JP7337123B2 - Information processing device, information processing method and information processing program - Google Patents

Description

The present invention relates to an information processing device, an information processing method, and an information processing program.

Each consumer's residential area identified as located within the target area by referring to information representing a cluster pre-assigned to the consumer's residential area among a plurality of clusters, which are multiple categories according to the attributes of the area. and create target area cluster information representing the identified cluster of consumers identified as located within the target area.

Japanese Patent No. 5313091

However, in the above-described conventional technology, clusters of residential areas of consumers are identified, and target area cluster information representing each residential cluster of consumers identified as being located within the target area is created. . For example, there are users who live in other areas but frequently visit a specific area and behave in a manner similar to that of residents of that area. Such users are familiar with the area and may migrate if appropriately proposed or recommended to migrate to the area.

The present application was made in view of the above, and aims to propose migration to the area from the similarity of behavior with the residents of the area other than the residential area to the user.

The information processing apparatus according to the present application includes an acquisition unit that collects information of an unspecified number of users, each user based on the information of the unspecified number of users, and residents of areas other than the residence of each user An estimation unit that estimates users who are likely to migrate to the area based on the similarity of behavior with the above, and proposes migration to the area for users who are likely to migrate to the area. and a providing unit for

According to one aspect of the embodiment, it is possible to suggest migration to an area other than the area of residence based on the similarity of behavior with residents of the area other than the area of residence.

FIG. 1 is an explanatory diagram showing an outline of an information processing method according to an embodiment. FIG. 2 is a diagram illustrating a configuration example of an information processing system according to the embodiment; FIG. 3 is a diagram illustrating a configuration example of a terminal device according to the embodiment; FIG. 4 is a diagram illustrating a configuration example of an information providing apparatus according to the embodiment; FIG. 5 is a diagram showing an example of a user information database. FIG. 6 is a diagram showing an example of the history information database. FIG. 7 is a diagram showing an example of a similarity information database. FIG. 8 is a flow chart showing a processing procedure according to the embodiment. FIG. 9 is a diagram illustrating an example of a hardware configuration;

Embodiments for implementing an information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail below with reference to the drawings. The information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment. Also, in the following embodiments, the same parts are denoted by the same reference numerals, and overlapping descriptions are omitted.

[1. Outline of information processing method]
First, an outline of an information processing method performed by an information processing apparatus according to an embodiment will be described with reference to FIG. FIG. 1 is an explanatory diagram showing an outline of an information processing method according to an embodiment. In FIG. 1, a case will be described as an example in which the user is proposed to move to an area other than the residential area based on the similarity of behavior with residents of the area other than the residential area.

As shown in FIG. 1 , the information processing system 1 includes a terminal device 10 and an information providing device 100 . The terminal device 10 and the information providing device 100 are communicably connected to each other by wire or wirelessly via a network N (see FIG. 2). In this embodiment, the terminal device 10 cooperates with the information providing device 100 .

The terminal device 10 is a smart device such as a smartphone or tablet used by a user U (user), and communicates with an arbitrary server device via a wireless communication network such as 4G (Generation) or LTE (Long Term Evolution). It is a portable terminal device capable of performing The terminal device 10 has a screen such as a liquid crystal display and has a touch panel function, and the user U can perform a tap operation, a slide operation, a scroll operation, or the like with a finger, a stylus, or the like, and display data such as contents. Accepts various operations for . An operation performed on an area where content is displayed on the screen may be an operation on the content. In addition, the terminal device 10 may be an information processing device such as a desktop PC (Personal Computer) or a notebook PC as well as a smart device.

The information providing device 100 cooperates with the terminal device 10 of each user U, and provides the terminal device 10 of each user U with API (Application Programming Interface) services for various applications (hereinafter referred to as apps) and various It is an information processing device that provides data, and is realized by a server device, a cloud system, or the like.

Also, the information providing device 100 may be an information processing device that provides some web service online to the terminal device 10 of each user U. FIG. For example, the information providing apparatus 100 provides Web services such as Internet connection, search service, SNS (Social Networking Service), electronic commerce, electronic payment, online game, online banking, online trading, accommodation/ticket reservation, video/music distribution, Services such as news, maps, route search, route guidance, route information, operation information, and weather forecast may be provided. In practice, the information providing apparatus 100 may cooperate with various servers that provide web services as described above, mediate web services, or take charge of web service processing.

Note that the information providing device 100 can acquire user information about the user U. FIG. For example, the information providing device 100 acquires information about attributes of the user U, such as the user's U gender, age, and area of residence. The information providing apparatus 100 stores and manages identification information indicating the user U (user ID, etc.) and information related to the attributes of the user U. FIG.

Further, the information providing apparatus 100 acquires various types of history information (log data) indicating actions of the user U from the terminal apparatus 10 of the user U or from various servers based on the user ID or the like. For example, the information providing device 100 acquires a location history, which is a history of the user U's location and date and time, from the terminal device 10 . The information providing apparatus 100 also acquires a search history, which is a history of search queries input by the user U, from a search server (search engine). Further, the information providing apparatus 100 acquires a viewing history, which is a history of content viewed by the user U, from the content server. The information providing apparatus 100 also acquires a purchase history (payment history), which is a history of product purchases and payment processing of the user U, from an electronic commerce server or a payment processing server. Further, the information providing apparatus 100 may acquire the exhibition history and sales history, which are the history of the user U's exhibition in the marketplace, from the electronic commerce server or the settlement server. In addition, the information providing apparatus 100 acquires the posting history, which is the posting history of the user U, from a posting server that provides a word-of-mouth posting service or an SNS server.

In the present embodiment, the information providing apparatus 100 collects data of an unspecified number of users U, and based on location information and history information of each user U, an area other than the residential area of each user U ( Non-residential area) determines the similarity of behavior between each user U and residents of the area. That is, the information providing device 100 determines the similarity in behavior between the user U who is a non-resident of the area and the resident of the area. Then, the information providing apparatus 100 presumes that the user U whose behavior is similar to that of a resident of the area is likely to migrate to the area (potential immigrant), and the user U propose to move to the area. A person who is likely to migrate to the area (potentially migratable person) is a person who can adapt to the area and who can live there without any problems. Moreover, the behavior similar to that of the resident includes behavior that is the same as that of the resident or that the behavior is similar to that of the resident.

For example, the information providing apparatus 100 determines whether the location history of the user U, SNS, payment history with a credit card, electronic money, or the like, when there is a large history of use of stores frequented by local people, or when there is a history of staying in the area. If the person behaves like a local, such as frequently using the local shopping district, it is determined that the behavior is similar to that of a resident of the area.

At this time, the information providing apparatus 100 may calculate a similarity score indicating how similar the actions of the user U and the residents of the area are (similarity). Note that the information providing apparatus 100 compares the behavior of the user U and the residents of the area within a predetermined period (for example, one day, one week, one month), and compares the actions of the user U and the residents of the area. You may calculate the similarity score of the action with. Further, the information providing apparatus 100 may extract individual actions of the user U in the area, compare them with actions of residents in the area, and calculate a similarity score for each individual action. Then, based on the similarity score, the information providing device 100 estimates that the user U is likely to migrate to the area, and proposes to the user U to migrate to the area. good. For example, when the similarity score is equal to or greater than a threshold, the information providing device 100 may estimate the user U as a person who may migrate to the area. In addition, the information providing device 100 may select an area where many residents who take actions with a high similarity score live, and propose to the user U to move to that area. At this time, the information providing apparatus 100 may present to the user U, together with the behavioral similarity score, areas in which many residents who take behaviors with high similarity scores live in a ranking format.

Further, when the user U and a resident of the area frequently act together in the area, the information providing apparatus 100 presumes that there is a person who is on good terms with the user U in the area. The user U may be presumed to be a person who has the possibility of moving to the area, and the user U may be proposed to move to the area. Moreover, when the user U and the resident of the area act together, the behavior of both naturally resembles. For example, the information providing apparatus 100 detects whether the user U and the resident of the area are acting together from the location information of each user U, various history information (such as payment history at a store), or SNS. We estimate that Alternatively, when the terminal devices 10 of the users U continue to be able to detect each other through short-range wireless communication, the information providing device 100 is configured so that the users U and the residents of the area are acting together. presumed to be

Further, the information providing apparatus 100 creates a persona (personal image) of the residents of the area from the data of an unspecified number of residents of the area, and the behavior of the user U is the persona of the residents of the area. If the behavior is similar, the user U may be presumed to be a person who may migrate to the area. At this time, the information providing apparatus 100 may create a persona of a resident (representative resident of the area) who behaves like most residents in the area. Further, the information providing apparatus 100 may cluster the residents of the area according to their behavior patterns and create a persona of the residents of the area for each cluster.

In addition, the information providing apparatus 100 determines not only the similarity of behavior between the user U and the residents of the area, but also the similarity of the attributes and hobbies/interests between the user U and the residents of the area, A user U whose attributes, hobbies, and interests are similar to those of a resident may be presumed to be a person who may migrate to the area.

For example, if the user U has a hobby of surfing and visits a seaside town where people who have the same hobby of surfing gather every weekend, the information providing apparatus 100 sends the user U to the town. It is estimated that there is a possibility of immigration. The same applies to scuba diving, fishing, skiing/snowboarding, mountain climbing/hiking, camping/barbecue, canoeing/kayaking, hang gliding/paragliding, and the like, in addition to surfing.

Further, when the user U regularly visits an area where people with the same purpose, such as agriculture or volunteer work, gather, the information providing apparatus 100 presumes that the user U is likely to migrate to that area.

In addition, the information providing apparatus 100 is designed so that the user U has a strong interest in a specific drama, movie, animation, etc., and even after the drama, movie, animation, etc. ends, the information providing apparatus 100 does not appear in the drama, movie, animation, etc. If the user U frequently visits an area or place that has been used as a model (or a model) (so-called pilgrimage to sacred places), it is estimated that the user U is likely to migrate to that town.

In addition, when the user U frequently visits the same area personally (no need to visit) regardless of daily work or homecoming, the information providing apparatus 100 sends the user U to the area. It is estimated that there is a possibility of immigration of For example, the information providing device 100 can obtain information from the user U's location history, SNS, train/airplane ticket purchase history, highway bus/hotel reservation history, payment history at stores not in the daily life area, and the like. , when it is estimated that the user U is visiting a specific area on a regular basis, the user U is estimated to be a person who may migrate to that area.

In addition, even if the user U has not actually visited the area, the information providing apparatus 100 can determine the It may be determined that the user U matches the area, and the user U may be estimated to be a person who may migrate to the area. The behavior pattern may be, for example, consumption behavior, lifestyle, or the like.

In addition, the information providing device 100 proposes migration to the area to the user U designated as having the possibility of migration to the area. For example, the information providing device 100 introduces and guides areas that match the user U as migration destination candidates (migration candidate sites) via the network N (see FIG. 2). In addition, the information providing device 100 provides information regarding the introduction and mediation of local properties and jobs that match the user U. FIG. In addition, the information providing device 100 provides information on the migration support system of the local government that matches the user U, and the like.

Further, the information providing device 100 is not limited to providing local information to the user U, and may also provide selected local governments with information on personas of persons who may migrate to the local governments. . In addition, the information providing device 100 issues an advertisement (advertisement for potential immigrants) corresponding to the persona of a person who is likely to migrate to the selected local government. may be suggested.

In addition, the information providing apparatus 100 may generate and present a ranking of regions that match the user for each user. For example, the information providing device 100 may generate and present to the user U a ranking of “your” easy-to-migrate areas.

Furthermore, the information providing apparatus 100 is used when the user U is at home (does not go to work) during the day, but there is no significant change in income (annual income), or when the user U has left or changed jobs. If not, it may be assumed that the user U is teleworking. In addition, it is the same when the user U is a nomad worker.

At this time, the information providing apparatus 100 considers the current place of work, living environment, etc., for the user U who is doing telework, so that the rent is cheaper than the current one, there is a network environment, and the place of work is Select a location that is easy to move to and propose it as a migration destination candidate (migration candidate site).

In addition, when the user U is looking for a workation (work + vacation) place, or when the user U is a potential workation applicant, the information providing apparatus 100 matches the user U. In addition to being an area where a workation is to be held, an area with a good communication environment (an area where a network can be connected) may be searched and proposed as a workcation location. Furthermore, the information providing apparatus 100 may search for areas where there are places where meetings can be held, such as meeting rooms, and propose them as workation places.

At this time, the information providing apparatus 100 provides the user U who desires the workation with information on the rent market price, infrastructure, etc. of the area as area information.

[1-1. Migration proposal method for potential migrants]
Here, with reference to FIG. 1, a method of proposing emigration to potential immigrants will be described.

As shown in FIG. 1, the information providing device 100 collects context information of an unspecified number of users U via a network N (see FIG. 2) (step S1). For example, the information providing apparatus 100 collects user U's location information, various history information, attribute information, etc. as user U's context information from each user's U terminal device 10, various servers, and the like.

Subsequently, the information providing apparatus 100 identifies residents in each area based on the information on the place of residence of the user U, and extracts the behavior of the residents in each area from the context information of the residents in each area (step S2). At this time, the information providing apparatus 100 may model the behavior patterns of residents in each region. Alternatively, the information providing apparatus 100 may generate personas of residents of each area.

Subsequently, the information providing device 100 extracts the behavior of the user U from the context information of each user U (step S3).

Subsequently, the information providing device 100 determines the similarity with the behavior of the residents of the area other than the residence of the user U (step S4). At this time, the information providing apparatus 100 may determine the similarity between the behavior pattern of the user U and the behavior pattern of the residents of each area. Alternatively, the information providing device 100 may determine the similarity between the behavior of the user U and the behavior of the persona of the resident of each area. The information providing apparatus 100 may determine the similarity between the attributes of the user U and the attributes of the residents of each region, in addition to the similarity of actions.

Subsequently, the information providing device 100 presumes that the user U whose behavior is similar to that of a resident of the area is a person who may migrate to the area (potential immigrant) (step S5). In addition to the similarity of behavior, the information providing apparatus 100 may also estimate a user U who has similar attributes to residents of the area as a person who may migrate to the area.

Subsequently, the information providing device 100 proposes migration to the area to the user U who is estimated to have the possibility of migration to the area (step S6). Further, the information providing device 100 provides the user U with various information about the area in addition to the suggestion of moving to the area.

As described above, the information providing apparatus 100 according to the present embodiment detects the possibility of immigration to the area based on the similarity in behavior between the user and the residents of the area other than the user's residential area. Estimate the user and propose to the user to move to the area.

[2. Configuration example of information processing system]
Next, the configuration of the information processing system 1 including the information providing device 100 according to the embodiment will be described with reference to FIG. FIG. 2 is a diagram showing a configuration example of the information processing system 1 according to the embodiment. As shown in FIG. 2, the information processing system 1 according to the embodiment includes a terminal device 10 and an information providing device 100. As shown in FIG. These various devices are communicatively connected via a network N by wire or wirelessly. The network N is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network) such as the Internet.

Also, the number of devices included in the information processing system 1 shown in FIG. 2 is not limited to the illustrated one. For example, in FIG. 2, only one terminal device 10 is shown for simplification of illustration, but this is only an example and is not limited, and two or more devices may be provided.

The terminal device 10 is an information processing device used by the user U. FIG. For example, the terminal device 10 may be a smart device such as a smartphone or a tablet terminal, a feature phone, a PC (Personal Computer), a PDA (Personal Digital Assistant), a game machine with a communication function, a car navigation system, a smart watch, or a head-mounted display. and other wearable devices, smart glasses, and the like.

In addition, the terminal device 10 is compatible with wireless communication networks such as LTE (Long Term Evolution), 4G (4th Generation), 5G (5th Generation: fifth generation mobile communication system), Bluetooth (registered trademark), wireless LAN (Local It is possible to communicate with the information providing apparatus 100 by connecting to the network N via short-range wireless communication such as Area Network).

The information providing device 100 is, for example, a PC, a server device, a mainframe, a workstation, or the like. Note that the information providing apparatus 100 may be realized by cloud computing.

[3. Configuration example of terminal device]
Next, the configuration of the terminal device 10 will be described using FIG. FIG. 3 is a diagram showing a configuration example of the terminal device 10. As shown in FIG. As shown in FIG. 3, the terminal device 10 includes a communication unit 11, a display unit 12, an input unit 13, a positioning unit 14, a sensor unit 20, a control unit 30 (controller), and a storage unit 40. Prepare.

(Communication unit 11)
The communication unit 11 is connected to the network N (see FIG. 2) by wire or wirelessly, and transmits and receives information to and from the information providing apparatus 100 via the network N. FIG. For example, the communication unit 11 is implemented by a NIC (Network Interface Card), an antenna, or the like.

(Display unit 12)
The display unit 12 is a display device that displays various information such as position information. For example, the display unit 12 is a liquid crystal display (LCD) or an organic EL display (Organic Electro-Luminescent Display). Also, the display unit 12 is a touch panel display, but is not limited to this.

(Input unit 13)
The input unit 13 is an input device that receives various operations from the user U. For example, the input unit 13 has buttons and the like for inputting characters, numbers, and the like. The input unit 13 may be an input/output port (I/O port), a USB (Universal Serial Bus) port, or the like. Moreover, when the display unit 12 is a touch panel display, a part of the display unit 12 functions as the input unit 13 . Also, the input unit 13 may be a microphone or the like that receives voice input from the user U. FIG. The microphone may be wireless.

(Positioning unit 14)
The positioning unit 14 receives signals (radio waves) transmitted from GPS (Global Positioning System) satellites, and based on the received signals, position information (for example, latitude and longitude). That is, the positioning unit 14 positions the position of the terminal device 10 . GPS is merely an example of GNSS (Global Navigation Satellite System).

Also, the positioning unit 14 can measure the position by various methods other than GPS. For example, the positioning unit 14 may measure the position using various communication functions of the terminal device 10 as described below as auxiliary positioning means for position correction and the like.

(Wi-Fi positioning)
For example, the positioning unit 14 measures the position of the terminal device 10 using the Wi-Fi (registered trademark) communication function of the terminal device 10 or the communication network provided by each communication company. Specifically, the positioning unit 14 performs Wi-Fi communication or the like and measures the position of the terminal device 10 by measuring the distance to a nearby base station or access point.

(beacon positioning)
The positioning unit 14 may also use the Bluetooth (registered trademark) function of the terminal device 10 to measure the position. For example, the positioning unit 14 positions the position of the terminal device 10 by connecting with a beacon transmitter connected by the Bluetooth (registered trademark) function.

(geomagnetic positioning)
Further, the positioning unit 14 positions the position of the terminal device 10 based on the geomagnetism pattern of the structure measured in advance and the geomagnetic sensor provided in the terminal device 10 .

(RFID positioning)
Further, for example, if the terminal device 10 has an RFID (Radio Frequency Identification) tag function equivalent to a contactless IC card used at station ticket gates, shops, etc., or has a function of reading an RFID tag In this case, the location used is recorded together with the information that the payment was made by the terminal device 10 . The positioning unit 14 may measure the position of the terminal device 10 by acquiring such information. Also, the position may be measured by an optical sensor provided in the terminal device 10, an infrared sensor, or the like.

The positioning unit 14 may measure the position of the terminal device 10 using one or a combination of the positioning means described above, if necessary.

(Sensor unit 20)
The sensor unit 20 includes various sensors mounted on or connected to the terminal device 10 . The connection may be wired connection or wireless connection. For example, the sensors may be detection devices other than the terminal device 10, such as wearable devices and wireless devices. In the example shown in FIG. 3, the sensor unit 20 includes an acceleration sensor 21, a gyro sensor 22, an atmospheric pressure sensor 23, an air temperature sensor 24, a sound sensor 25, an optical sensor 26, a magnetic sensor 27, and an image sensor ( camera) 28.

The sensors 21 to 28 described above are only examples and are not limited. That is, the sensor unit 20 may be configured to include a part of the sensors 21 to 28, or may include other sensors such as a humidity sensor in addition to or instead of the sensors 21 to 28. .

The acceleration sensor 21 is, for example, a three-axis acceleration sensor, and detects physical movements of the terminal device 10 such as movement direction, speed, and acceleration of the terminal device 10 . The gyro sensor 22 detects physical movements of the terminal device 10 such as inclination in three axial directions based on the angular velocity of the terminal device 10 and the like. The atmospheric pressure sensor 23 detects the atmospheric pressure around the terminal device 10, for example.

Since the terminal device 10 includes the above-described acceleration sensor 21, gyro sensor 22, barometric pressure sensor 23, etc., techniques such as pedestrian dead-reckoning (PDR: Pedestrian Dead-Reckoning) using these sensors 21 to 23, etc. , the position of the terminal device 10 can be determined. This makes it possible to acquire indoor position information that is difficult to acquire with a positioning system such as GPS.

For example, a pedometer using the acceleration sensor 21 can calculate the number of steps, walking speed, and distance walked. Further, by using the gyro sensor 22, it is possible to know the traveling direction, the direction of the line of sight, and the inclination of the body of the user U. Also, from the atmospheric pressure detected by the atmospheric pressure sensor 23, the altitude at which the terminal device 10 of the user U is present and the number of floors can be known.

The temperature sensor 24 detects the temperature around the terminal device 10, for example. The sound sensor 25 detects sounds around the terminal device 10, for example. The optical sensor 26 detects the illuminance around the terminal device 10 . The magnetic sensor 27 detects, for example, geomagnetism around the terminal device 10 . The image sensor 28 captures an image around the terminal device 10 .

The atmospheric pressure sensor 23, the temperature sensor 24, the sound sensor 25, the optical sensor 26, and the image sensor 28 described above detect the atmospheric pressure, temperature, sound, and illuminance, respectively, or capture an image of the surroundings to detect the terminal device 10. It is possible to detect the surrounding environment and situations. In addition, it is possible to improve the accuracy of the location information of the terminal device 10 based on the surrounding environment and situation of the terminal device 10 .

(control unit 30)
The control unit 30 includes, for example, a microcomputer having a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM, an input/output port, and various circuits. Also, the control unit 30 may be configured by hardware such as an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control unit 30 includes a transmission unit 31 , a reception unit 32 and a processing unit 33 .

(Sending unit 31)
The transmission unit 31 receives, for example, various information input by the user U using the input unit 13, various information detected by the sensors 21 to 28 mounted on or connected to the terminal device 10, and information measured by the positioning unit 14. The position information of the terminal device 10 and the like can be transmitted to the information providing device 100 via the communication unit 11 .

(Receiver 32)
The receiving unit 32 can receive various information provided by the information providing apparatus 100 and requests for various information from the information providing apparatus 100 via the communication unit 11 .

(Processing unit 33)
The processing unit 33 controls the entire terminal device 10 including the display unit 12 and the like. For example, the processing unit 33 can output various types of information transmitted by the transmitting unit 31 and various types of information received by the receiving unit 32 from the information providing apparatus 100 to the display unit 12 for display.

(storage unit 40)
The storage unit 40 is realized by, for example, a semiconductor memory device such as RAM (Random Access Memory) or flash memory, or a storage device such as HDD (Hard Disk Drive), SSD (Solid State Drive), or optical disk. be. Various programs, various data, and the like are stored in the storage unit 40 .

[4. Configuration example of information providing device]
Next, the configuration of the information providing device 100 according to the embodiment will be described using FIG. FIG. 4 is a diagram showing a configuration example of the information providing device 100 according to the embodiment. As shown in FIG. 4, the information providing device 100 has a communication section 110, a storage section 120, and a control section .

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. Also, the communication unit 110 is connected to the network N (see FIG. 2) by wire or wirelessly.

(storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG. 4 , storage unit 120 has user information database 121 , history information database 122 , and similarity information database 123 .

(User information database 121)
The user information database 121 stores user information about the user U. FIG. For example, the user information database 121 stores various information such as user U attributes. FIG. 5 is a diagram showing an example of the user information database 121. As shown in FIG. In the example shown in FIG. 5, the user information database 121 has items such as "user ID (Identifier)", "age", "gender", "home", "place of work", and "interest".

“User ID” indicates identification information for identifying the user U. The “user ID” may be the user U's contact information (telephone number, e-mail address, etc.), or may be identification information for identifying the user U's terminal device 10 .

"Age" indicates the age of the user U identified by the user ID. Note that the "age" may be information indicating a specific age of the user U (for example, 35 years old) or information indicating the age of the user U (for example, 30's). . Alternatively, the "age" may be information indicating the date of birth of the user U, or information indicating the generation of the user U (for example, born in the 80's). "Gender" indicates the gender of the user U identified by the user ID.

"Home" indicates location information of the home of the user U identified by the user ID. In the example shown in FIG. 5, "home" is represented by an abstract code such as "LC11", but may be latitude/longitude information or the like. Also, for example, "home" may be an area name or an address.

"Place of work" indicates location information of the place of work (school in the case of a student) of the user U identified by the user ID. In the example shown in FIG. 5, the "place of work" is illustrated as an abstract code such as "LC12", but may be latitude/longitude information or the like. Also, for example, the "place of work" may be an area name or an address.

"Interest" indicates the interest of the user U identified by the user ID. That is, "interest" indicates an object in which the user U identified by the user ID is highly interested. For example, the "interest" may be a search query (keyword) that the user U has entered into a search engine and searched for. In the example shown in FIG. 5, one "interest" is shown for each user U, but a plurality of "interests" may be shown.

For example, in the example shown in FIG. 5, the age of the user U identified by the user ID "U1" is "twenties" and the gender is "male". Also, for example, the user U identified by the user ID "U1" indicates that the home is "LC11". Also, for example, the user U identified by the user ID "U1" indicates that the place of work is "LC12". Also, for example, the user U identified by the user ID "U1" indicates that he is interested in "sports".

Here, in the example shown in FIG. 5, abstract values such as “U1”, “LC11” and “LC12” are used, but “U1”, “LC11” and “LC12” are concrete values. It is assumed that information such as character strings and numerical values is stored. Hereinafter, abstract values may also be illustrated in diagrams relating to other information.

The user information database 121 is not limited to the above, and may store various types of information depending on the purpose. For example, the user information database 121 may store various information about the terminal device 10 of the user U. FIG. In addition, the user information database 121 stores user U's demographics (demographic attributes), psychographics (psychological attributes), geographics (geographical attributes), behavioral attributes (behavioral attributes), etc. Information about attributes may be stored. For example, the user information database 121 includes name, family structure, hometown (local), occupation, position, income, qualification, residence type (detached house, condominium, etc.), presence or absence of car, commuting time, commuting time, commuting time. Information such as routes, commuter pass sections (stations, lines, etc.), frequently used stations (other than the nearest station to your home or place of work), lessons (places, time zones, etc.), hobbies, interests, lifestyle, etc. may

(History information database 122)
The history information database 122 stores various types of information related to history information (log data) indicating user U's actions. FIG. 6 is a diagram showing an example of the history information database 122. As shown in FIG. In the example shown in FIG. 6, the history information database 122 has items such as "user ID", "location history", "search history", "browsing history", "purchase history", and "posting history".

“User ID” indicates identification information for identifying the user U. "Position history" indicates a position history that is a history of the user's U position and movement. Also, "search history" indicates a search history that is a history of search queries input by the user U. FIG. "Browsing history" indicates a browsing history that is a history of contents browsed by the user U. FIG. "Purchase history" indicates the purchase history of the user U's purchases. In addition, “posting history” indicates a posting history that is a history of posts by the user U. FIG. In addition, the “posting history” may include questions about user U's property.

For example, in the example shown in FIG. 6, the user U identified by the user ID "U1" moves along the "location history #1", searches along the "search history #1", It indicates that the content was browsed according to the "Purchase history #1", the predetermined product etc. was purchased at the predetermined store etc. according to the "Purchase history #1", and the content was posted according to the "Posting history".

Here, in the example shown in FIG. 6, abstract history such as "U1", "location history #1", "search history #1", "browsing history #1", "purchase history #1", and "posting history #1" "U1", "location history #1", "search history #1", "browsing history #1", "purchase history #1" and "posting history #1" , information such as specific character strings and numerical values are stored.

Note that the history information database 122 may store various types of information, not limited to the above, depending on the purpose. For example, the history information database 122 may store the user U's usage history of a predetermined service. In addition, the history information database 122 may store the user U's store visit history, facility visit history, and the like. In addition, the history information database 122 may store a history of payment (electronic payment) using the terminal device 10 of the user U, and the like.

(Similarity information database 123)
The similarity information database 123 stores various types of information related to similarities in behavior between each user and residents of each area. FIG. 7 is a diagram showing an example of the similarity information database 123. As shown in FIG. In the example shown in FIG. 7, the similarity information database 123 includes items such as "user ID", "area", "visit frequency", "behavior", "execution frequency", "persona", and "similarity". have.

“User ID” indicates identification information for identifying the user U. "Area" indicates an area that the user U has visited. The area may be indicated by area divisions such as the Kanto region, names of administrative divisions such as prefectures and municipalities, or may be indicated by location coordinates such as addresses, regional mesh codes, and latitude and longitude.

"Visit frequency" indicates the frequency with which the user U visits the area. For example, "visit frequency" indicates the number of times the user U has visited the area so far, and how many days (every weekend, etc.) in a year/month/week the user U has visited the area (frequency).

Also, "behavior" indicates the behavior that the user U has taken. For example, "action" indicates actions taken by the user U when the user U visits the area. It should be noted that, in fact, the action taken by the user U may be irrespective of whether or not the user U has visited the area. Also, the number of "behaviors" is not limited to one, and may be plural. Also, it may be a daily action pattern or a continuous action (a series of actions).

Also, "execution frequency" indicates the frequency with which the user U takes the action. For example, the "execution frequency" indicates the number of times the user U has taken the action so far, and the frequency or ratio (probability) of taking the action when the user U visits the area.

"Persona" indicates a persona (personal image) of a resident of the area. Note that the persona may be a persona of a representative resident of the area, or may be a persona of a resident for each cluster classified according to behavior patterns.

The "similarity" indicates the similarity of behavior between the user U and the persona of a resident of the area. The “similarity” may be the similarity of individual actions between the user U and the persona of the resident of the area, or may be the similarity of a series of actions.

For example, in the example shown in FIG. 7, a user U identified by a user ID "U1" visits a certain area "area #A1" with a frequency of "visit frequency #A1" and visits a certain area "area #A1". The action "action #A1" is performed at a frequency of "execution frequency #A1", and the action is similar to the action of the persona "persona #A1" of the resident of the area with a "similarity #A1".

Here, in the example shown in FIG. 7, "U1", "region #A1", "visit frequency #A1", "behavior #A1", "execution frequency #A1", "persona #A1", and "similarity # Although illustrated using abstract values such as "A1", "U1", "area #A", "visit frequency #A1", "behavior #A1", "execution frequency #A1", "persona #A1" and Information such as specific character strings and numerical values is stored in “similarity #A1”.

It should be noted that the similarity information database 123 may store various types of information, not limited to the above, depending on the purpose. For example, the similarity information database 123 may store information regarding the order of regional rankings as migration recommendation candidates arranged in descending order of similarity. Further, the similarity information database 123 may store detailed information such as an introduction to the area, advertisements about properties and jobs in the area, and the like for each area. Further, the similarity information database 123 stores the possibility or probability (migration possibility, migration probability) of the user U migrating to the area based on the context information (attribute information, various history information, etc.) of the user U. may store information about

(control unit 130)
Returning to FIG. 4, the description is continued. The control unit 130 is a controller, and for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like controls the information providing apparatus 100. Various programs (corresponding to an example of an information processing program) stored in the internal storage device are executed by using a storage area such as a RAM as a work area. In the example illustrated in FIG. 4 , the control unit 130 has an acquisition unit 131 , an extraction unit 132 , an estimation unit 133 and a provision unit 134 .

(Acquisition unit 131)
The acquisition unit 131 acquires a search query input by the user U. For example, the acquisition unit 131 acquires the search query via the communication unit 110 when the user U inputs a search query into a search engine or the like and performs a keyword search.

The acquisition unit 131 also acquires user information about the user U via the communication unit 110 . For example, the acquisition unit 131 acquires identification information (user ID, etc.) indicating the user U, location information of the user U, attribute information of the user U, and the like, from the terminal device 10 of the user U. FIG. Further, the acquisition unit 131 may acquire identification information indicating the user U, attribute information of the user U, and the like when the user U is registered as a user. Acquisition unit 131 then registers the user information in user information database 121 of storage unit 120 .

In addition, the acquisition unit 131 acquires various types of history information (log data) indicating actions of the user U via the communication unit 110 . For example, the acquisition unit 131 acquires various types of history information indicating actions of the user U from the terminal device 10 of the user U or from various servers based on the user ID or the like. The acquisition unit 131 then registers various types of history information in the history information database 122 of the storage unit 120 .

In this embodiment, the acquisition unit 131 collects information on an unspecified number of users U. FIG. For example, the acquisition unit 131 collects user U's context information via the communication unit 110 . At this time, the acquisition unit 131 collects at least one of user U's attribute information, location information, and history information as user U's context information. In addition, the acquisition unit 131 may collect, as the user U's context information, information related to the detection/measurement results of each sensor mounted on the user U's terminal device 10 .

Acquisition unit 131 also collects information about the area via communication unit 110 . For example, the acquisition unit 131 collects information about regional features via the communication unit 110 . The acquisition unit 131 also collects, via the communication unit 110, information on local governments and the like that seek potential immigrants. Acquisition unit 131 also collects information about local introductions and advertisements via communication unit 110 .

(Extraction unit 132)
The extraction unit 132 extracts the behavior of each user U and the behavior of residents in areas other than the residence of each user U from the information of an unspecified number of users U.

(Estimation unit 133)
The estimating unit 133 determines the possibility of migration to the area based on the similarity in behavior between each user U based on information on an unspecified number of users U and a resident of an area other than the residence of each user U. Estimate a user U with

In addition, the estimation unit 133 determines the user U who is likely to migrate to the region based on the similarity in behavior between each extracted user U and a resident of the region other than the residence of each user U. presume.

In addition, the estimation unit 133 identifies the user U who, when visiting an area other than the place of residence, behaves similar to the behavior of the residents of the area, as a user who may migrate to the area. Estimate as U.

In addition, the estimation unit 133 determines, from the similarity in behavior between each user U and a resident of an area other than the residence of each user U within a predetermined period (for example, one day, one week, one month), Estimate users U who may migrate to the area.

In addition, the estimation unit 133 estimates users U who are likely to migrate to the area from the similarity of individual behavior between each user U and residents of areas other than the residence of each user U. do.

In addition, the estimation unit 133 estimates users U who are likely to migrate to the area from the similarity of behavior patterns between each user U and residents of areas other than the residence of each user U. .

In addition, the estimation unit 133 estimates users U who are likely to migrate to the region from the similarity in behavior between each user U and personas of residents of regions other than the residence of each user U. do.

In addition, the estimation unit 133 clusters the residents of the area other than the residence of each user U, and based on the similarity in behavior between each user U and the persona of each cluster resident, determines whether it is likely to immigrate to the area. A possible user U is estimated.

In addition, the estimating unit 133 calculates a similarity score indicating the degree of similarity in behavior between each user U and a resident of an area other than the residence of each user U, and selects a user U whose similarity score is equal to or greater than a threshold. , as users U who may migrate to the area.

In addition to the similarity of behavior, the estimating unit 133 also determines the possibility of migration to the area based on the similarity of attributes between each user U and residents of areas other than the place of residence of each user U. Estimate a user U with

At this time, the estimating unit 132 may construct a model for estimating whether or not the user U is a potential immigrant by using a machine learning technique, using the context information of the user U as input data. The machine learning method is, for example, deep learning using a DNN (Deep Neural Network). Data mining and other machine learning algorithms may also be used.

For example, the estimation unit 132 uses RNN (Recurrent Neural Network), LSTM (Long short-term memory), etc. as a data set of the behavior (and attributes) of residents in each area and the area (resident area of the resident). machine learning using , and build a model for estimating people who can migrate as a learning model. Then, the estimation unit 132 inputs the behavior (and attributes) of the user U to the built estimation model of persons who can migrate, and out of the areas obtained as output, the areas other than the residential area of the user U are identified as possible migrants. to get as Thereby, the estimation unit 132 can determine whether or not the user U is a potential immigrant person, and can estimate to which region the user U can migrate.

(Providing unit 134)
The provision unit 134 proposes migration to a certain area to the user U who is estimated to have a possibility of migration to that area. In addition, the providing unit 134 provides the terminal device 10 of the user U with information on the area where migration is proposed via the communication unit 110 . At this time, the providing unit 134 may provide information on the ranking of the regions to which migration is proposed. In addition, the providing unit 134 provides information on the persona (personal image) of a potential immigrant to the municipality of the area where immigration is proposed via the communication unit 110 . Further, the providing unit 134 issues advertisements (advertisements for potential immigrants) according to the persona of potential immigrants to the local governments of the areas where migration is proposed. You can suggest.

[5. Processing procedure]
Next, a processing procedure performed by the information providing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 8 is a flow chart showing a processing procedure according to the embodiment. Note that the processing procedure described below is repeatedly executed by the control unit 130 of the information providing apparatus 100 .

As shown in FIG. 8, the acquisition unit 131 of the information providing device 100 collects context information of an unspecified number of users U via the communication unit 110 (step S101). For example, the acquisition unit 131 collects at least one of user U's attribute information, location information, and history information as user U's context information.

Subsequently, the extraction unit 132 of the information providing device 100 extracts the behavior of the residents of each region from the context information of the unspecified number of users U (step S102). For example, the extraction unit 132 extracts the residential area of the user U from the attribute information and location information of the user U acquired as the context information of the user U, the delivery destination information included in the purchase history, or the content posted on the SNS. is estimated, and the behavior as a resident of the area is extracted from the context information of the user U who is a resident of the area of residence.

Subsequently, the estimation unit 133 of the information providing device 100 estimates that the user U has visited the specific area from the context information of the user U (step S103). The specific area to be visited is an area other than the user U's residential area. That is, the user U is a non-resident of the specific area. For example, the estimating unit 133 determines the location history of the user U acquired as the context information of the user U, travel destination information such as tickets and hotel reservations included in the purchase history, content posted on SNS, etc. estimated to have visited a specific region.

Subsequently, the extracting unit 132 of the information providing device 100 extracts the behavior of the user U in the specific area of the visit destination from the context information of the user U (step S104). For example, the extracting unit 132 extracts the behavior of the user U in the specific area visited from the user U's location information and various history information acquired as the user U's context information, or from the content posted on the SNS. do. Note that the specific area is not limited to one place, and may be a plurality of areas. When the user U visits a plurality of areas, the extraction unit 132 extracts the behavior of the user U for each area visited.

Subsequently, the estimation unit 133 of the information providing device 100 determines whether or not the actions of the user U and the residents in the specific area to be visited are similar (step S105). At this time, the estimating unit 133 calculates a similarity score indicating the degree of similarity in behavior between the user U and the resident in the specific area visited, and if the similarity score is equal to or greater than a threshold, the estimating unit 133 It may be determined that the behavior with the person is similar. In addition, the estimation part 133 complete|finishes a series of processes, when the action of the user U and the resident in the specific area of a visiting place is not similar (step S105: No).

Subsequently, when the behavior of the user U and the resident in the specific area of the visiting destination is similar (step S105: Yes), the estimation unit 133 of the information providing device 100 determines that the user U is located in the specific area. (step S106).

Subsequently, the providing unit 134 of the information providing device 100 specifies, via the communication unit 110, the user U, who is estimated to be a person who may migrate to the specific area (potential person who can migrate). Propose migration to the area (step S107).

Subsequently, the providing unit 134 of the information providing device 100 provides the terminal device 10 of the user U with information on the specific area via the communication unit 110 (step S108). Note that the providing unit 134 may periodically provide information on the specific area to the terminal device 10 of the user U, not only at the time of proposing migration to the specific area to the user U, but also after the proposal. good.

At this time, the providing unit 134 presents a ranking of areas where many residents who behave similarly to the user U live (areas to which the user U can move), and the area designated by the user U from among the rankings. may be provided to the terminal device 10. In addition, the providing unit 134 may provide the terminal device 10 with information related to local introductions and advertisements. Further, the providing unit 134 proposes to a municipality in an area where many residents who behave similarly to the user U live, to put out an advertisement for potential immigrants to the municipality. good.

[6. Modification]
The terminal device 10 and the information providing device 100 described above may be implemented in various different forms other than the above embodiments. So, below, the modification of embodiment is demonstrated.

In the above embodiment, part or all of the processing executed by the information providing device 100 may actually be executed by the terminal device 10 . For example, the processing may be completed stand-alone (by the terminal device 10 alone). In this case, it is assumed that the terminal device 10 has the functions of the information providing device 100 in the above embodiment. In addition, in the above-described embodiment, the terminal device 10 cooperates with the information providing device 100, so from the user U's point of view, it appears that the terminal device 10 is executing the processing of the information providing device 100 as well. That is, from another point of view, it can be said that the terminal device 10 includes the information providing device 100 .

Further, in the above-described embodiment, when the information providing device 100 determines the similarity of behavior between each user U and a resident of that area in an area (non-residential area) other than the area where each user U resides, may include movement between the area and surrounding areas as actions of each user U and residents of the area.

Further, in the above embodiment, the information providing apparatus 100 further includes actions taken by residents of areas other than the residential area of each user U in the residential area of each user U, Also when the actions taken in step 2 are similar, it may be determined that the actions of each user U and the residents of the area are similar.

[7. effect〕
As described above, the information processing apparatus (information providing apparatus 100) according to the present application includes the acquisition unit 131 that collects information on an unspecified number of users U, and each usage based on the information on an unspecified number of users U. Based on the similarity of behavior between the user U and the residents of the region other than the residence of each user U, an estimation unit that estimates the user U who has the possibility of migrating to the region, and the possibility of migration to the region and a providing unit that proposes migration to the area to the user U who has the potential to move to the area.

In addition, the information processing apparatus according to the present application includes an extraction unit that extracts the behavior of each user U and the behavior of residents in areas other than the residence of each user U from information on an unspecified number of users U. and further. Then, the estimating unit estimates the users U who are likely to migrate to the area from the similarity in behavior between each extracted user U and the residents of the area other than the residential area of each user U. do.

In addition, the estimating unit identifies the user U who, when visiting an area other than the place of residence, behaves similar to the behavior of the residents of the area, as the user U who may migrate to the area. estimated as

Further, the estimating unit determines the user U who is likely to migrate to the area based on the similarity in behavior between each user U and a resident of the area other than the user U's residence within a predetermined period. presume.

Also, the estimating unit estimates the users U who are likely to migrate to the area from the similarity of individual behavior between each user U and the residents of the area other than the residence of each user U. .

Also, the estimating unit estimates the users U who are likely to migrate to the area from the similarity of behavior patterns between each user U and the residents of the area other than the user U's residential area.

Also, the estimating unit estimates the users U who are likely to migrate to the region from the similarity in behavior between each user U and the persona of a resident of the region other than the residence of each user U. .

In addition, the estimating unit clusters residents of areas other than the residence of each user U, and determines whether it is possible to migrate to the area based on the similarity in behavior between each user U and the persona of each cluster resident. Presume a user U who is likely to have

In addition, the estimation unit calculates a similarity score indicating the degree of similarity in behavior between each user U and a resident of an area other than the residence of each user U, and It is estimated as a user U who has the possibility of immigration to the area.

In addition to the similarity of behavior, the estimating unit determines the possibility of migration to the area based on the similarity of attributes between each user U and residents of areas other than the residential area of each user U. Assume a certain user U.

Through any one or a combination of the processes described above, the information processing apparatus according to the present application proposes to the user to move to that area based on the similarity of behavior with residents of the area other than the residential area. can be done.

[8. Hardware configuration]
Also, the terminal device 10 and the information providing device 100 according to the above-described embodiments are implemented by a computer 1000 configured as shown in FIG. 9, for example. The information providing apparatus 100 will be described below as an example. FIG. 9 is a diagram illustrating an example of a hardware configuration; The computer 1000 is connected to an output device 1010 and an input device 1020, and an arithmetic device 1030, a primary storage device 1040, a secondary storage device 1050, an output I/F (Interface) 1060, an input I/F 1070, and a network I/F 1080 are buses. It has a form connected by 1090.

Arithmetic device 1030 operates based on programs stored in primary storage device 1040 and secondary storage device 1050, programs read from input device 1020, and the like, and executes various types of processing. The arithmetic unit 1030 is implemented by, for example, a CPU (Central Processing Unit), MPU (Micro Processing Unit), ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array), or the like.

The primary storage device 1040 is a memory device such as a RAM (Random Access Memory) that temporarily stores data used for various calculations by the arithmetic device 1030 . The secondary storage device 1050 is a storage device in which data used for various calculations by the arithmetic device 1030 and various databases are registered. State Drive), flash memory, or the like. The secondary storage device 1050 may be an internal storage or an external storage. Also, the secondary storage device 1050 may be a removable storage medium such as a USB (Universal Serial Bus) memory or an SD (Secure Digital) memory card. Also, the secondary storage device 1050 may be a cloud storage (online storage), a NAS (Network Attached Storage), a file server, or the like.

The output I/F 1060 is an interface for transmitting information to be output to the output device 1010 that outputs various information such as a display, a projector, and a printer. (Digital Visual Interface), HDMI (registered trademark) (High Definition Multimedia Interface), and other standardized connectors. Also, the input I/F 1070 is an interface for receiving information from various input devices 1020 such as a mouse, keyboard, keypad, buttons, scanner, etc., and is realized by, for example, USB.

Also, the output I/F 1060 and the input I/F 1070 may be wirelessly connected to the output device 1010 and the input device 1020, respectively. That is, the output device 1010 and the input device 1020 may be wireless devices.

Also, the output device 1010 and the input device 1020 may be integrated like a touch panel. In this case, the output I/F 1060 and the input I/F 1070 may also be integrated as an input/output I/F.

Note that the input device 1020 includes, for example, optical recording media such as CDs (Compact Discs), DVDs (Digital Versatile Discs), PDs (Phase change rewritable discs), magneto-optical recording media such as MOs (Magneto-Optical discs), and tapes. It may be a device that reads information from a medium, a magnetic recording medium, a semiconductor memory, or the like.

Network I/F 1080 receives data from other devices via network N and sends the data to arithmetic device 1030, and also transmits data generated by arithmetic device 1030 via network N to other devices.

Arithmetic device 1030 controls output device 1010 and input device 1020 via output I/F 1060 and input I/F 1070 . For example, arithmetic device 1030 loads a program from input device 1020 or secondary storage device 1050 onto primary storage device 1040 and executes the loaded program.

For example, when the computer 1000 functions as the information providing device 100 , the arithmetic device 1030 of the computer 1000 implements the functions of the control unit 130 by executing a program loaded on the primary storage device 1040 . Further, arithmetic device 1030 of computer 1000 may load a program acquired from another device via network I/F 1080 onto primary storage device 1040 and execute the loaded program. Further, the arithmetic unit 1030 of the computer 1000 may cooperate with another device via the network I/F 1080, and call functions, data, etc. of the program from another program of the other device for use.

[9. others〕
Although the embodiments of the present application have been described above, the present invention is not limited by the contents of these embodiments. In addition, the components described above include those that can be easily assumed by those skilled in the art, those that are substantially the same, and those within the so-called equivalent range. Furthermore, the components described above can be combined as appropriate. Furthermore, various omissions, replacements, or modifications of components can be made without departing from the gist of the above-described embodiments.

Further, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or the processes described as being performed manually can be performed manually. All or part of this can also be done automatically by known methods. In addition, information including processing procedures, specific names, various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

Also, each component of each device illustrated is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution and integration of each device is not limited to the illustrated one, and all or part of them can be functionally or physically distributed and integrated in arbitrary units according to various loads and usage conditions. Can be integrated and configured.

For example, the information providing apparatus 100 described above may be implemented by a plurality of server computers, and depending on the function, may be implemented by calling an external platform or the like using an API (Application Programming Interface), network computing, or the like. can be changed flexibly.

Also, the above-described embodiments and modifications can be appropriately combined within a range that does not contradict the processing content.

Also, the above-mentioned "section, module, unit" can be read as "means" or "circuit". For example, the acquisition unit can be read as acquisition means or an acquisition circuit.

1 information processing system 10 terminal device 100 information providing device 110 communication unit 120 storage unit 121 user information database 122 history information database 123 similarity information database 130 control unit 131 acquisition unit 132 extraction unit 133 estimation unit 134 provision unit

Claims (12)

an acquisition unit that collects information of an unspecified number of users;
Based on the information of an unspecified number of users, based on the similarity of behavior between each user and the residents of the area other than the residence of each user, users who are likely to migrate to the above area are estimated. an estimation unit;
a provision unit that proposes migration to the region to users who have a possibility of migration to the region;
An information processing device comprising: An extraction unit that extracts the behavior of each user and the behavior of residents in areas other than the residence of each user from information on an unspecified number of users,
The estimating unit estimates users who are likely to migrate to the area from the similarity in behavior between each extracted user and residents of the area other than the user's residence. 2. The information processing apparatus according to claim 1. The estimating unit estimates a user who, when visiting an area other than the place of residence, behaves in a manner similar to that of a resident of the area as a user who is likely to migrate to the area. 3. The information processing apparatus according to claim 1, wherein: The estimating unit estimates users who are likely to migrate to the area based on the similarity in behavior between each user and a resident of the area other than the user's residence within a predetermined period of time. 4. The information processing apparatus according to any one of claims 1 to 3, characterized by: The estimating unit is characterized by estimating users who are likely to migrate to the area from the similarity of individual behavior between each user and residents of the area other than the residence of each user. The information processing apparatus according to any one of claims 1 to 4. The estimating unit is characterized by estimating users who are likely to migrate to the area based on similarities in behavior patterns between each user and residents of areas other than the user's residential area. The information processing apparatus according to any one of claims 1 to 5. The estimating unit is characterized by estimating users who are likely to migrate to the area from the similarity in behavior between each user and the persona of a resident of the area other than the user's residential area. The information processing apparatus according to any one of claims 1 to 6. The estimating unit clusters residents in areas other than the residential area of each user, and determines the possibility of migration to the area based on the similarity in behavior between the persona of each user and the residents of each cluster. 8. The information processing apparatus according to any one of claims 1 to 7, wherein a certain user is estimated. The estimation unit calculates a similarity score indicating a degree of similarity in behavior between each user and a resident of an area other than the residence of each user, and determines users whose similarity score is equal to or greater than a threshold to the area 9. The information processing apparatus according to any one of claims 1 to 8, characterized in that the user is estimated as a user who has a possibility of migrating to Japan. In addition to the similarity of behavior, the estimating unit further determines that there is a possibility of migration to the area based on the similarity of attributes between each user and residents of areas other than the residence of each user. 10. The information processing apparatus according to any one of claims 1 to 9, which estimates a person. An information processing method executed by an information processing device,
an acquisition step of collecting information of an unspecified number of users;
Based on the information of an unspecified number of users, based on the similarity of behavior between each user and the residents of the area other than the residence of each user, users who are likely to migrate to the above area are estimated. an estimation step;
A providing step of proposing migration to the region to a user who is likely to migrate to the region;
An information processing method comprising: Acquisition procedure for collecting information of an unspecified number of users;
Based on the information of an unspecified number of users, based on the similarity of behavior between each user and the residents of the area other than the residence of each user, users who are likely to migrate to the above area are estimated. an estimation procedure;
A provision procedure for proposing migration to the region for a user who has a possibility of migration to the region;
An information processing program for executing a computer.

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