Information processing unit, information processing method and information processing program

Abstract

To provide features of various regions for a user.SOLUTION: An information processing unit comprises: an acquisition unit which acquires user information related to a user who have visited at least one of a plurality of places included in a predetermined region; an estimation unit which uses a generative model learnt to output an answer to an input question to extract a featured place included in the predetermined region as an object region from the user information acquired by the acquisition unit, and estimates characteristics of the extracted object region; and a display unit which displays the characteristics of the object region estimated by the estimation unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] Conventionally, there are known techniques for formulating sales strategies for stores, etc. For example, Patent Document 1 proposes a technique for analyzing a trade area specified from a client device. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2016-170778 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the above-mentioned conventional technology only analyzes the trade area, and therefore, for example, it may not be said that it provides information for considering sales strategies for users in various regions, taking into account the characteristic information of the region.

[0005] The present application has been made in view of the above, and aims to provide an information processing device, an information processing method, and an information processing program that can provide users with the characteristics of various regions. [Means for solving the problem]

[0006] The information processing device of the present application is characterized by comprising an acquisition unit that acquires user information about users who have visited at least one of a plurality of locations included in a specified area, an estimation unit that extracts characteristic locations included in the specified area as target areas from the user information acquired by the acquisition unit using a generative model that has been trained to output answers to input questions, and estimates the characteristics of the extracted target area, and a display unit that displays the characteristics of the target area estimated by the estimation unit. [Effects of the Invention]

[0007] According to one aspect of the embodiment, it is possible to provide a summary of places based on information about pre-set characteristics of the places. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a system according to the first embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of the overall configuration of a system according to the first embodiment. [Figure 3] FIG. 3 is a block diagram illustrating an example of a functional configuration of the information processing device according to the first embodiment. [Figure 4] FIG. 4 is a diagram illustrating the user information DB. [Figure 5] FIG. 5 is a diagram illustrating the facility information DB. [Figure 6] FIG. 6 is a diagram illustrating the prompt DB. [Figure 7] FIG. 7 is a diagram illustrating an example of a prompt used by the estimation unit according to the first embodiment. [Figure 8] FIG. 8 is a diagram illustrating an example of characteristics of a target area displayed on a user terminal device by a display unit according to the first embodiment. [Figure 9] FIG. 9 is a flowchart showing an example of a processing flow in the information processing device according to the first embodiment. [Figure 10] FIG. 10 is a block diagram illustrating an example of a functional configuration of an information processing device according to the second embodiment. [Figure 11] FIG. 11 is a diagram illustrating the user information DB. [Figure 12] FIG. 12 is a diagram illustrating the facility information DB. [Figure 13] FIG. 13 is a diagram illustrating an example of a prompt used by the estimation unit according to the second embodiment. [Figure 14] FIG. 14 is a diagram illustrating an example of characteristics of a target area displayed on a user terminal device by a display unit according to the second embodiment. [Figure 15] FIG. 15 is a diagram illustrating a hardware configuration. DETAILED DESCRIPTION OF THE INVENTION

[0009] The present invention will be described through the following embodiments, but the following embodiments do not limit the scope of the invention as claimed. In addition, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0010] <Embodiment 1> (Overall composition) An information processing device according to embodiment 1 will be described. Fig. 1 is a diagram showing an example of the configuration of a system according to embodiment 1. As shown in Fig. 1, the system according to embodiment 1 includes an information processing device 10, a user terminal device 20, and a network N. Note that the number of information processing devices 10 and user terminal devices 20 is not limited to that shown in Fig. 1.

[0011] The information processing device 10 is a device that provides various online services to service users in cooperation with the user terminal device 20. The information processing device 10 is an example of a computer that acquires input data, generates answers using a model, and outputs and executes various information to the user terminal device 20.

[0012] The user terminal device 20 is an example of a terminal device used by a user. For example, the user terminal device 20 is a mobile phone, a smartphone, a tablet terminal, a personal computer, etc. The user terminal device 20 also has an audio input device (e.g., a microphone) that accepts audio input, and an audio output device (e.g., a speaker) that outputs audio.

[0013] (Processing executed by information processing device 10) Here, the processing performed by the information processing device 10 will be described. Fig. 2 is a diagram showing an example of the overall configuration of a system according to the first embodiment. As shown in Fig. 2, the information processing device 10 acquires various data input from a user terminal device 20. For example, the data acquired by the information processing device 10 includes user information, location information including latitude and longitude, information on facilities visited by the user, etc., but is not limited to such examples.

[0014] Next, the information processing device 10 inputs the acquired data into a generative model trained to output answers to input questions, and estimates the characteristics of the target area. For example, the information processing device 10 inputs a prompt to the generative model, including data on users who have visited at least one of multiple locations included in a predetermined area as the target area and an instruction sentence in natural language instructing the generative model to estimate a characteristic location included in the predetermined area from the data, and estimates the characteristic location included in the predetermined area as the target area. Furthermore, the information processing device 10 creates and estimates a summary of the estimated target area using image data and a message. For example, the information processing device 10 estimates map data as image data and estimates a bulleted sentence about the characteristics of the target area as a message. Furthermore, the information processing device 10 performs mapping on the estimated map data and distinguishes the mapping by shape and color. The information processing device 10 then displays the estimated image data and message on the screen of the user terminal device 20.

[0015] That is, the information processing device 10 reads data related to user information, data related to location information, and various data related to facility information, estimates the characteristics of the target area using a generative model, and displays the estimation results on the user terminal device 20. As a result, the information processing device 10 can use the attributes, search behavior, concerns, characteristic services, etc. of users who visit a certain location to visualize ranges and characteristics that have certain meanings on a map using a generative model.

[0016] (Functional configuration of information processing device 10) Next, a description will be given of the functional configuration of the information processing device 10. Fig. 3 is a block diagram showing an example of the functional configuration of the information processing device 10 according to embodiment 1. As shown in Fig. 3, the information processing device 10 has a communication unit 11, a control unit 12, and a storage unit 13.

[0017] The communication unit 11 is realized by, for example, a communication module or a network interface card (NIC). The communication unit 11 is connected to a network N by wire or wirelessly, and transmits and receives information to and from various other devices. For example, the communication unit 11 transmits and receives information between the information processing device 10 and the user terminal device 20 via the network N.

[0018] The storage unit 13 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 13 has a user information DB 13a, a location information DB 13b, a facility information DB 13c, and a prompt DB 13d.

[0019] The user information DB 13a stores data on users who have visited a certain location. FIG. 4 is a diagram illustrating the user information DB. As shown in FIG. 4, the user information DB 13a stores the following items: "user name," "attribute," "route," and "search behavior." Here, the stored "user name" is information for identifying the visiting user. "Attribute" further includes items such as "gender, age, and occupation," and is information for identifying the attributes of the user. "Route" is information for identifying the route taken by the user. "Search behavior" is information for identifying the location searched for and headed to using the terminal device used by the user.

[0020] Using the example of FIG. 4, the user information DB 13a stores "User A, male, in his 30s, working professional, route C, business district" and "User B, female, in his 40s, housewife, route D, residential area" as "user name, attributes (gender, age, occupation), route, search behavior." That is, the user information DB 13a stores information that "User A," a "working professional" with a gender of "male" and an age of "30s," took "route C" to head to the "business district." The user information DB 13a also stores information that "User B," a "housewife" with a gender of "female" and an age of "40s," took "route D" to head to the "residential area."

[0021] The user information DB 13a also stores information indicating user attributes, such as demographic attributes and psychographic attributes. Demographic attributes include, for example, gender, age, place of residence, place of work, and occupation, while psychographic attributes include interests such as travel, clothing, cars, and religion, lifestyle, and thoughts and tendencies.

[0022] The location information DB 13b stores geographical information, such as, but not limited to, information indicating topography, information indicating latitude and longitude, information indicating routes, information indicating routes of public institutions, information indicating traffic regulations and signs, information on news articles, information on disasters, information on facilities and stores, and weather information.

[0023] The facility information DB 13c stores data related to facilities. FIG. 5 is a diagram illustrating the facility information DB. As shown in FIG. 5, the facility information DB 13c stores the following items: "facility ID," "type," "location information," "stay length," "business hours," and "crowding status." Here, the stored "facility ID" indicates identification information for identifying a facility. "Type" is information for specifying the type of facility. "Location information" is information for specifying the location (address, etc.) of the facility. "stay length" is information for specifying the business hours of the facility. "Crowding status" indicates the congestion status of the facility, and is information for specifying, for example, a time period when the degree of congestion is equal to or greater than a predetermined threshold.

[0024] Using the example of FIG. 5, the facility information DB13c stores "SID#1, Office 1, City Center, 6 hours, 24 hours, Crowded" and "SID#2, Residential Area 2, Suburban, 2 hours, None, Not Crowded" as "facility ID, type, location information, stay time, business hours, congestion status." That is, the facility information DB13c stores information that the facility ID is "SID#1," the facility type is "Office 1," the location is "City Center," the stay time is "6 hours," the facility business hours are "24 hours," and the congestion status is "Crowded." The facility information DB13c also stores information that the facility ID is "SID#2," the facility type is "Residential Area 2," the location is "Suburban," the stay time is "2 hours," the facility business hours are "None," and the congestion status is "Not Crowded."

[0025] The prompt DB 13d stores information related to prompts. FIG. 6 is a diagram illustrating the prompt DB. The information stored in the prompt DB 13d is used, for example, to generate questions in the pre-processing according to the first embodiment (generate questions for learning a generative model) and to change prompts according to the first embodiment. As shown in FIG. 6, the prompt DB 13d has items such as a "prompt ID" and "prompt information." Here, the stored "prompt ID" is identification information for identifying a prompt. The "prompt information" is information included in a prompt.

[0026] Explaining using the example of FIG. 6, the prompt DB 13d stores "P1, prompt information #1" and "P2, prompt information #2" as "prompt ID, prompt information." That is, the prompt DB 13d stores information in which the prompt ID is "P1" and the information included in the prompt is "prompt information #1." The prompt DB 13d also stores information in which the prompt ID is "P2" and the information included in the prompt is "prompt information #2."

[0027] Next, returning to Fig. 3, the control unit 12 of the information processing device 10 will be described. The control unit 12 has an internal memory for storing programs that define various processing procedures and required data, and executes various processes using these. Here, the control unit 12 is, for example, an electronic circuit such as a CPU (Central Processing Unit) or an MPU (Micro Processing Unit), or an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control unit 12 has an acquisition unit 12a, an estimation unit 12b, and a display unit 12c.

[0028] The acquisition unit 12a acquires user information about a user who has visited at least one of a plurality of places included in a predetermined area. For example, the acquisition unit 12a acquires, as the user information, user information about a user who has traveled from a predetermined departure point to a predetermined destination via a predetermined route. Furthermore, for example, the acquisition unit 12a acquires characteristic information indicating the characteristics of each place included in the predetermined area.

[0029] The acquisition unit 12a stores the acquired information in the user information DB 13a, the location information DB 13b, and the facility information DB 13c.

[0030] The estimation unit 12b uses a generative model trained to output answers to input questions to extract characteristic locations included in a predetermined area as a target area from the user information acquired by the acquisition unit 12a, and estimates characteristics of the extracted target area. Furthermore, the estimation unit 12b extracts locations included in the predetermined area that share common user information as a target area, and estimates characteristics of the extracted target area based on user information about users who visited the target area. Furthermore, for example, the estimation unit 12b extracts the target area based on characteristic information.

[0031] For example, the estimation unit 12b reads out "User A, male, in his 30s, working professional, route C, business district" stored in the user information DB 13a and estimates that the target area visited by user A is a business district. Also, for example, the estimation unit 12b reads out "User B, female, in his 40s, housewife, route D, residential district" stored in the user information DB 13a and estimates that the target area visited by user B is a residential district.

[0032] Furthermore, for example, the estimation unit 12b estimates the content of an explanation about a user who visited the target area as a characteristic of the target area.

[0033] For example, in the estimation process, the estimation unit 12b uses, as instruction information for instructing the estimation of the characteristics of a certain location, information for instructing the summarization of the estimation results, information for instructing the naming of the summary content, information for instructing the output of the title and the summary content, etc.

[0034] Here, a prompt used when estimating the characteristics of the target area will be described with reference to FIG. 7. FIG. 7 is a diagram showing an example of a prompt used by the estimation unit 12b according to the first embodiment. The estimation unit 12b inputs, for example, the prompt shown in FIG. 7 into a generative model, and estimates a title and a summary of the location in the generative model. The instruction information of the prompt shown in FIG. 7 includes output format information specifying how to output the title and the summary of the location, such as output format information "output the location, the title of the cluster, and a description of the cluster," "separate the three elements with "\t," and connect the latitude and longitude of the location with ","," and "separate the items with line breaks, and start each with "·."

[0035] Specifically, the generative model that executes the prompt shown in Figure 7 includes location information within a certain range, regional information about that location, and user data. The generative model executes the process of outputting an output format based on the steps and elements.

[0036] The area information is information included in the generative model. For example, the area information is facility information or store information based on latitude and longitude. Furthermore, the area information may use data from the location information DB 13b or the facility information DB 13c.

[0037] User data is information included in the generative model. For example, the user data is information indicating the user's movement direction linked to latitude and longitude. The user data is also information indicating the route, distance, and movement speed from the user's starting point to the destination. The user data is also information indicating the attributes of users who visit a certain place or location. The user data is also information on the user's search behavior. The user data may also use data from the user information DB 13a.

[0038] The steps executed by the generative model indicate the order and content of the processing to be executed. In the example in Figure 7, there are steps 1 to 3. Step 1 extracts the characteristics of each location from the area and facility information of the location, the movements and actions associated with users who visited the location, and data related to the user's interests. Step 2 groups locations with similar characteristics into one cluster as much as possible. Step 3 outputs the titles and descriptions of the locations and clusters.

[0039] The elements that the generative model executes indicate the conditions for information processing described in the steps. As shown in Figure 7, the elements maximize the number of clusters. <n>The condition for the element is that it must be an individual element. The condition also includes that the title and description of the element must be concise so that the differences from other characteristics are clear. The condition also includes that the element must not express anything other than the elements in the list.

[0040] The output format output by the generative model specifies the format of the data to be output. The output format specifies the output of the location, cluster title, and cluster description. The output format also specifies that the three elements are separated by "\t" and that the viewpoint's latitude and longitude are connected by a ",". The output format also specifies that the bulleted lists are separated by line breaks and each begins with a "·".

[0041] The display unit 12c displays the characteristics of the target area estimated by the estimation unit 12b. For example, the display unit 12c displays content linking the estimation result by the estimation unit 12b with the target area. Furthermore, for example, the display unit 12c displays the characteristics of the target area estimated by the estimation unit 12b on the user terminal device 20 as map data and a summary of a message.

[0042] Here, the characteristics of the displayed target area will be described with reference to Fig. 8. Fig. 8 is a diagram showing an example of the characteristics of the target area displayed on the user terminal device 20 by the display unit 12c according to the first embodiment. In Fig. 8, the description will be given using summary content 41 and summary content 42.

[0043] Summary content 41 is information about the business district. Display section 12c displays information as summary content, such as that 30 companies have offices there, most of the residents are in their 30s and 40s, and the population density is high between 7:00 and 9:00 in the morning. Summary content 42 is information about a residential area. Display section 12c displays information as summary content, such as that 20 houses are there, many of the residents are parents and children, and the population density is high between 4:00 and 6:00 in the evening.

[0044] As described above, the information processing device 10 visualizes the characteristics of a certain place on a map using a generative model. This allows the information processing device 10 to estimate and provide the characteristics of the place as summary content to the user.

[0045] (Processing procedure of embodiment 1) Next, an example of a processing procedure performed by the information processing device 10 according to the first embodiment will be described with reference to Fig. 9. Fig. 9 is a flowchart showing an example of a processing flow in the information processing device 10 according to the first embodiment.

[0046] 9, the information processing device 10 acquires information about users who have visited a predetermined area from the user terminal device 20 (step S101). Next, the information processing device 10 inputs the acquired information into a pre-trained generative model, extracts characteristic locations included in the predetermined area as a target area, and estimates characteristics of the extracted target area (step S102). Then, the information processing device 10 displays the estimated characteristics of the target area as a summary of image data and a message (step S103), and ends the process.

[0047] (Effects of the First Embodiment) In embodiment 1, the information processing device 10 acquires information about users who have visited a specified area from the user terminal device 20, inputs the acquired information into a pre-trained generative model, and displays a message with the characteristics of the target area attached to image data, thereby providing a summary of the location based on information about the characteristics of the location that has been set in advance.

[0048] For example, the information processing device 10 can use the estimated characteristics of the target area to improve road traffic by displaying image data and messages as summary content.

[0049] Furthermore, for example, the information processing device 10 can use the estimated characteristics of the target area in planning a store opening by displaying image data and a message as a summary of the contents.

[0050] <Embodiment 2> (Summary of Embodiment 2) In the first embodiment, an example was described in which image data and messages estimated by a generative model were displayed as map information. However, the disclosed information processing device 10 can also visualize people flow between certain points on a map as a summary of points. Therefore, in the second embodiment, an example is described in which characteristics on a route are input into a generative model and image data and messages are displayed. Note that the system configuration of the second embodiment is the same as that of FIG. 2 described in the first embodiment, and therefore a detailed description thereof will be omitted.

[0051] (Functional configuration of information processing device 10) Next, the functional configuration of the second embodiment will be described. Fig. 10 is a block diagram showing an example of the functional configuration of the information processing device 10 according to the second embodiment. The information processing device 10 has the same configuration as the communication unit 11 and the location information DB 13b and the prompt DB 13d of the storage unit 13 described in Fig. 3, and therefore detailed description thereof will be omitted. Here, the user information DB 13a, facility information DB 13c, and route statistics DB 13e of the control unit 12 and the storage unit 13, which are different from those of the first embodiment, will be described.

[0052] The user information DB 13a stores data on users who have visited between certain points. FIG. 11 is a diagram illustrating the user information DB. As shown in FIG. 11, the user information DB 13a stores the items of "user name," "attribute," and "search behavior." Here, the stored "user name" is information for identifying the visiting user. The "attribute" further includes items such as "gender, age, and occupation," and is information for identifying the attributes of the user. The "search behavior" is information for identifying the location that the user searched for and headed to using the terminal device.

[0053] Using the example of FIG. 11, the user information DB 13a stores "User E, male, late teens, student, near the library" and "User B, female, early twenties, student, convenience store" as "user name, attributes (gender, age, occupation), search behavior." That is, the user information DB 13a stores information that "User E," a "student" whose gender is "male" and whose age is "late teens," headed to "near the library." The user information DB 13a also stores information that "User B," a "student" whose gender is "female" and whose age is "early twenties," headed to "a convenience store."

[0054] The facility information DB 13c stores data related to facilities. FIG. 12 is a diagram illustrating the facility information DB. As shown in FIG. 12, the facility information DB 13c stores the following items: "facility ID," "type," "location information," "stay length," "business hours," and "crowding status." Here, the stored "facility ID" indicates identification information for identifying a facility. "Type" is information for specifying the type of facility. "Location information" is information for specifying the location (address, etc.) of the facility. "stay length" is information for specifying the business hours of the facility. "Crowding status" indicates the congestion status of the facility, and is information for specifying, for example, a time period when the degree of congestion is equal to or greater than a predetermined threshold.

[0055] Using the example of FIG. 12, the facility information DB13c stores "SID#3, Library 1, Suburban, 2 hours, 9 hours, not crowded" and "SID#4, Convenience Store 2, Suburban, 15 minutes, 24 hours, crowded" as "facility ID, type, location information, stay time, business hours, congestion status." That is, the facility information DB13c stores information that the facility ID is "SID#3," the facility type is "Library 1," the location is "Suburban," the stay time is "2 hours," the facility business hours are "9 hours," and the congestion status is "not crowded." The facility information DB13c also stores information that the facility ID is "SID#4," the facility type is "Convenience Store 2," the location is "Suburban," the stay time is "15 minutes," the facility business hours are "24 hours," and the congestion status is "crowded."

[0056] The route statistics DB 13e accumulates statistical information on people flow. The route statistics DB 13e may also store statistical information based on the information stored in the user information DB 13a, location information DB 13b, and facility information DB 13c. For example, the route statistics DB 13e may store statistical information such as the location (position) of users for each time period and the percentage of users with each attribute who are at that location at that time, or the search keywords of users for each time period and the percentage of users with each attribute who performed the search at that time.

[0057] The acquisition unit 12a acquires, as the user information, user information relating to a user who traveled from a predetermined departure point to a predetermined destination via a predetermined route.

[0058] The estimation unit 12b uses the user information acquired from the acquisition unit 12a to extract characteristic locations on a predetermined route as a target area from the user information, and estimates the characteristics of the extracted target area. For example, the estimation unit 12b acquires data on people flow statistical information stored in the route statistics DB 13e by the acquisition unit 12a, and estimates image data and messages using a generative model.

[0059] For example, the estimation unit 12b reads out "User E, male, late teens, student, around the library" stored in the user information DB 13a and estimates that the target area visited by user E is around the library. Also, for example, the estimation unit 12b reads out "User F, female, early twenties, student, convenience store" stored in the user information DB 13a and estimates that the target area visited by user F is a convenience store.

[0060] Here, a prompt used when estimating the characteristics of the target area will be described with reference to FIG. 13. FIG. 13 is a diagram showing an example of a prompt used by the estimation unit 12b according to the second embodiment. The estimation unit 12b inputs, for example, the prompt shown in FIG. 13 into a generative model, and estimates a route title and a summary of the route in the generative model. The instruction information of the prompt shown in FIG. 13 includes output format information specifying how to display the route title and the summary of the route, such as output format information "output longitude, latitude, and location description," "separate the three elements with "\t," and for locations, connect the latitude and longitude with ","," and "separate items with line breaks, and start each with "·."

[0061] Specifically, the generative model that executes the prompt shown in Fig. 13 includes log data of a certain route and user data. The generative model executes a process of outputting an output format based on the steps and elements.

[0062] Although Figure 13 does not provide detailed descriptions of the steps executed by the generative model, as in Figure 7, the steps executed by the generative model indicate the order and content of the processing to be executed. For example, Figure 13 has steps 1 to 3. Step 1 extracts the characteristics of each route from the area and facility information of the location, the movements and actions associated with users who visited the location, and the user's interest data. Step 2 attempts to group similar characteristics into one cluster whenever possible. Step 3 outputs the titles and descriptions of the routes and clusters.

[0063] User data is information included in the generative model. For example, the user data is information indicating the user's movement direction linked to latitude and longitude. For example, the user data is information indicating the route, distance, and movement speed from the user's starting point to the destination. For example, the user data is information indicating the attributes of a user who visits a certain place or location. For example, the user data is information on the user's search behavior. For example, the user data may use data from the user information DB 13a.

[0064] The route data is information included in the generative model. For example, the route data is data of position information such as latitude and longitude. Alternatively, the route data may use data from the position information DB 13b.

[0065] The area information is information included in the generative model. For example, the area information is facility information based on latitude and longitude, or store information. The area information may also be obtained from the facility information DB 13c.

[0066] The elements executed by the generative model represent the conditions for information processing described in the steps. As shown in Figure 13, the elements extract characteristic points along each route from the surrounding conditions and user data of the users who traveled that route. For example, the elements include a condition that prioritizes and considers user attributes such as stores along the route, the user's travel speed and speed change, time spent at a location, and occupation when extracting the characteristics. For example, the elements include a condition that summarizes the characteristic elements of the extracted locations and assigns titles and descriptions. For example, the elements include a condition that only items listed in bullet points are expressed.

[0067] The output format output by the generative model specifies the format of the data to be output. The output format specifies the output of latitude, longitude, and a description of the location. The output format also specifies that the three elements are separated by "\t", and that the latitude and longitude of the location are connected by a ",". The output format also specifies that the bulleted list is separated by a line break, and that each begins with a "·".

[0068] The display unit 12c displays the map information including the image and message generated by the estimation unit 12b on the user terminal device 20. For example, the display unit 12c displays on the user terminal device 20 a summary of the route estimated by the estimation unit 12b.

[0069] Here, the characteristics of the displayed target area will be described with reference to Fig. 14. Fig. 14 is a diagram showing an example of the characteristics of the target area displayed on the user terminal device 20 by the display unit 12c according to the second embodiment. In Fig. 14, the description will be given using summary content 43 and summary content 44.

[0070] Summary content 43 is information about the area around the library. Display section 12c displays information as summary content, such as that students' walking speeds around the library have decreased, that students are researching reports, and that population density is high between 10:00 a.m. and 2:00 p.m. Furthermore, summary content 44 is information about convenience stores. Display section 12c displays information as summary content, such as that students are stopping by convenience stores to buy breakfast before going to school, and that population density is high between 7:00 a.m. and 9:00 a.m.

[0071] As described above, the information processing device 10 visualizes the characteristics of a route on a map using a generative model. This allows the information processing device 10 to generate and provide a summary of the characteristics of a location to the user.

[0072] (Effects of the second embodiment) In embodiment 2, the information processing device 10 acquires specified information from the user terminal device 20, inputs the acquired information into a pre-trained generative model, estimates and displays images and messages, and thereby provides a summary of the route based on information on the characteristics of pre-set locations.

[0073] For example, the information processing device 10 can grasp the behavior of a group of users living in the area based on the route summary content.

[0074] Furthermore, for example, the information processing device 10 can be used when considering the placement of advertisements such as OOH (Out Of Home) that a group of users see in their daily lives, based on the route summary content.

[0075] Furthermore, for example, the information processing device 10 can grasp the behavior of a group of users based on the route summary, and therefore can be used to improve road traffic.

[0076] Furthermore, for example, the information processing device 10 can grasp the behavior of a group of users based on the summary of the routes, and therefore can be used for store opening plans of companies and the like.

[0077] <Hardware configuration> The information processing device 100 according to the embodiment described above is realized, for example, by a computer 1000 configured as shown in Fig. 15. Fig. 15 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device 10. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, an HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

[0078] The CPU 1100 operates and controls each unit based on programs stored in the ROM 1300 or the HDD 1400. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, programs that depend on the hardware of the computer 1000, and the like.

[0079] The HDD 1400 stores programs executed by the CPU 1100, data used by these programs, etc. The communication interface 1500 acquires data from other devices via a predetermined communication network and sends it to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the predetermined communication network.

[0080] The CPU 1100 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse, via the input / output interface 1600. The CPU 1100 acquires data from the input devices via the input / output interface 1600. The CPU 1100 also outputs generated data to the output devices via the input / output interface 1600.

[0081] Media interface 1700 reads a program or data stored in recording medium 1800 and provides it to CPU 1100 via RAM 1200. CPU 1100 loads the program or data from recording medium 1800 onto RAM 1200 via media interface 1700 and executes the loaded program. Recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase Change Rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0082] For example, when the computer 1000 functions as the information processing device 10 according to the embodiment, the CPU 1100 of the computer 1000 executes programs loaded onto the RAM 1200, thereby realizing the functions of the control unit 12. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, the CPU 1100 may obtain these programs from another device via a predetermined communication network.

[0083] Furthermore, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using a known method. In addition, the information including the processing procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown in the drawings.

[0084] Furthermore, the components of each device shown in the figure are conceptual functional components and do not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

[0085] Furthermore, the above-described embodiments can be combined as appropriate within the scope of not causing any contradiction in the processing content.

[0086] Although some of the embodiments of the present application have been described in detail above with reference to the drawings, these are merely examples, and the present invention can be implemented in other forms that include the embodiments described in the Disclosure of the Invention section and that have been modified and improved in various ways based on the knowledge of those skilled in the art.

[0087] Furthermore, the above-mentioned "section, module, unit" can be read as "means" or "circuit," etc. For example, an acquisition unit can be read as an acquisition means or an acquisition circuit. [Explanation of symbols]

[0088] 10. Information processing equipment 11 Communications Department 12 Control Unit 12a Acquisition part 12b Estimation part 12c Display section 13a User Information DB 13b Location information DB 13c Facility Information DB 13d Prompt DB 13e Route Statistics DB 20 User terminal device N Network< / n>

Claims

1. an acquisition unit that acquires user information related to a user who has visited at least one of a plurality of places included in a predetermined area; an estimation unit that extracts, as a target area, a characteristic location included in the predetermined area from the user information acquired by the acquisition unit, using a generative model that has been trained to output an answer to an input question, and estimates characteristics of the extracted target area; a display unit that displays the characteristics of the target region estimated by the estimation unit; An information processing device comprising:

2. The estimation unit extracts, as the target area, locations that have the same user information among locations included in the predetermined area, and estimates characteristics of the extracted target area based on user information about users who have visited the target area.

2. The information processing apparatus according to claim 1, wherein:

3. the acquisition unit acquires, as the user information, user information related to a user who traveled from a predetermined departure point to a predetermined destination via a predetermined route; The estimation unit extracts characteristic locations on the predetermined route as target areas from the user information and estimates characteristics of the extracted target areas.

2. The information processing apparatus according to claim 1, wherein:

4. The acquisition unit further acquires characteristic information indicating characteristics of each location included in the predetermined area, The estimation unit further extracts the target region based on the characteristic information.

4. The information processing device according to claim 1, wherein the information processing device is a computer.

5. The information processing apparatus according to claim 1 , wherein the estimation unit estimates, as the characteristic of the target area, the content of an explanation about a user who has visited the area.

6. The information processing apparatus according to claim 1 , wherein the display unit displays content that associates the estimation result by the estimation unit with the target area.

7. an acquisition step of acquiring user information related to a user who has visited at least one of a plurality of places included in a predetermined area; an estimation step of extracting, as a target area, a characteristic location included in the predetermined area from the user information acquired in the acquisition step, using a generative model that has been trained to output an answer to an input question, and estimating characteristics of the extracted target area; a display step of displaying the characteristics of the target region estimated by the estimation step; An information processing method comprising:

8. an acquisition step of acquiring user information related to a user who has visited at least one of a plurality of places included in a predetermined area; an estimation step of extracting, as a target area, a characteristic location included in the predetermined area from the user information acquired by the acquisition step, using a generative model that has been trained to output an answer to an input question, and estimating characteristics of the extracted target area; a display step of displaying the characteristics of the target region estimated by the estimation step; An information processing program comprising:

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