics or tendencies of the user (or POI). The recommendation unit 13 is a functional module that presents the visiting order to the target user. The billing unit 14 is a functional module that executes billing for the administrator of the POI in response to a user who has acquired the advertising information of the POI visiting the POI.

[0020] 3 also shows the individual databases that make up the database group 20. In one example, the database group 20 includes a map database 21, a user database 22, a movement history database 23, a visit candidate database 24, and a visit history database 25.

[0021] The map database 21 is a database that stores map data indicating map elements that make up a map. Examples of map elements include nodes, links, and POIs.

[0022] A node is a location that characterizes a route, and more specifically, a location where the moving method (e.g., direction, speed, etc.) of a moving object can be changed, or where the moving method changes. For example, a node corresponds to a transfer point such as a station, a bus stop, or a parking lot, or an intersection.

[0023] A link is a virtual line that is set to indicate a route, and connects adjacent nodes. The shape of a link may be straight or curved, or may be a combination of straight and curved lines. On the ground, the shape of a link may depend on the shape of a road or a track such as a railway. There may be multiple links connecting two nodes. For example, two nodes may be connected by both a railway-related link and a road-related link.

[0024] In one example, the map data includes node data indicating a plurality of nodes, link data indicating a plurality of links, and POI data indicating a plurality of POIs. The structures of these data will be described with reference to Fig. 4. Fig. 4 is a diagram showing an example of the data structure of the map data. In this example, the map data 210 includes node data 211, link data 212, and POI data 213.

[0025] In one example, the node data 211 includes the following data items: node ID, coordinates, and node attributes. The node ID is an identifier that uniquely identifies an individual node. The coordinates are values ​​that indicate the two-dimensional or three-dimensional geographic location of the node. The coordinates may be expressed using latitude and longitude, or may be set according to other coordinate systems. The node attributes are information that describes the nature, characteristics, or status of the node. For example, the node attributes may include feature information about a feature associated with the node.

[0026] In one example, the link data 212 includes, as data items, a link ID, a first node ID, a second node ID, and link attributes. The link ID is an identifier that uniquely identifies an individual link. The first node ID and the second node ID are both node IDs that identify nodes located at the ends of the link. The link attributes are information that represents the nature, characteristics, or status of the link. For example, the link attributes may include at least one of a means of transportation such as a means of transportation, a time or cost required to travel the link, a status of the link (e.g., traffic information), and a feature associated with the link (i.e., feature information).

[0027] In one example, the POI data 213 includes data items such as a POI_ID, basic POI information, and POI attributes. The POI_ID is an identifier that uniquely identifies each POI. In one example, the basic POI information includes, for example, an arrival point, a name, representative coordinates, and feature information. The arrival point indicates a link (e.g., a road) to which the entrance / exit of the POI is connected, and the link ID of the link is set in this data item. The arrival point is an example of a data item that indicates a connection between a POI and a link. The name is the official name or common name of the POI, and is represented by, for example, the name of the head of the household, the house name, or the name of the building. The representative coordinates are values ​​that indicate the two-dimensional or three-dimensional geographical position of the POI, and are used to represent the location of a POI that has a two-dimensional or three-dimensional shape. The representative coordinates can also be called facility coordinates. When a facility that is considered as a single facility as a whole contains multiple smaller facilities in a nested structure, facility coordinates (representative coordinates) that represent the single facility as a whole may be used. The feature information is any information about features related to the POI. At least a part of the POI attributes is used as a POI tag for tagging the travel data. The POI attributes (POI tags) may indicate various items such as the classification of a store or facility, the classification of a product or service, etc. As shown in Fig. 4, the map data 210 (POI data 213) indicates the correspondence between the geographical positions of the POIs and the POI tags.

[0028] When one POI has multiple POI tags, at least some of the multiple POI tags may have a hierarchical structure. For example, multiple POI tags may be used that indicate the classification of the POI in multiple stages (e.g., major classification, medium classification, and minor classification). At least some of the multiple POI tags may be extended tags that are set later by processing by the analysis unit 12. POI data 213 for a main POI having multiple sub-POIs (e.g., a complex having multiple stores) may include POI attributes for each of the sub-POIs as POI tags.

[0029] The POI tags may be registered in advance in the map database 21 by an administrator of the information management system 1 or an administrator of the POIs. Alternatively, the POI tags may be added, changed, or deleted later in response to a request from the facility terminal 40. Alternatively, the POI tags may be automatically registered by the information management system 1 or another computer system. As an example of this automatic registration, the information management system 1 or another computer system may analyze an article on the Internet, such as a comment on a social networking service (SNS), set a POI tag, and register the POI tag in the map database 21.

[0030] The user database 22 is a database that stores user data related to users. FIG. 5 is a diagram showing an example of a data structure of user data. In this example, the user data 220 includes data items such as a user ID, user basic information, user attributes, and a user type. The user ID is an identifier that uniquely identifies an individual user. The user basic information includes, for example, a name. At least a part of the user attributes is used as a user tag for tagging the movement data. The user attributes (user tags) may indicate various items such as gender, age or age group, hobbies, and preferences. The user type may be obtained by analyzing the tagged movement data, or may be set in advance.

[0031] The movement history database 23 is a database that stores movement data indicating the movement route actually taken by the user. FIG. 6 is a diagram showing an example of the data structure of the movement data. In this example, the movement data 230 includes a user ID, position information, time information, and POI_ID as data items. The position information indicates the geographical position of the user terminal 30 that can be considered as the user's position. For example, the position information may be expressed by latitude and longitude, may be expressed as three-dimensional data further including altitude, or may be expressed by other coordinate systems. The time information indicates the date and time when the position information (geographical position) was obtained. The POI_ID is the ID of the POI corresponding to the geographical position indicated by the position information. As shown in FIG. 6, in the movement data 230, a plurality of combinations of the position information, time information, and POI_ID are associated with each user ID as time-series data.

[0032] In one example, movement data is provided from each user terminal 30 and stored in the movement history database 23. The user terminal 30 acquires a current location, which is the current geographical location of the user terminal 30, and a current time, which is the time when the current location is acquired. The user terminal 30 may identify the current location using a global positioning system (GPS), or may identify the current location by other means such as mobile phone base station data, WiFi (registered trademark) access point data, transportation IC card data, and proximity beacons. The user terminal 30 generates a record indicating a combination of a corresponding user ID, location information indicating the current location, and time information indicating the current time, and transmits this record to the movement history database 23. This record can be considered as information indicating the user's location at a given point in time. The user terminal 30 generates and transmits records at a given time interval, and thus a plurality of records of the user terminal 30 are accumulated in the movement history database 23 as time-series data, thereby recording the user's movement history (movement log). The computer that registers the records provided from the user terminal 30 in the movement history database 23 may be the server 10, or may be a computer different from the server 10, or may be a computer system different from the information management system 1.

[0033] A null value (NULL) is set in the POI_ID of a record newly registered in the movement history database 23. The new record is then processed by the information management system 1. If the geographical position indicated by the position information of the record corresponds to a POI, a significant value is set in the POI_ID field. The movement data 230 is associated with the user data 220 by the user ID, and is further associated with the POI data 213 by setting the POI_ID. Therefore, by referring to the movement data 230 in which the POI_ID is set, it is possible to identify the relationship between the user and the POI.

[0034] The visit candidate database 24 is a database that stores visit candidate data indicating a visiting order that may be recommended to a user. Fig. 7 is a diagram showing an example of the data structure of the visit candidate data. In this example, the visit candidate data 240 includes, as data items, a reference POI_ID, a user type, and a visiting order of at least one visiting POI. The reference POI_ID is the POI_ID of the reference POI. The visiting order is represented, for example, by the order of the POI_ID of at least one visiting POI.

[0035] The visit history database 25 is a database that stores visit history data used for charging the administrator of the POI. FIG. 8 is a diagram showing an example of the data structure of the visit history data. In this example, the visit history data 250 includes a recommendation ID, a user ID, and visit destination information as data items. The recommendation ID is an identifier that uniquely identifies the visit order presented to the target user. The user ID is the ID of the target user. The visit destination information indicates a pair of a POI_ID and a visit flag for each of at least one visit destination POI indicated by the visit order. The visit flag is information that indicates, in binary terms, whether or not the target user actually stopped at the visit destination POI. In one example, a visit flag of "0" indicates that the target user did not actually stop at the visit destination POI, and a visit flag of "1" indicates that the target user actually stopped at the visit destination POI.

[0036] With regard to each of the above data, each data item may be set either statically or dynamically. "Statically set" means that a value is set in advance and the setting will not be changed without human intervention. On the other hand, "dynamically set" means that a value can be changed without human intervention in response to any event. Dynamic setting is realized by executing a program that controls a given data item on a specific computer. Dynamic setting may be executed by the information management system 1 or by another computer system.

[0037] [System processing procedure] (Tagging movement data) 9 is a flowchart showing an example of tagging of movement data as a process flow S1. This process is executed after the movement data 230 is stored in the movement history database 23. For example, the process flow S1 may be executed by a periodic batch process.

[0038] In step S11, the tagging unit 11 selects one user to be processed. For example, the tagging unit 11 refers to the movement history database 23 and selects one user ID.

[0039] In step S12, the tagging unit 11 acquires the movement data 230 of the selected user. The tagging unit 11 reads out the movement data 230 including the selected user ID from the movement history database 23. As described above, this movement data 230 is time-series data consisting of a plurality of records (e.g., a large number of records).

[0040] In step S13, the tagging unit 11 identifies the user's stopover points based on the movement data 230. The tagging unit 11 refers to each record of the movement data 230 and identifies the location where the user continued to stay for a given time span or more as the stopover point. For example, the tagging unit 11 identifies a group of records in which the change in geographical position indicated by the position information is within a given geographical range continuously in the time span, and identifies the stopover point based on the position information of the group of records. The given time span may be, for example, 10 minutes, 30 minutes, 1 hour, 3 hours, 6 hours, etc. The given geographical range may be, for example, a radius of several meters or a radius of several tens of meters. The tagging unit 11 may identify one or more stopover points from the movement data 230 of one user. The tagging unit 11 may obtain, as the location of the stopover point, a statistical value (for example, an average value, a median value, a mode value, etc.) of a plurality of geographical positions indicated by the position information, or may obtain a geographical range indicated by the plurality of geographical positions.

[0041] In step S14, the tagging unit 11 identifies a POI corresponding to each of the one or more identified stop-off points. For each stop-off point, the tagging unit 11 searches the POI data 213 in the map database 21 for a POI having facility coordinates or representative coordinates that are closest to the geographical position or geographical range of the stop-off point. Then, the tagging unit 11 recognizes that the POI corresponds to the stop-off point.

[0042] In step S15, the tagging unit 11 associates the POI tags of the identified one or more POIs with the movement data 230. For each of the one or more POIs, the tagging unit 11 acquires a POI_ID from the POI data 213 in the map database 21, and sets the POI_ID in the movement data 230 of the selected user in the movement history database 23. Through this process, the movement data 230 is associated with the POI data 213 via the POI_ID, and thus the POI tag corresponding to the POI_ID is associated with the movement data 230.

[0043] As shown in step S16, tagging section 11 executes the processes of steps S11 to S15 for all users to be processed.

[0044] FIG. 10 is a diagram showing a concept of tagging movement data. In this example, the tagging unit 11 identifies three stopover points 301, 302, and 303 from movement data 300 of a user Ua having user attributes (user tags) of “male” and “40s”. Next, the tagging unit 11 identifies a cafe 311 corresponding to the stopover point 301, a hot spring 312 corresponding to the stopover point 302, and a convenience store 313 corresponding to the stopover point 303. Then, the tagging unit 11 associates the POI_IDs of the cafe 311, the hot spring 312, and the convenience store 313 with the movement data 300. As a result, the POI tags “coffee” and “single person” of the cafe 311, the POI tags “hot spring” and “single person” of the hot spring 312, and the POI tag “shopping” of the convenience store 313 are associated with the movement data 300. Since the movement data 300 includes the user ID of the user Ua, two user tags, "male" and "40s", are also associated with the movement data 300. Therefore, the movement data 300 associated with the POI tag indicates a combination of the POI tag and the user tag. The movement data 300 indicates a combination of the user tag and the POI tag of a cafe 311, a combination of the user tag and the POI tag of a hot spring 312, and a combination of the user tag and the POI tag of a convenience store 313.

[0045] (User Analysis) 11 is a flow chart showing an example of a user analysis as process flow S2, which is executed after the POI tags are associated with the travel data 230.

[0046] In step S21, the analysis unit 12 selects one user to be processed. For example, the analysis unit 12 refers to the movement history database 23 and selects one user ID.

[0047] In step S22, the analysis unit 12 acquires the user's movement data 230 associated with the POI tag. The analysis unit 12 reads out from the movement history database 23 a record group of the movement data 230 including the selected user ID and POI_ID.

[0048] In step S23, the analysis unit 12 counts the POI tags associated with the travel data 230. For example, the analysis unit 12 reads out the POI data 213 corresponding to the POI_ID of the read out travel data 230, and counts the number of occurrences of at least one POI tag included in the POI data 213. Then, the analysis unit 12 identifies POI tags that appear relatively frequently. For example, the analysis unit 12 may arrange the individual POI tags in descending order of appearance number, and identify the top n POI tags.

[0049] In step S24, the analysis unit 12 outputs the counting result. For example, the counting result indicates the identified POI tag (for example, "single diners", "family", etc.). The analysis unit 12 may display the counting result on a given display device, or may transmit the counting result to another computer or computer system. Alternatively, the analysis unit 12 may register the counting result in the corresponding user data 220 in the user database 22. For example, the analysis unit 12 may register the counting result in a user attribute (user tag) field of the user data 220. The counting result set as a user tag can be said to be information indicating the tendency of the user to visit POIs (for example, "frequently visits stores for single diners", "frequently visits stores for families", etc.). Alternatively, the analysis unit 12 may identify a user type based on the counting result (for example, at least one POI tag) and register the user type in the user data 220. If a large number of POI tags are identified by the analysis and it is not possible to narrow down the POI tags to one, the counting result indicating the classification "other" may be output.

[0050] As shown in step S25, the analysis unit 12 executes the processes of steps S21 to S24 for all users to be processed.

[0051] (POI analysis) 12 is a flow chart showing an example of POI analysis as process flow S3, which is performed after POI tags are associated with the travel data 230.

[0052] In step S31, the analysis unit 12 selects one POI to be processed. For example, the analysis unit 12 refers to the movement history database 23 and selects one POI_ID.

[0053] In step S32, the analysis unit 12 acquires the movement data 230 associated with the selected POI. The analysis unit 12 reads out from the movement history database 23 a group of records of the movement data 230 including the selected POI_ID.

[0054] In step S33, the analysis unit 12 counts the user tags associated with the movement data 230. For example, the analysis unit 12 reads out the user data 220 corresponding to the user ID of the read out movement data 230, and counts the number of occurrences of at least one user tag included in the user data 220. Then, the analysis unit 12 identifies user tags that appear relatively frequently. For example, the analysis unit 12 may arrange the individual user tags in descending order of the number of occurrences and identify the top m user tags.

[0055] In step S34, the analysis unit 12 outputs the counting result. For example, the counting result indicates the specified user tag. The analysis unit 12 may display the counting result on a given display device, or may transmit the counting result to another computer or computer system. Alternatively, the analysis unit 12 may register the counting result in the corresponding POI data 213 in the map database 21. For example, the analysis unit 12 may register the counting result in the POI attribute (POI tag) field of the POI data 213. The counting result set as a POI tag (for example, "40s", "male") can be said to be information indicating the tendency of users visiting the POI (for example, "stores frequently visited by men in their 40s").

[0056] As shown in step S35, the analysis unit 12 executes the processes of steps S31 to S34 for all POIs to be processed.

[0057] (Recommendation of visiting order) FIG. 13 is a flowchart showing an example of a visiting order recommendation to a target user as a processing flow S4. This processing is executed after the user type of the user is set. As described above, in one example, the user type is set based on at least one POI. In this case, the visiting order recommendation is executed after analyzing the movement data 230 associated with the POI tag. In this embodiment, an example is shown in which a user type is identified and a visiting order according to the user type is recommended, but this is not limiting, and a visiting order that is not bound to the user type, such as a "popular route," may be recommended.

[0058] In step S41, the recommendation unit 13 receives a recommendation request from the user terminal 30 of the target user. The user terminal 30 may transmit the recommendation request in response to an operation of the target user, or may transmit the recommendation request automatically without accepting the user operation. The recommendation request is a data signal for requesting a recommendation of a visiting order. The request signal includes the user ID of the target user and reference location information for identifying a reference POI. The reference location information may be represented by a POI_ID or may be represented by the geographical location of the user terminal 30.

[0059] In step S42, the recommendation unit 13 identifies the user type of the target user. The recommendation unit 13 refers to the user database 22 to identify the user type corresponding to the user ID included in the recommendation request.

[0060] In step S43, the recommendation unit 13 identifies a reference POI. When the reference location information is represented by a POI_ID, the recommendation unit 13 identifies the POI indicated by the POI_ID as the reference POI. When the reference location information is represented by the geographical position of the user terminal 30, the recommendation unit 13 refers to the POI data 213 in the map database 21 and identifies the POI having the facility coordinates or representative coordinates closest to the geographical position as the reference POI.

[0061] In step S44, the recommendation unit 13 acquires a visiting order corresponding to the identified user type and reference POI. The recommendation unit 13 reads a record corresponding to the combination of the user type and reference POI from the visit candidate database 24, and acquires the visiting order indicated by the record.

[0062] In step S45, the recommendation unit 13 transmits the visit order to the user terminal 30 of the target user. The user terminal 30 displays the visit order on a display device, so that the target user can know the visit order that suits his or her tendency.

[0063] In step S46, the recommendation unit 13 registers a new record of the visit history data 250 corresponding to the visit order in the visit history database 25. The recommendation unit 13 generates a new record of the visit history data 250 using a new recommendation ID, the user ID of the target user, and the POI_ID of at least one visited POI indicated by the visit order. In one example, the recommendation unit 13 sets the visit flag in the new record to "0", which indicates that the target user did not stop by the visited POI.

[0064] As shown as step S47, the recommendation unit 13 may further execute route guidance according to the visiting order. In one example, the recommendation unit 13 receives a guidance request from the user terminal 30 of the target user. The guidance request is a data signal for requesting route guidance according to the visiting order. In response to the guidance request, the recommendation unit 13 refers to the map database 21 to determine a route corresponding to the visiting order, and transmits route information indicating the route to the user terminal 30. The user terminal 30 displays the route information on a display device, whereby the target user can visit at least one visiting destination presented by the recommendation unit 13 in the presented order.

[0065] FIG. 14 is a diagram showing the concept of visiting order recommendation. In this example, the reference POI is a hotel 401, and visiting order candidates are visiting orders 411, 412, and 413. The visiting order 411 corresponds to a user type Ta that "likes eating out" and indicates that the user stops at a restaurant 402 and a drugstore 403 in this order. The visiting order 412 corresponds to a user type Ta that "likes running" and indicates that the user stops at a convenience store 404. The visiting order 413 corresponds to a user type Tc that "likes reading" and indicates that the user stops at a bookstore 405 and a cafe 406 in this order. For example, when a target user Ub corresponds to the user type Ta, the recommendation unit 13 presents the visiting order 411 to the target user Ub. As described above, the recommendation unit 13 may further execute route guidance according to the visiting order. For example, as shown in FIG. 14, the recommendation unit 13 may guide the target user along a route in which a reference POI (hotel 401) is the start point and end point, and each destination is a stopover point.

[0066] As shown as step S48, the recommendation unit 13 may update the visit flag of the corresponding record in the visit history data 250 based on the actual movement route of the target user for which the visiting order has been acquired. In one example, the recommendation unit 13 receives movement data from the user terminal 30 of the target user, and compares the location information indicated by the movement data with the representative coordinates of each visited POI indicated by the POI data 213 in the map database 21. Based on this comparison, the recommendation unit 13 estimates whether the target user has stopped at each visited POI indicated in the corresponding visit history data 250. In one example, for a visited POI that is estimated to have been visited by the target user, the recommendation unit 13 updates the visit flag corresponding to the visited POI to "1".

[0067] (Charges to POI administrators) 15 is a flowchart showing an example of charging a POI manager as a process flow S5. This process is executed after the visiting order is presented to at least one user. For example, the process flow S5 may be executed by a periodic batch process.

[0068] In step S51, the accounting unit 14 selects one POI to be processed. For example, the analysis unit 12 refers to the POI data 213 and selects one POI_ID.

[0069] In step S52, the accounting unit 14 acquires the visit history data 250 corresponding to the POI. The accounting unit 14 reads from the visit history database 25 the record of the visit history data 250 in which the selected POI_ID is set as visited destination information.

[0070] In step S53, the billing unit 14 counts the number of visitors to the selected POI based on the visit history data 250. In one example, the billing unit 14 may count the number of records in which the visit flag corresponding to the selected POI_ID is "1" and identify the number of records as the number of visitors. In this case, the number of visitors is the total number of people. Alternatively, the billing unit 14 may further refer to the user ID of each record in which the visit flag corresponding to the POI_ID is "1" and identify the actual number of people who visited the POI as the number of visitors.

[0071] In step S54, the charging unit 14 performs charging for the selected POI based on the number of visitors. In one example, the charging unit 14 calculates a charging amount based on the number of visitors, and transmits charging data indicating the charging amount to the facility terminal 40. This charging data is electronic data for charging for the POIs visited by the user who has acquired the advertising information (visiting order) based on the POI tag. The facility terminal 40 receives the charging data and displays the charging amount. Furthermore, the charging unit 14 registers the charging data in a given database. Then, a given financial system performs charging for the POI based on the charging data.

[0072] As shown in step S55, the accounting unit 14 executes the processes of steps S51 to S54 for all POIs to be processed.

[0073] [program] The program for causing the computer 110 to function as the server 10 includes program code for implementing each functional module of the server 10. The program may be provided in a state in which it is permanently recorded on a non-transitory recording medium such as a CD-ROM, a DVD-ROM, or a semiconductor memory. Alternatively, the program may be provided via a communication network as a data signal superimposed on a carrier wave. The provided program is stored in the storage 103. The processor 101 cooperates with the memory 102 to execute the program, thereby implementing the corresponding functional module.

[0074] [effect] As described above, a computer system according to an aspect of the present disclosure includes a processor. The processor associates at least one POI tag with travel data indicating a user's travel route based on map data indicating a correspondence between a geographical position of a POI and a POI tag indicating an attribute of the POI.

[0075] In this aspect, the attributes of the POIs are associated with the user's movement data. The movement history processed in this manner can be used for analysis of the user or the POIs. Thus, the utilization of the user's movement history can be realized.

[0076] In the computer system according to another aspect, the processor may identify a place where the user continues to stay for a given time range or more based on the movement data, identify a POI corresponding to the identified place, and associate a POI tag corresponding to the identified POI with the movement data. By taking into account the user's stay time, a POI tag that is estimated to be meaningful can be associated with the movement data.

[0077] In the computer system according to another aspect, the processor may associate at least one POI tag with the movement data of each of the users, and analyze the users or POIs based on the movement data associated with the at least one POI tag. In this case, a series of processes from tagging the movement data to analysis based on the processed movement data can be realized.

[0078] A computer system according to an aspect of the present disclosure includes a processor that presents a visiting order from a reference POI corresponding to a target user to the target user based on a user type indicating a classification of the user and visiting candidate data indicating a correspondence between the visiting order from a reference POI to at least one visiting POI.

[0079] In this aspect, a visiting sequence from a reference POI that matches the user type of the target user is presented to the target user. Therefore, it is possible to introduce to the target user visiting destinations and visiting sequences that are considered desirable for the target user.

[0080] In the computer system according to another aspect, the processor may identify a reference POI based on a geographical location of a user terminal of the target user. Since a location where the target user is estimated to be located is identified as the reference POI, a visiting sequence from the current location can be presented to the target user.

[0081] In a computer system according to another aspect, a processor may associate at least one POI tag with movement data indicating a movement route of a target user based on map data indicating a correspondence between a geographical position of a POI and a POI tag indicating an attribute of the POI, identify a user type of the target user based on the at least one POI tag associated with the movement data, and present to the target user a visiting order from a reference POI corresponding to the identified user type. In this case, the user type of the target user is identified based on the attributes of the POI visited by the target user, and a visiting order corresponding to the user type is presented to the target user. Therefore, it is possible to provide visiting destinations and visiting orders that match the behavioral tendencies of the target user.

[0082] A computer system according to an aspect of the present disclosure includes a processor. The processor generates billing data for charging a user for the POI visited based on map data indicating the correspondence between the geographical location of the POI and a POI tag indicating an attribute of the POI, and movement data indicating the movement route of the user who acquired the advertisement information based on the POI tag. In this case, it can be said that the POI tag and the advertisement information attracted the user to the POI. In this aspect, a fee corresponding to the contribution can be obtained from the POI.

[0083] [Variations] The present disclosure has been described in detail above based on the embodiments. However, the present disclosure is not limited to the above embodiments. The present disclosure can be modified in various ways without departing from the spirit and scope of the present disclosure.

[0084] The information management system 1 (server 10) may not include a tagging unit 11, and therefore may not execute the process flow S1. The information management system 1 (server 10) may not include an analysis unit 12, and therefore may not execute the process flows S2 and S3. The information management system 1 (server 10) may not include a recommendation unit 13, and therefore may not execute the process flow S4. Alternatively, the information management system 1 (server 10) may include the recommendation unit 13 and may further include a stop unit that temporarily stops the recommendation function upon a request from the user terminal 30. The information management system 1 (server 10) may not include a billing unit 14, and therefore may not execute the process flow S5.

[0085] For purposes of this disclosure, a first computer sending data or information "to" a second computer means that the first computer sends the data or information to the second computer either directly or through at least one communications device (i.e., indirectly).

[0086] In this disclosure, the expression "at least one processor executes a first process, executes a second process, ... executes an nth process" or a corresponding expression indicates a concept including a case where the executing entity (i.e., the processor) of n processes from the first process to the nth process changes midway. In other words, this expression indicates a concept including both a case where all n processes are executed by the same processor and a case where the processor changes among the n processes according to an arbitrary policy.

[0087] When comparing the magnitude relationship of two numerical values ​​in a computer system, either of the two criteria "greater than or equal to" and "greater than" may be used, or either of the two criteria "less than or equal to" and "less than" may be used. The selection of such criteria does not change the technical meaning of the process of comparing the magnitude relationship of two numerical values.

[0088] The processing procedure of the method executed by at least one processor is not limited to the example in the above embodiment. For example, some of the steps (processing) described above may be omitted, or each step may be executed in a different order. In addition, any two or more of the steps described above may be combined, or some of the steps may be modified or deleted. Alternatively, other steps may be executed in addition to each of the steps described above.

[0089] The aspects described in all or part of the above embodiments solve any one of the following problems: control of movement paths or movement history, improving processing speed, improving processing accuracy, improving usability, improving functions using data or providing appropriate functions, other improving functions or providing appropriate functions, reducing the capacity of data and / or programs, miniaturizing devices and / or systems, providing appropriate data, programs, recording media, devices and / or systems, and optimizing the production and manufacturing of data, programs, recording media, devices and / or systems, such as reducing the production and manufacturing costs of data, programs, devices or systems, facilitating production and manufacturing, and shortening production and manufacturing times. [Explanation of symbols]

[0090] 1...information management system, 10...server, 11...tagging unit, 12...analysis unit, 13...recommendation unit, 14...billing unit, 20...database group, 21...map database, 22...user database, 23...movement history database, 24...visit candidate database, 25...visit history database, 30...user terminal, 40...facility terminal, 210...map data, 211...node data, 212...link data, 213...POI data, 220...user data, 230...movement data, 240...visit candidate data, 250...visit history data, 411-413...visit order.

Claims

1. A processor is provided. The processor associates at least one POI tag with movement data indicating a movement route of the user based on map data indicating a correspondence between a geographical position of a POI and a POI tag indicating an attribute of the POI; The processor, based on the POI tag associated with the movement data of the user to be analyzed, a user tag indicating an attribute of the user is set, and based on the set user tag of the user of the movement data associated with the POI to be analyzed, the POI tag of the POI is set; The processor, identifying a user type indicative of a classification of a target user based on the at least one POI tag associated with the movement data; presenting to the target user the visiting sequence from the reference POI corresponding to the specified user type, based on visiting candidate data indicating a correspondence between the user type and a visiting sequence from a reference POI to at least one visiting destination POI; Computer system.

2. The processor, generating visit history data including visiting POIs estimated to have been visited by the target user based on an actual movement route of the target user who has acquired the presented visiting order; counting the number of visitors to the visited POI based on the visit history data, calculating a charge according to the counted number of visitors, and charging the administrator of the visited POI.

2. The computer system of claim 1.

3. A computer comprising: Associating at least one POI tag with movement data indicating a user's movement route based on map data indicating a correspondence between a geographical position of a POI and a POI tag indicating an attribute of the POI; based on the POI tag associated with the movement data of the user to be analyzed, a user tag indicating an attribute of the user is set, and based on the set user tag of the user of the movement data associated with the POI to be analyzed, the POI tag of the POI is set; identifying a user type indicative of a classification of a target user based on the at least one POI tag associated with the movement data; presenting to the target user the visiting sequence from the reference POI corresponding to the specified user type, based on visiting candidate data indicating a correspondence between the user type and a visiting sequence from a reference POI to at least one visiting destination POI; The processing method that performs the action.

4. A computer comprising: generating visit history data including visiting POIs estimated to have been visited by the target user based on an actual movement route of the target user who has acquired the presented visiting order; counting the number of visitors to the visited POI based on the visit history data, calculating a charge according to the counted number of visitors, and charging the administrator of the visited POI. The method of claim 3 further comprising the step of:

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