Information providing device, information processing method, and program

Abstract

An information providing device, an information processing method, and a program for providing information to a destination while preventing a user of a business from being identified. [Solution] The information providing device according to the present application includes a generation unit, an identification unit, and a provision unit. The generation unit generates a classification model that classifies users into clusters based on user-related data acquired by a predetermined business. The identification unit identifies, for each cluster, statistical information about the users classified by the classification model. The provision unit provides the classification model and statistical information to a destination.

Description

[Technical field]

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

[0002] Conventionally, there has been provided an online shopping mall service that allows a user to purchase items sold by a plurality of businesses. As an example of such a service, a technology is known that proposes items of trade selected according to a user's attributes. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2014-186582 A Summary of the Invention [Problem to be solved by the invention]

[0004] When proposing a trading object, the recipient can propose a trading object based on the provided information provided by the business operator. However, in this case, it is not preferable to provide the recipient with personal information of the business operator's user. For example, it is not preferable to provide the recipient with information that identifies the business operator's user.

[0005] The present application has been made in consideration of the above, and aims to provide an information providing device, an information processing method, and a program that are capable of providing useful information to a destination while preventing information that identifies an operator's user from being provided to the destination. [Means for solving the problem]

[0006] The information providing device according to the present application includes a generating unit, an identifying unit, and a providing unit. The generating unit generates a classification model for classifying users into clusters based on data related to users acquired by a predetermined business. The identifying unit identifies statistical information related to the users classified by the classification model for each cluster. The providing unit provides the classification model and the statistical information to a destination. Effect of the Invention

[0007] According to one aspect of the embodiment, it is possible to provide information to a destination while preventing a user of the business from being identified. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is an explanatory diagram showing an overview of an information processing method according to the first embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of the configuration of the information processing system according to the first embodiment. [Diagram 3] FIG. 3 is a diagram illustrating an example of the configuration of the information providing device according to the first embodiment. [Figure 4] FIG. 4 is a diagram illustrating a vector space classified by a classification model. [Diagram 5] FIG. 5 is a flowchart showing the statistical information providing process according to the first embodiment. [Figure 6] FIG. 6 is a diagram (part 1) showing a schematic diagram of a vector space classified by a classification model. [Figure 7] FIG. 7 is a schematic diagram showing a vector space classified by a classification model (part 2). [Figure 8] FIG. 8 is a flowchart showing a model generation process according to the second embodiment. [Figure 9] FIG. 9 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the information providing device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, the information providing device, the information processing method, and the program according to the present application will be described in detail with reference to the drawings. Note that the information providing device, the information processing method, and the program according to the present application are not limited to the embodiments.

[0010] (First embodiment) <Outline of information processing method> First, an overview of an information processing method performed by an information providing device 1 according to the first embodiment will be described with reference to Fig. 1. Fig. 1 is an explanatory diagram showing an overview of the information processing method according to the first embodiment.

[0011] The information providing device 1 is connected to an external device 100 via a network N (see FIG. 2) in a wired or wireless manner so as to be able to communicate with each other.

[0012] 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 related to a user of the information providing device 1. The data related to the user includes attributes of the user.

[0013] User attributes include the user's demographic, geographic, behavioral, etc. For example, user data includes information such as name, age, sex, family structure, hometown (local area), occupation, job title, income, qualifications, type of residence (detached house, apartment, etc.), whether or not the user has a car, commuting time, commuting route, commuter pass section (station, line, etc.), place of work, frequently used station (other than the station nearest to home or workplace), extracurricular activities (location, time, etc.), hobbies, interests, lifestyle, etc.

[0014] The data on the user may also include a user's action log. The user's action log includes data on information such as search queries and actions. A search query indicates a keyword that a user entered into a search engine or the like. An action is, for example, a step-by-step action (clicking, adding to cart, pressing a purchase button, etc.) that leads to a conversion (final action) such as a purchase.

[0015] The information providing device 1 is an information processing device of a business operator (a specified business operator) and is realized by a server device, a cloud system, or the like. The business operator is an entity that provides classification models and statistical information, which will be described later, to a recipient. The information providing device 1 has data on users of the business operator. The information providing device 1 generates a classification model for classifying users of the business operator based on the data on the users of the business operator (S1).

[0016] The classification model is a model that performs unlabeled clustering of the operator's users based on data about the operator's users. The classification model is generated by applying any machine learning algorithm. The any machine learning algorithm includes deep learning, logistic analysis, random forest, support vector machine, decision tree, etc. The clusters classified by the classification model may include attributes of the operator's users. The clusters classified by the classification model may be a combination of attributes of the operator's users.

[0017] 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 destination. Note that the information providing device 1 does not transmit personal information on the business's users to the external device 100. Specifically, the information providing device 1 does not transmit information that identifies the business's users to the external device 100.

[0018] The external device 100 classifies the destination users using the classification model transmitted from the information providing device 1 (S3). That is, the external device 100 clusters the destination users using the classification model based on data related to the destination users. The external device 100 transmits data related to a cluster to which the destination users belong (hereinafter referred to as a "destination cluster") to the information providing device 1 (S4). The destination cluster may include attributes of the destination users. The destination cluster may be a combination of attributes of the destination users.

[0019] The information providing device 1 identifies statistical information related to users of the business in the destination cluster based on the destination cluster transmitted from the external device 100 (S5).

[0020] The statistical information is a score of the degree to which the attributes of the business operator's users are satisfied. For example, the statistical information is a score indicating the possibility that the business operator's users will purchase a refrigerator, or a score indicating the possibility that the business operator's users will like wine. The user attributes (items) in the statistical information are specified, for example, by the provider. The user attributes in the statistical information may be set by the business operator.

[0021] 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 statistical information on the users of the business that belong to the destination cluster to the destination. Note that the information providing device 1 does not transmit personal information on the users of the business to the external device 100.

[0022] In this way, the information providing device 1 transmits the classification model and the statistical information to the destination without transmitting personal information on the business's users. Therefore, the information providing device 1 can provide the destination with statistical information on the destination's users and prevent personal information of the business's users from leaking to the outside.

[0023] The recipient can make suitable proposals to the recipient's users based on the provided statistical information.

[0024] <Configuration of information processing system> Next, a configuration of the information processing system 300 will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of the configuration 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.

[0025] The number of devices 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 the sake of simplicity, only one terminal device 200 is shown, but this is merely an example and is not limiting, and two or more devices may be included.

[0026] The terminal device 200 is an information processing device used by a user. For example, the terminal device 200 is a smart device such as a smartphone or a 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, smart glasses, etc.

[0027] In addition, the terminal device 200 can connect to a network N via a wireless communication network such as LTE (Long Term Evolution), 4G (4th Generation), or 5G (5th Generation: 5th generation mobile communication system), or via short-range wireless communication such as Bluetooth (registered trademark) or wireless LAN (Local Area Network), and communicate with an external device 100 and an information providing device 1.

[0028] The external device 100 can acquire data related to a user (a user to whom the information is to be provided) via the terminal device 200. The information providing device 1 can acquire data related to a user (a user of a business entity) via the terminal device 200.

[0029] <Configuration of information providing device> Next, the configuration of the information providing device 1 will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of the configuration 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.

[0030] The communication unit 10 is realized by, for example, a network interface card (NIC), etc. The communication unit 10 is also connected to a network N (see FIG. 2) in a wired or wireless manner.

[0031] The storage unit 20 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk.

[0032] The storage unit 20 stores data on users of the business operator, classification models, and statistical information. The storage unit 20 has a user information database 21, a model database 22, and a statistical information database .

[0033] The user information database 21 stores various information related to users of the business. For example, the user information database 21 stores various information such as attributes of users of the business. For example, the user information database 21 has items such as "User ID (Identifier)", "Age", "Gender", "Home", "Workplace", and "Interests". The user ID indicates identification information for identifying users of the business.

[0034] In addition, the user information database 21 stores various information related to the action logs of users of the business. For example, the user information database 21 has items such as "user ID", "search query", and "action".

[0035] The user information database 21 may store various information according to the purpose, not limited to the above. For example, the user information database 21 may store information such as the location history, search history, browsing history, purchase history, and posting history of users of the business.

[0036] The model database 22 stores the classification model generated by a generating unit 32, which will be described later.

[0037] 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 pieces of statistical information for each cluster. For example, the statistical information database 23 stores a score indicating the likelihood that users of the business operator belonging to each cluster will purchase a refrigerator, and a score indicating the likelihood that users of the business operator belonging to each cluster will like wine.

[0038] The control unit 30 is a controller, and is realized, for example, by a CPU (Central Processing Unit), MPU (Micro Processing Unit), ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array), etc., by executing various programs (corresponding to an example of an information processing program) stored in a storage device inside the information providing device 1 using a storage area such as a RAM as a working area.

[0039] 3, the control unit 30 includes an acquisition unit 31, a generation unit 32, a determination unit 33, and a provision unit 34. The acquisition unit 31, the generation unit 32, the determination unit 33, and the provision unit 34 are not limited to this, and may be configured as an integrated unit or may be configured as separate units.

[0040] The acquisition unit 31 acquires data related to the user of the business from the terminal device 200 via the communication unit 10. For example, the acquisition unit 31 acquires attributes of the user of the business and a behavior log of the user of the business from the terminal device 200 of the user in response to an operation of the terminal device 200 via the communication unit 10.

[0041] The acquiring unit 31 acquires the destination cluster from the external device 100 via the communication unit 10 .

[0042] The generation unit 32 performs machine learning using the data related to the business's users acquired by the acquisition unit 31, and generates a classification model.

[0043] The generation unit 32 generates the classification model such that, when the users of the business are clustered by the classification model, the number of users of the business included in each cluster is equal to or greater than a predetermined number. The predetermined number is, for example, "10." The generation unit 32 stores the generated classification model in the model database 22.

[0044] The generating unit 32 generates statistical information for each cluster. Specifically, the generating unit 32 calculates statistical information for each cluster. The generating unit 32 stores the calculated statistical information in the statistical information database 23. The generating unit 32 calculates, for example, statistical information regarding a user attribute designated by a destination. The generating unit 32 may calculate statistical information regarding a user attribute set by a business operator. The generating unit 32 may calculate statistical information regarding a plurality of attributes.

[0045] The identification unit 33 identifies statistical information for each cluster. Specifically, the identification unit 33 identifies statistical information of users of a business operator who belongs to the same cluster as the destination cluster, based on the information of the destination cluster acquired by the acquisition unit 31. The identification unit 33 identifies statistical information based on user attributes designated by the destination. Note that the identification unit 33 may identify statistical information based on user attributes set by the business operator.

[0046] For example, it is assumed that users of a business operator are classified into three clusters A to C in a vector space by the classification model, as shown in Fig. 4. Fig. 4 is a diagram illustrating a vector space classified by the classification model.

[0047] Then, when the acquired destination cluster is "cluster A", the identification unit 33 identifies the statistical information of users of the business entity belonging to cluster A.

[0048] For example, if the statistical information is a score of the likelihood of purchasing wine, the specification unit 33 specifies the score of the likelihood of purchasing wine for users of a business that belongs to cluster A.

[0049] 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.

[0050] The providing unit 34 transmits data on the statistical information of the users of the business identified by the identifying unit 33 to the external device 100 via the communication unit 10. That is, the providing unit 34 provides the external device 100 with the statistical information.

[0051] <Explanation of statistical information provision process> Next, the statistical information providing process according to the first embodiment will be described with reference to Fig. 5. Fig. 5 is a flowchart showing the statistical information providing process according to the first embodiment.

[0052] The control unit 30 of the information providing device 1 transmits the classification model to the external device 100 (S100). Note that the classification model may be transmitted to the external device 100 in advance.

[0053] The control unit 30 of the information providing device 1 acquires data of a destination cluster from the external device 100 (S101).

[0054] The control unit 30 of the information providing device 1 identifies statistical information of users of businesses that belong to the same cluster as the acquired destination cluster (S102).

[0055] The control unit 30 of the information providing device 1 transmits the specified statistical information to the external device 100 (S103).

[0056] <Effects> The information providing device 1 includes a generating unit 32, an identifying unit 33, and a providing unit 34. The generating unit 32 generates a classification model that classifies users of the business into clusters based on data on users of the business acquired by the business. The identifying unit 33 identifies statistical information on the users of the business classified by the classification model for each cluster. The providing unit 34 provides the classification model and the statistical information to a destination.

[0057] This allows the information providing device 1 to provide the destination with statistical information on the users of the business that belong to the cluster, without providing the destination with personal information of the users of the business. That is, the information providing device 1 can provide the destination with useful statistical information while preventing the users of the business from being identified. The destination to which the statistical information has been provided can make proposals suitable for the users of the destination based on the provided statistical information. Therefore, for example, the destination can make proposals that cannot be obtained from the data of the users of the destination.

[0058] The information providing device 1 includes an acquisition unit 31. The acquisition unit 31 acquires, from a destination, a destination cluster classified by a classification model. After providing the classification model to the destination, when the acquisition unit 31 acquires data of the destination cluster, the providing unit 34 provides the destination with statistical information of a cluster to which a user of the destination belongs.

[0059] This allows the information providing device 1 to appropriately provide the statistical information required by the destination to the destination, and also prevents unnecessary information from being provided to the destination.

[0060] The specification unit 33 specifies the statistical information based on the attributes of the user specified by the destination.

[0061] This allows the information providing device 1 to provide the statistical information desired by the destination to the destination.

[0062] The statistical information is a score of the degree to which the business entity satisfies the attributes of the user. This allows the information providing device 1 to provide the statistical information to the destination in a state in which the statistical information is quantified. This allows the destination to easily determine the usefulness of the proposal to the destination user.

[0063] The generation unit 32 generates a classification model in which the number of users of the business that belong to a cluster is equal to or greater than a predetermined number.

[0064] When the number of users of an operator belonging to a cluster is small, there is a risk that 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 operator belonging to the cluster is a predetermined number or more, and can suppress the identification of the users of the operator when the statistical information using the classification model is provided to the destination.

[0065] Second embodiment <Configuration of the information providing device> Next, an information providing device 1 according to a second embodiment will be described. Here, differences from the first embodiment will be mainly described. Detailed descriptions of configurations and processes similar to those of the first embodiment will be omitted.

[0066] 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 if there is a cluster in which the number of users of the business operator included in the cluster is less than a predetermined number, the generation unit 32 regenerates the classification model so that the number of users of the business operator included in each cluster is equal to or greater than the predetermined number. For example, the generation unit 32 changes the clusters, and generates a classification model so that the number of users of the business operator included in each cluster after the change is equal to or greater than the predetermined number.

[0067] For example, assume that the users of a business operator are clustered by the generated classification model and classified into five clusters D to H in the vector space as shown in Fig. 6. Fig. 6 is a diagram (part 1) that illustrates a vector space classified by the classification model. The predetermined number is assumed to be "10".

[0068] The number of users of the operators included in clusters D, E, and H is "10" or more. However, the number of users of the operators included in 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 operators included in each cluster is equal to or more than a predetermined number.

[0069] For example, when the division of the attribute of users of a business for classification into clusters D to H is "in units of 5 years" for "age", the generation unit 32 generates a classification model in which the division is "in units of 10 years" for "age".

[0070] As a result, when the operators' users are clustered by the regenerated classification model, the operators' users are classified into three clusters I to K in the vector space, for example, as shown in Fig. 7. The number of operators' users included in each of the clusters G to H classified by the regenerated classification model is all 10 or more. Fig. 7 is a diagram (part 2) that illustrates a vector space classified by the classification model.

[0071] The generation unit 32 may increase (widen) the division of the attributes of the users of the business operator so that the number of users of the business operator included in each cluster is equal to or greater than a predetermined number. The generation unit 32 may decrease (narrow) the division of the attributes of the users of the business operator so that the number of users of the business operator included in each cluster is equal to or greater than a predetermined number.

[0072] The model database 22 stores a classification model in which the number of users of the business included in each cluster is equal to or greater than a predetermined number.

[0073] <Model generation process> Next, a model generation process according to the second embodiment will be described with reference to Fig. 8. Fig. 8 is a flowchart showing the model generation process according to the second embodiment.

[0074] The control unit 30 of the information providing device 1 acquires data relating to users of the business from the terminal device 200 via the communication unit 10 (S200). The acquired data relating to users of the business is stored in the user information database 21.

[0075] The control unit 30 of the information providing device 1 generates a classification model based on the acquired data on users of the business (S201). The control unit 30 of the information providing device 1 clusters the users of the business using the generated classification model (S202).

[0076] If the number of users of the business included in each cluster is equal to or greater than a predetermined number, i.e., if there is no cluster in which the number of users of the business is less than the predetermined number (S202: No), the control unit 30 of the information providing device 1 stores the generated model in the model database 22 (S203).

[0077] If the generated classification model results in a cluster having fewer than a predetermined number of users of the business (S202: Yes), the control unit 30 of the information providing device 1 regenerates the classification model so that the number of users of the business included in each cluster is equal to or greater than the predetermined number (S201).

[0078] <Effects> If there is a cluster in which the number of users of an operator belonging to the cluster is less than a predetermined number, the generation unit 32 generates a classification model in which the division of the cluster is changed so that the number of users of the operator belonging to the cluster is equal to or greater than the predetermined number.

[0079] This makes it possible for the information providing device 1 to prevent users of the business from being identified when providing statistical information using the classification model to a destination.

[0080] (Modification) The information providing device 1 according to the modified example may set an upper limit on the number of users of an enterprise included in a cluster.

[0081] The information providing device 1 according to the modified example may transmit the classification model and the statistical information to the external device 100 at the same time. In this case, the cluster of the classification model and the statistical information are linked and transmitted. The external device 100 can use the classification model to identify a cluster to which the destination user belongs, and obtain statistical information for the identified cluster. Note that in this case as well, personal information of the business user is not transmitted to the external device 100.

[0082] The information providing device 1 according to the modified example may generate a classification model using data related to users shared among the business operator and the destination, thereby enabling the information providing device 1 to provide the destination with statistical information required by the destination.

[0083] The information providing device 1 according to the modified example generates a generative model based on data on the attributes of a user specified by a destination, thereby enabling the information providing device 1 to provide the destination with statistical information required by the destination.

[0084] (Hardware configuration) Moreover, the external device 100, the information providing device 1, and the terminal device 200 according to the above-described embodiments are realized by a computer 1000 having a configuration as shown in Fig. 9, for example. The information providing device 1 will be described below as an example. Fig. 9 is a diagram showing an example of a hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and has a configuration in which a calculation 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 connected by a bus 1090.

[0085] The arithmetic device 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050, programs read from the input device 1020, and the like, and executes various processes. The arithmetic device 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.

[0086] The primary storage device 1040 is a memory device such as a RAM (Random Access Memory) that primarily stores data used by the arithmetic device 1030 for various calculations. The secondary storage device 1050 is a storage device in which data used by the arithmetic device 1030 for various calculations and various databases are registered, and is realized by a ROM (Read Only Memory), an HDD (Hard Disk Drive), an SSD (Solid State Drive), a flash memory, or the like. The secondary storage device 1050 may be an internal storage device or an external storage device. The secondary storage device 1050 may be a removable storage medium such as a USB memory or a Secure Digital (SD) memory card. The secondary storage device 1050 may be a cloud storage device (online storage device), a NAS (Network Attached Storage), a file server, or the like.

[0087] The output I / F 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various types of information, such as a display, a projector, a printer, etc., and is realized by a connector conforming to a standard such as USB (Universal Serial Bus), DVI (Digital Visual Interface), or HDMI (registered trademark) (High Definition Multimedia Interface). 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, etc., and is realized by a USB, etc.

[0088] Furthermore, 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.

[0089] The output device 1010 and the input device 1020 may be integrated into one device, such as a touch panel. In this case, the output I / F 1060 and the input I / F 1070 may also be integrated into one device, such as an input / output I / F.

[0090] The input device 1020 may be a device that reads information from, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0091] The network I / F 1080 receives data from other devices via the network N and sends it to the arithmetic device 1030, and also transmits data generated by the arithmetic device 1030 to other devices via the network N.

[0092] 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.

[0093] For example, when the computer 1000 functions as the information providing device 1, the arithmetic unit 1030 of the computer 1000 executes a program loaded onto the primary storage device 1040 to realize the functions of the control unit 30. The arithmetic unit 1030 of the computer 1000 may also load a program acquired from another device via the network I / F 1080 onto the primary storage device 1040 and execute the loaded program. The arithmetic unit 1030 of the computer 1000 may also cooperate with the other device via the network I / F 1080 and use functions, data, etc. of a program by calling them from another program of the other device.

[0094] (others) Although the embodiments of the present application have been described above, the present invention is not limited to the contents of these embodiments. The above-described components include those that can be easily imagined by a person skilled in the art, those that are substantially the same, and those that are within the so-called equivalent range. Furthermore, the above-described components can be appropriately combined. Furthermore, various omissions, substitutions, or modifications of the components can be made without departing from the spirit of the above-described embodiments.

[0095] Furthermore, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by a known method. In addition, the information including the processing procedures, specific names, various data and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

[0096] In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc.

[0097] For example, the above-mentioned information providing device 1 may be realized by multiple server computers, and depending on the functions, the configuration can be flexibly changed, such as by calling an external framework using an API (Application Programming Interface) or network computing.

[0098] Furthermore, the above-described embodiments and modifications can be appropriately combined as long as the processing contents are not contradictory.

[0099] Moreover, the above-mentioned "section, module, unit" can be read as "means" or "circuit", etc. For example, the acquisition unit 31 can be read as acquisition means or acquisition circuit. [Explanation of symbols]

[0100] 1 Information provision device 10. Communications Department 20 Memory section 30 Control section 31 Acquisition Department 32 Generation part 33 Specific section 34 Providing Department 100 External device 200 Terminal Equipment 300 Information Processing Systems

Claims

1. A generation unit that generates a classification model for classifying users into clusters based on data related to the users acquired by a predetermined business; An identification unit that identifies, for each cluster, statistical information regarding the user classified by the classification model; a providing unit that provides the classification model and the statistical information to a destination at the same time; An information providing device comprising:

2. An information providing device as described in claim 1, wherein the clusters of the classification model and the statistical information are provided in a linked manner.

3. The information providing device according to claim 1 , wherein the specifying unit specifies the statistical information based on an attribute of the user designated by the destination.

4. The information providing device according to claim 3 , wherein the statistical information is a score of a degree to which an attribute of the user is satisfied.

5. 5. The information providing device according to claim 1, wherein the generation unit generates the classification model such that the number of the users belonging to the cluster is equal to or greater than a predetermined number.

6. 6. The information providing device according to claim 5, wherein when there is a cluster in which the number of users belonging to the cluster is less than the predetermined number, the generation unit generates the classification model in which the division of the cluster is changed so that the number of users belonging to the cluster is equal to or greater than the predetermined number.

7. 7. The information providing device according to claim 1, wherein the generating unit generates the classification model based on an attribute designated by the destination.

8. An information processing method executed by an information providing device, comprising: A generation step of generating a classification model for classifying users into clusters based on data related to the users acquired by a predetermined business; a step of identifying, for each cluster, statistical information regarding the user classified by the classification model; providing the classification model and the statistical information to a recipient at the same time; An information processing method comprising the steps of:

9. A generation step of generating a classification model for classifying users into clusters based on data related to the users acquired by a predetermined business; an identification step of identifying statistical information on the users classified by the classification model for each cluster; a provision step of simultaneously providing the classification model and the statistical information to a recipient; A program that causes a computer to execute the following.

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