JP7032595B1 - Information providers, information processing methods, and programs - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information providing device, an information processing method, and a program for providing information to a provider while preventing a user of a business operator from being identified. An information providing device according to the present application includes a generation unit, a specific unit, and a providing unit. The generation unit generates a classification model that classifies users into clusters based on the data about users acquired by a predetermined business operator. The identification unit identifies statistical information about users classified by the classification model for each cluster. The provider provides the classification model and statistical information to the provider. [Selection diagram] Fig. 1

Description

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

Conventionally, an electronic shopping street service that allows purchase of transaction targets sold by a plurality of businesses has been provided. As an example of such a service, a technique of proposing a transaction target selected according to a user's attribute is known.

Japanese Unexamined Patent Publication No. 2014-186582

When proposing a transaction target, the provider can propose a transaction target based on the provided information by providing information from the business operator. However, in this case, it is not preferable to provide the personal information of the user of the business operator to the provider. For example, it is not preferable that information that identifies the user of the business operator is provided to the provider.

The present application has been made in view of the above, and is an information providing device capable of providing useful information to a provider while preventing the information specified by the user of the business operator from being provided to the provider. The purpose is to provide information processing methods and programs.

The information providing device according to the present application includes a generation unit, a specific unit, and a providing unit. The generation unit generates a classification model that classifies users into clusters based on the data about users acquired by a predetermined business operator. The identification unit identifies statistical information about users classified by the classification model for each cluster. The provider provides the classification model and statistical information to the provider.

According to one aspect of the embodiment, information can be provided to the provider while preventing the user of the business operator from being identified.

FIG. 1 is an explanatory diagram showing an outline of an information processing method according to the first embodiment. FIG. 2 is a diagram showing a configuration example of the information processing system according to the first embodiment. FIG. 3 is a diagram showing a configuration example of the information providing device according to the first embodiment. FIG. 4 is a diagram schematically showing a vector space classified by a classification model. FIG. 5 is a flowchart showing the statistical information providing process according to the first embodiment. FIG. 6 is a diagram schematically showing a vector space classified by a classification model (No. 1). FIG. 7 is a diagram schematically showing a vector space classified by a classification model (No. 2). FIG. 8 is a flowchart showing a model generation process according to the second embodiment. FIG. 9 is a hardware configuration diagram showing an example of a computer that realizes the function of the information providing device.

Hereinafter, the information providing device, the information processing method, and the embodiment for implementing the program (hereinafter referred to as “the embodiment”) according to the present application will be described in detail with reference to the drawings. It should be noted that this embodiment does not limit the information providing device, the information processing method, and the program according to the present application.

(First Embodiment)
<Overview of information processing method>
First, with reference to FIG. 1, an outline of an information processing method performed by the information providing device 1 according to the first embodiment will be described. FIG. 1 is an explanatory diagram showing an outline of an information processing method according to the first embodiment.

The information providing device 1 is connected to the external device 100 via a network N (see FIG. 2) so as to be able to communicate with each other by wire or wirelessly.

The external device 100 is an information processing device to which various information is provided from the information providing device 1, and is realized by a server device, a cloud system, or the like. The external device 100 has data about the user to whom it is provided. Data about the user includes the attributes of the user.

User attributes include user demographics (demographic attributes), geographics (geographical attributes), behavioral attributes (behavioral attributes), and the like. For example, user-related data includes name, age, gender, family structure, place of origin (local), occupation, position, income, qualification, living style (detached house, apartment, etc.), presence or absence of a car, commuting time, commuting to school.・ Commuting route, commuter pass section (station, route, etc.), work location, frequently used station (other than the nearest station to your home / work location), lessons (location, time zone, etc.), hobbies, interests, lifestyle, etc. Includes informational data.

In addition, the data about the user may include the user's action log. The user's action log contains informational data such as search queries and actions. The search query indicates a keyword entered by the user into a search engine or the like. The action is, for example, a stepwise action (clicking, adding to a cart, pressing a purchase button, etc.) leading to a conversion (final action) such as a purchase.

The information providing device 1 is an information processing device of a business operator (predetermined business operator), and is realized by a server device, a cloud system, or the like. The business operator is a person who provides the classification model and statistical information described later to the provider. The information providing device 1 has data about the user of the business operator. The information providing device 1 generates a classification model for classifying the users of the business based on the data about the users of the business (S1).

The classification model is a model in which the users of the business are clustered without a label based on the data about the users of the business. The classification model is generated by applying an arbitrary machine learning algorithm. Arbitrary machine learning algorithms include deep learning, logistic analysis, random forests, support vector machines, decision trees, and more. Clusters classified by the classification model may include the attributes of the operator's users. The cluster classified by the classification model may be a combination of the attributes of the users of the business operator.

The information providing device 1 transmits the generated classification model to the external device 100 (S2). That is, the information providing device 1 provides the classification model to the providing destination. The information providing device 1 does not transmit personal information about the user of the business operator to the external device 100. Specifically, the information providing device 1 does not transmit the information specified by the user of the business operator to the external device 100.

The external device 100 classifies the providing user by using the classification model transmitted from the information providing device 1 (S3). That is, the external device 100 clusters the users of the provision destination using the classification model based on the data regarding the users of the provision destination. The external device 100 transmits data regarding the cluster to which the provider user belongs (hereinafter, referred to as “provider cluster”) to the information provider device 1 (S4). The destination cluster may include the attributes of the destination user. The destination cluster may be a combination of attributes of the destination user.

The information providing device 1 identifies statistical information about the user of the business operator in the providing destination cluster based on the providing destination cluster transmitted from the external device 100 (S5).

The statistical information is a score of the degree to which the attribute of the user of the business operator is satisfied. For example, the statistical information is a score indicating the possibility that the user of the business operator purchases a refrigerator or a score indicating the possibility that the user of the business operator prefers wine. User attributes (items) in the statistical information are specified, for example, by the provider. User attributes in the statistics may be set by the operator.

The information providing device 1 transmits the specified statistical information to the external device 100 (S6). That is, the information providing device 1 provides the providing destination with statistical information about the users of the business operators belonging to the providing destination cluster. The information providing device 1 does not transmit personal information about the user of the business operator to the external device 100.

In this way, the information providing device 1 transmits the classification model and the statistical information to the providing destination without transmitting the personal information about the user of the business operator. Therefore, the information providing device 1 can provide the providing destination with statistical information about the user of the providing destination and prevent the personal information of the user of the business operator from leaking to the outside.

The provider can make a proposal suitable for the user of the provider based on the provided statistical information.

<Information processing system configuration>
Next, the configuration of the information processing system 300 will be described with reference to FIG. FIG. 2 is a diagram showing a configuration example of the information processing system 300 according to the first embodiment. The information processing system 300 includes an external device 100, an information providing device 1, and a terminal device 200.

The number of each device included in the information processing system 300 shown in FIG. 2 is not limited to that shown in the figure. For example, in FIG. 2, for simplification of the illustration, only one terminal device 200 is shown, but this is merely an example and is not limited, and may be two or more.

The terminal device 200 is an information processing device used by the user. For example, the terminal device 200 is a smart device such as a smartphone or tablet terminal, a feature phone, a PC (Personal Computer), a PDA (Personal Digital Assistant), a car navigation system, a wearable device such as a smart watch or a head-mounted display (Wearable Device). , Smart glasses, etc.

Further, the terminal device 200 includes a wireless communication network such as LTE (Long Term Evolution), 4G (4th Generation), 5G (5th Generation: 5th generation mobile communication system), Bluetooth (registered trademark), and wireless LAN (Local). It can be connected to the network N via short-range wireless communication such as Area Network) and communicate with the external device 100 and the information providing device 1.

The external device 100 can acquire data about a user (user of a provider) via the terminal device 200. The information providing device 1 can acquire data about a user (user of a business operator) via a terminal device 200.

<Configuration of information providing device>
Next, the configuration of the information providing device 1 will be described with reference to FIG. FIG. 3 is a diagram showing a configuration example of the information providing device 1 according to the first embodiment. The information providing device 1 includes a communication unit 10, a storage unit 20, and a control unit 30.

The communication unit 10 is realized by, for example, a NIC (Network Interface Card) or the like. Further, the communication unit 10 is connected to the network N (see FIG. 2) by wire or wirelessly.

The storage unit 20 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as a hard disk or an optical disk.

The storage unit 20 stores data, a classification model, and statistical information about the user of the business operator. The storage unit 20 has a user information database 21, a model database 22, and a statistical information database 23.

The user information database 21 stores various information about the user of the business operator. For example, the user information database 21 stores various information such as attributes of the user of the business operator. For example, the user information database 21 has items such as "user ID (Identifier)", "age", "gender", "home", "work location", and "interest". The user ID indicates identification information for identifying the user of the business operator.

Further, the user information database 21 stores various information related to the action log of the user of the business operator. For example, the user information database 21 has items such as "user ID", "search query", and "behavior".

The user information database 21 is not limited to the above, and various information may be stored depending on the purpose. For example, the user information database 21 may store information such as the position history, search history, browsing history, purchase history, and posting history of the user of the business operator.

The model database 22 stores the classification model generated by the generation unit 32 described later.

The statistical information database 23 stores statistical information for each cluster of users of the business operator classified by the classification model. The statistical information database 23 may store a plurality of statistical information for each cluster. For example, the statistical information database 23 stores a score indicating the possibility of purchasing a refrigerator for a user of a business operator belonging to each cluster, a score indicating a possibility of preferring wine for a user of a business operator belonging to each cluster, and the like.

The control unit 30 is a controller, and is an information providing device 1 by, 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. It is realized by executing various programs (corresponding to an example of an information processing program) stored in the internal storage device of the ASIC with a storage area such as a RAM as a work area.

In the example shown in FIG. 3, the control unit 30 includes an acquisition unit 31, a generation unit 32, a specific unit 33, and a provision unit 34. The acquisition unit 31, the generation unit 32, the specific unit 33, and the provision unit 34 are not limited to this, and may be integrated or may be divided and configured.

The acquisition unit 31 acquires data about the user of the business operator from the terminal device 200 via the communication unit 10. For example, the acquisition unit 31 acquires the attributes of the user of the business operator and the action log of the user of the business operator from the terminal device 200 of the user in response to the operation of the terminal device 200 via the communication unit 10.

The acquisition unit 31 acquires the provider cluster from the external device 100 via the communication unit 10.

The generation unit 32 performs machine learning using the data about the user of the business operator acquired by the acquisition unit 31 to generate a classification model.

When the users of the business operator are clustered by the classification model, the generation unit 32 generates the classification model so that the number of users of the business operator included in each cluster becomes a predetermined number or more. The predetermined number is, for example, "10". The generation unit 32 stores the generated classification model in the model database 22.

The generation unit 32 generates statistical information in each cluster. Specifically, the generation unit 32 calculates statistical information in each cluster. The generation unit 32 stores the calculated statistical information in the statistical information database 23. The generation unit 32 calculates, for example, statistical information regarding the attributes of the user specified by the provider. The generation unit 32 may calculate statistical information regarding the attributes of the user set by the business operator. The generation unit 32 may calculate statistical information regarding a plurality of attributes.

The identification unit 33 specifies statistical information for each cluster. Specifically, the specifying unit 33 identifies the statistical information of the user of the business operator belonging to the same cluster as the providing destination cluster based on the information of the providing destination cluster acquired by the acquiring unit 31. The identification unit 33 identifies the statistical information based on the attributes of the user specified by the provider. The specifying unit 33 may specify statistical information based on the attributes of the user set by the business operator.

For example, it is assumed that the user of the business operator is classified into three clusters A to C in the vector space by the classification model, as shown in FIG. FIG. 4 is a diagram schematically showing a vector space classified by a classification model.

Then, when the acquired supply destination cluster is "cluster A", the specifying unit 33 specifies the statistical information of the user of the business operator belonging to the cluster A.

For example, when the statistical information is the score of the possibility of purchasing wine, the identification unit 33 identifies the score of the possibility of purchasing wine among the users of the business operators belonging to the cluster A.

The providing unit 34 transmits the classification model generated by the generating unit 32 to the external device 100 via the communication unit 10. That is, the providing unit 34 provides the classification model to the external device 100.

The providing unit 34 transmits data regarding the statistical information of the user of the business operator specified by the specifying unit 33 to the external device 100 via the communication unit 10. That is, the providing unit 34 provides the statistical information to the external device 100.

<Explanation of statistical information provision processing>
Next, the statistical information providing process according to the first embodiment will be described with reference to FIG. FIG. 5 is a flowchart showing the statistical information providing process according to the first embodiment.

The control unit 30 of the information providing device 1 transmits the classification model to the external device 100 (S100). The classification model may be transmitted to the external device 100 in advance.

The control unit 30 of the information providing device 1 acquires the data of the providing destination cluster from the external device 100 (S101).

The control unit 30 of the information providing device 1 identifies the statistical information of the user of the business operator who belongs to the same cluster as the acquired providing destination cluster (S102).

The control unit 30 of the information providing device 1 transmits the specified statistical information to the external device 100 (S103).

<Effect>
The information providing device 1 includes a generation unit 32, a specific unit 33, and a providing unit 34. The generation unit 32 generates a classification model for classifying the users of the business into clusters based on the data about the users of the business acquired by the business. The identification unit 33 specifies statistical information about the users of the business operator classified by the classification model for each cluster. The providing unit 34 provides the classification model and the statistical information to the providing destination.

As a result, the information providing device 1 can provide the statistical information of the users of the business belonging to the cluster to the providing destination without providing the personal information of the user of the business to the providing destination. That is, the information providing device 1 can provide useful statistical information to the providing destination while preventing the user of the business operator from being identified. The provider to whom the statistical information is provided can make a proposal suitable for the user of the provider based on the provided statistical information to the user of the provider. Therefore, for example, the provider can make a proposal that cannot be obtained from the data of the user of the provider.

The information providing device 1 includes an acquisition unit 31. The acquisition unit 31 acquires the delivery destination cluster classified by the classification model from the delivery destination. When the data of the provider cluster is acquired by the acquisition unit 31 after the classification model is provided to the provider, the provider 34 provides the statistical information of the cluster to which the user of the provider belongs to the provider.

As a result, the information providing device 1 can appropriately provide the statistical information requested by the providing destination to the providing destination. Further, the information providing device 1 can prevent unnecessary information from being provided to the providing destination.

The identification unit 33 identifies statistical information based on the attributes of the user specified by the provider.

As a result, the information providing device 1 can provide the statistical information requested by the providing destination to the providing destination.

The statistical information is a score of the degree to which the attribute of the user of the business operator is satisfied. As a result, the information providing device 1 can provide the statistical information to the providing destination in a state where the statistical information is quantified. Therefore, the provider can easily determine the usefulness of the proposal to the user of the provider.

The generation unit 32 generates a classification model in which the number of users of the business operators belonging to the cluster is equal to or greater than a predetermined number.

If the number of users of the business operator belonging to the cluster is small, the users may be identified based on the statistical information. The information providing device 1 generates a classification model in which the number of users of the business operator belonging to the cluster is equal to or more than a predetermined number, and when statistical information using the classification model is provided to the provider, the user of the business operator. Can be suppressed from being identified.

(Second Embodiment)
<Configuration of information providing device>
Next, the information providing device 1 according to the second embodiment will be described. Here, the parts different from those of the first embodiment will be mainly described. Detailed description of the same configuration and the same processing as in the first embodiment will be omitted.

The generation unit 32 in the control unit 30 of the information providing device 1 of the second embodiment clusters the users of the business operator using the generated classification model, and the number of users of the business operator included in the cluster is more than a predetermined number. If there are few clusters, the classification model is regenerated so that the number of users of the business operator included in each cluster is equal to or more than a predetermined number. The generation unit 32 changes the cluster, for example, and generates a classification model so that the number of users of the business operator included in each changed cluster becomes a predetermined number or more.

For example, it is assumed that the users of the business operator are clustered by the generated classification model, and the users of the business operator are classified into five clusters D to H on the vector space as shown in FIG. FIG. 6 is a diagram schematically showing a vector space classified by a classification model (No. 1). The predetermined number shall be "10".

The number of users of the business operator included in the clusters D, E, and H is "10" or more. However, the number of users of the business operator included in the clusters F and G is "5" and "1". In such a case, the generation unit 32 regenerates the classification model so that the number of users of the business operator included in each cluster becomes a predetermined number or more.

For example, when the division of the attribute of the user of the business operator for classifying into clusters D to H is "5 years old unit" of "age", the generation unit 32 sets the division to "10 years old unit" of "age". Generate a classification model to do.

As a result, when the users of the business operator are clustered by the regenerated classification model, for example, as shown in FIG. 7, the users of the business operator are classified into three clusters I to K on the vector space. It is classified by the regenerated classification model, and the number of users of the business operator included in each cluster G to H is "10" or more. FIG. 7 is a diagram schematically showing a vector space classified by a classification model (No. 2).

The generation unit 32 may increase (widen) the division of the attributes of the users of the business so that the number of users of the business included in each cluster becomes a predetermined number or more. Further, the generation unit 32 may reduce (narrow) the division of the attributes of the users of the business so that the number of users of the business included in each cluster becomes a predetermined number or more.

The model database 22 stores a classification model in which the number of users of the business operator included in each cluster is equal to or greater than a predetermined number.

<Model generation process>
Next, the model generation process according to the second embodiment will be described with reference to FIG. FIG. 8 is a flowchart showing a model generation process according to the second embodiment.

The control unit 30 of the information providing device 1 acquires data about the user of the business operator from the terminal device 200 via the communication unit 10 (S200). The acquired data regarding the user of the business operator is stored in the user information database 21.

The control unit 30 of the information providing device 1 generates a classification model based on the acquired data regarding the user of the business operator (S201). The control unit 30 of the information providing device 1 clusters the users of the business operator according to the generated classification model (S202).

The control unit 30 of the information providing device 1 has a case where the number of users of the business operator included in each cluster is a predetermined number or more, that is, when there is no cluster in which the number of users of the business operator is less than the predetermined number (S202: No), the generated model is stored in the model database 22 (S203).

According to the generated classification model, the control unit 30 of the information providing device 1 has a cluster in which the number of users of the business operator included in the cluster is less than a predetermined number (S202: Yes), the business operator included in each cluster. The classification model is regenerated so that the number of users of the above is equal to or greater than a predetermined number (S201).

<Effect>
The generation unit 32 has changed the cluster delimiter so that when the number of users of the business operator belonging to the cluster is less than the predetermined number, the number of users of the business operator belonging to the cluster is equal to or more than the predetermined number. Generate a classification model.

As a result, the information providing device 1 can prevent the user of the business operator from being specified when the statistical information using the classification model is provided to the providing destination.

(Modification example)
The information providing device 1 according to the modified example may set an upper limit on the number of users of the business operator included in the cluster.

The information providing device 1 according to the modified example may simultaneously transmit the classification model and the statistical information to the external device 100. In this case, the cluster of the classification model and the statistical information are linked and transmitted. The external device 100 can specify the cluster to which the provider user belongs by using the classification model, and obtain statistical information in the specified cluster. In this case as well, the personal information of the user of the business operator is not transmitted to the external device 100.

The information providing device 1 according to the modification may generate a classification model using data about a user shared by a business operator and a providing destination. As a result, the information providing device 1 can provide the statistical information requested by the providing destination to the providing destination.

The information providing device 1 according to the modification generates a generation model based on the data related to the user's attribute specified by the providing destination. As a result, the information providing device 1 can provide the statistical information requested by the providing destination to the providing destination.

(Hardware configuration)
Further, the external device 100, the information providing device 1, and the terminal device 200 according to the above-described embodiment are realized by, for example, a computer 1000 having a configuration as shown in FIG. Hereinafter, the information providing device 1 will be described as an example. FIG. 9 is a diagram showing an example of a hardware configuration. The computer 1000 is connected to the output device 1010 and the input device 1020, and the arithmetic unit 1030, the primary storage device 1040, the secondary storage device 1050, the output I / F (Interface) 1060, the input I / F 1070, and the network I / F 1080 are bused. It has a form connected by 1090.

The arithmetic unit 1030 operates based on a program stored in the primary storage device 1040 or the secondary storage device 1050, a program read from the input device 1020, or the like, and executes various processes. The arithmetic unit 1030 is realized by, 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.

The primary storage device 1040 is a memory device such as a RAM (Random Access Memory) that temporarily stores data used by the arithmetic unit 1030 for various calculations. Further, the secondary storage device 1050 is a storage device in which data used by the calculation device 1030 for various calculations and various databases are registered, and is a ROM (Read Only Memory), an HDD (Hard Disk Drive), and an SSD (Solid). State Drive), flash memory, etc. The secondary storage device 1050 may be an internal storage or an external storage. Further, the secondary storage device 1050 may be a removable storage medium such as a USB memory or an SD (Secure Digital) memory card. Further, the secondary storage device 1050 may be a cloud storage (online storage), 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 an output device 1010 that outputs various information such as a display, a projector, and a printer. For example, USB (Universal Serial Bus) or DVI. (Digital Visual Interface), HDMI (Registered Trademark) (High Definition Multimedia Interface), etc. are realized by standard connectors. Further, the input I / F 1070 is an interface for receiving information from various input devices 1020 such as a mouse, a keyboard, a keypad, a button, a scanner, and the like, and is realized by, for example, USB.

Further, 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.

Further, 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 input / output I / F.

The input device 1020 is, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), a PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), or a tape. It may be a device that reads information from a medium, a magnetic recording medium, a semiconductor memory, or the like.

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

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

For example, when the computer 1000 functions as the information providing device 1, the arithmetic unit 1030 of the computer 1000 realizes the function of the control unit 30 by executing the program loaded on the primary storage device 1040. Further, the arithmetic unit 1030 of the computer 1000 may load a program acquired from another device via the network I / F 1080 onto the primary storage device 1040 and execute the loaded program. Further, the arithmetic unit 1030 of the computer 1000 may cooperate with other devices via the network I / F 1080 to call the functions and data of the program from other programs of the other devices and use them.

(others)
Although the embodiments of the present application have been described above, the present invention is not limited to the contents of these embodiments. Further, the above-mentioned components include those that can be easily assumed by those skilled in the art, those that are substantially the same, that is, those in a so-called equal range. Furthermore, the components described above can be combined as appropriate. Further, various omissions, replacements or changes of the components can be made without departing from the gist of the above-described embodiment.

Further, among the processes described in the above-described embodiment, all or a part of the processes described as being automatically performed can be manually performed, or the processes described as being manually performed can be performed. All or part of it can be done automatically by a known method. In addition, the processing procedure, specific name, and information including various data and parameters shown in the above document and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the information shown in the figure.

Further, each component of each of the illustrated devices is a functional concept, and does not necessarily have to be physically configured as shown in the figure. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or part of them may be functionally or physically distributed / physically in arbitrary units according to various loads and usage conditions. Can be integrated and configured.

For example, the above-mentioned information providing device 1 may be realized by a plurality of server computers, or may be realized by calling an external framework or the like by API (Application Programming Interface), network computing, or the like depending on the function. The configuration can be changed flexibly.

Further, the above-described embodiments and modifications can be appropriately combined as long as the processing contents do not conflict with each other.

Further, the above-mentioned "section, module, unit" can be read as "means", "circuit" and the like. For example, the acquisition unit 31 can be read as an acquisition means or an acquisition circuit.

1 Information providing device 10 Communication unit 20 Storage unit 30 Control unit 31 Acquisition unit 32 Generation unit 33 Specific unit 34 Providing unit 100 External device 200 Terminal device 300 Information processing system

Claims (9)

A generator that generates a classification model that classifies the users into clusters based on the data about the users acquired by the predetermined business operator.
A specific part that specifies statistical information about the user classified by the classification model for each cluster, and
An information providing device including the classification model and a providing unit that provides the statistical information to a providing destination. It is provided with an acquisition unit for acquiring cluster data regarding the user of the provision destination classified by the classification model from the provision destination.
When the providing unit provides the classification model to the providing destination and then the acquisition unit acquires the data of the cluster related to the providing destination user, the providing unit obtains the statistical information of the cluster to which the providing destination user belongs. The information providing device according to claim 1, which is provided to a provider. The information providing device according to claim 1 or 2, wherein the specifying unit specifies the statistical information based on the attribute of the user designated by the providing destination. The information providing device according to claim 3, wherein the statistical information is a score of a degree of satisfying the attribute of the user. The information providing device according to any one of claims 1 to 4, wherein the generation unit generates the classification model in which the number of users belonging to the cluster is equal to or greater than a predetermined number. When the number of the users belonging to the cluster is smaller than the predetermined number, the generation unit changes the cluster division so that the number of the users belonging to the cluster is equal to or more than the predetermined number. The information providing device according to claim 5, which generates the above-mentioned classification model. The information providing device according to any one of claims 1 to 6, wherein the generation unit generates the classification model based on the attribute specified by the provider. It is an information processing method executed by the information providing device.
A generation process that generates a classification model that classifies the users into clusters based on the data about the users acquired by the predetermined business operator.
A specific process for specifying statistical information about the user classified by the classification model for each cluster, and
An information processing method having the classification model and a providing process for providing the statistical information to a providing destination. A generation procedure for generating a classification model that classifies the users into clusters based on the data about the users acquired by the predetermined business operator, and a generation procedure.
A specific procedure for specifying statistical information about the user classified by the classification model for each cluster, and
A program that causes a computer to execute the classification model and the provision procedure for providing the statistical information to a provider.

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