Information processing apparatus, information processing method, and information processing program

Abstract

To provide an information processing apparatus, an information processing method, and an information processing program capable of improving the convenience for a user.SOLUTION: An information processing apparatus includes an acquisition unit, a generation unit, and a presentation unit. The acquisition unit acquires article information which is information on an article to be organized, and user information which is information on a user having the article. The generation unit generates, using a model that has learned a relationship between an article, an owner of the article, and a method of organizing the article, organization method information which is information indicating how to organize the article, from input information including the article information and the user information acquired by the acquisition unit. The presentation unit presents the organization method indicated by the organization method information generated by the generation unit, to an owner of the article.SELECTED DRAWING: Figure 3

Description

[Technical field]

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

[0002] As one type of service related to electronic commerce, there is known a service that mediates the buying and selling of items between users, such as an auction service or a flea market service (hereinafter, sometimes referred to as an item buying and selling mediation service). As a technology related to the item buying and selling mediation service, for example, Patent Document 1 proposes a technology that simplifies the user's information input work when listing an item (for example, see Patent Document 1).

[0003] In the technology described in Patent Document 1, when a user requests to use information on an item previously listed by a user when listing a new item, a listing screen is displayed to the user with the information on that item embedded as default information. This allows the default information embedded in the listing screen to be used when registering information on the new item. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2002-163492 A Summary of the Invention [Problem to be solved by the invention]

[0005] While the above-described conventional technology can reduce the amount of input work required when a user puts up a new item for sale, there is still room for improvement in terms of further improving user convenience.

[0006] The present application has been made in consideration of the above, and has an object to provide an information processing device, an information processing method, and an information processing program that can improve user convenience. [Means for solving the problem]

[0007] The information processing device according to the present application includes an acquisition unit, a generation unit, and a presentation unit. The acquisition unit acquires organized item information, which is information on the items to be organized, and user information, which is information on a user who owns the items to be organized. The generation unit generates organizing method information, which is information indicating a method of organizing the items to be organized, from input information including the organized item information and user information acquired by the acquisition unit, using a model that has learned the relationship between the items, the owners of the items, and the organizing methods of the items. The presentation unit presents the organizing method indicated by the organizing method information generated by the generation unit to the owner of the items to be organized. Effect of the Invention

[0008] According to one aspect of the embodiment, an effect is achieved in that it is possible to improve convenience for users. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of the configuration of an information processing system according to the embodiment. [Diagram 3] FIG. 3 is a diagram illustrating an example of the configuration of a terminal device according to the embodiment. [Figure 4] FIG. 4 is a diagram showing an example of an item organizing proposal screen showing an organizing method for each item to be organized, which is displayed on the terminal device according to the embodiment. [Diagram 5] FIG. 5 is a flowchart illustrating an example of information processing by the processing unit of the terminal device according to the embodiment. [Figure 6] FIG. 6 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of a terminal device according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, the information processing device, the information processing method, and the information processing program according to the present application (hereinafter, referred to as "embodiments") will be described in detail with reference to the drawings. Note that the information processing device, the information processing method, and the information processing program according to the present application are not limited to these embodiments. In addition, each embodiment can be appropriately combined as long as the processing contents are not contradictory. In addition, the same parts in each of the following embodiments are given the same reference numerals, and duplicated explanations will be omitted.

[0011] [1. An example of information processing] First, an example of information processing according to the embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of information processing according to the embodiment.

[0012] 1 has installed thereon a belongings organization app, which is an application program that presents a method for organizing items to be organized to a user U. The terminal device 1 having the belongings organization app installed thereon is an example of an information processing device.

[0013] The belongings sorting app can send and receive information between an item sales intermediary site 2, a used goods purchase site 3, etc. via an API (Application Programming Interface), but it may also send and receive information between an item sales intermediary site 2, a used goods purchase site 3, etc. without using an API.

[0014] The item trading intermediation site 2 is a site that provides an item trading intermediation service, which is one of the online services, and is realized by one or more servers or cloud systems, etc. The item trading intermediation service is a flea market-style electronic commerce service or an auction-style electronic commerce service, etc.

[0015] Flea market-style electronic commerce and auction-style electronic commerce services are CtoC (C2C) electronic commerce services between users U. In flea market-style electronic commerce, the selling user U determines the selling price of an item, and if the buying user agrees to that selling price, the transaction for the item is completed.

[0016] An auction-style electronic commerce service is an electronic commerce service in which a prospective purchaser proposes a price, and a transaction for the item is concluded with the bidder who proposes a price that satisfies predetermined conditions (e.g., the highest bid). A user U of the terminal device 1 can sell an item he or she owns to another user through a flea market-style electronic commerce service or an auction-style electronic commerce service.

[0017] The secondhand goods buying site 3 is a site that provides a secondhand goods buying service, which is one of the online services, and is realized by one or more servers or a cloud system, etc. The secondhand goods buying service is a CtoB (Consumer to Business) electronic commerce service, and by using this service, a user U can have his / her own items bought by a secondhand goods buying company.

[0018] 1, the terminal device 1 acquires user information, which is information about a user U who has items to be organized, by using a function of a belongings organization app (step S1). For example, the terminal device 1 acquires the information about the user U from an external information processing device or an internal storage unit.

[0019] The information of the user U is, for example, information indicating a persona related to organization of the user U. The persona related to organization of the user U is a character image of the user U related to organization, and hereinafter, the persona related to organization may be referred to as an organization persona.

[0020] The types of organizing personas include various types of people such as someone who does not want to put in the effort of organizing the items and is happy to sell the items at a low price, someone who does not want to put in the effort of organizing the items and wants to sell them at a high price, someone who is happy to take the effort of organizing the items but wants to sell them at a high price, and someone who is happy to take the effort and time to organize the items and wants to sell them at a high price, but is not limited to these examples.

[0021] The terminal device 1 can estimate the sorting persona of the user U based on, for example, one or more pieces of information among the attribute information and the behavioral history of the user U. The attribute information of the user U includes, for example, information indicating demographic attributes indicating the gender, age, occupation, place of residence, family structure, etc. of the user U, and information indicating demographic attributes indicating the interests, etc. of the user U.

[0022] User U's behavioral history includes, for example, a purchase history of various items, and the purchase history of the items includes, for example, information indicating the purchase frequency of various items, information indicating the elapsed time since the last purchase of various items, etc.

[0023] For example, the terminal device 1 uses a persona estimation model to estimate a cleaning persona of the user U. The persona estimation model estimates a persona related to cleaning of the user U using one or more pieces of information such as attribute information and behavioral history of the user U as input information.

[0024] The persona estimation model, for example, calculates the score of the persona related to organization of the user U for each type of persona, and estimates the persona type with the highest score or a type with a score equal to or greater than a threshold as the persona related to organization of the user U. The higher the score, the more likely it is to be a persona of the user U. The persona estimation model is generated by learning using learning information including, for each person, one or more pieces of attribute information and behavioral history, and information indicating the type of organization persona.

[0025] The persona estimation model is, for example, a model generated by machine learning, for example, by machine learning using a neural network such as a convolutional neural network, a recurrent neural network, or a deep neural network, but is not limited to such examples.

[0026] For example, the persona estimation model may be generated using machine learning with a learning algorithm such as a gradient boosting decision tree (GBDT), linear regression, or logistic regression instead of a neural network. The persona estimation model may also be a language model, which will be described later.

[0027] Furthermore, the information on the user U may be a persona of the user U instead of or in addition to the persona related to organization of the user U. The persona of the user U is information that represents an image of the user U, and is indicated by, for example, one or more pieces of information among the attribute information and the behavioral history of the user U.

[0028] Next, the terminal device 1 acquires information on items to be organized, which is information on items to be organized, by using a function of the belongings organization application (step S2). For example, the terminal device 1 acquires the information on items to be organized from information input or selected by the user U through the operation of the terminal device 1.

[0029] In step S2, the terminal device 1 receives information on the items to be organized that is input or selected by the user U operating the terminal device 1, for example, and acquires the received information on the items to be organized as information on the items to be organized.

[0030] Furthermore, the terminal device 1 receives, through a function of the belongings organization app, image information that is information on images of items to be organized that are captured by an internal imaging unit through operation of the terminal device 1 by the user U. The terminal device 1 acquires, as organized item information, information on the items to be organized that are identified by accepted image information that is the accepted image information.

[0031] The terminal device 1, for example, transmits the received image information to an external information processing device, causes the external information processing device to extract information on the organized items from the received image information, and acquires the extracted information on the organized items from the external information processing device as organized item information. The external information processing device, for example, has an item identification model that inputs image information as input information and outputs information on the organized items, and extracts the information on the organized items from the received image information using the item identification model.

[0032] The item identification model is a model generated by machine learning, for example, but not limited to, machine learning using a neural network. For example, the item identification model may be generated using machine learning using a learning algorithm such as GBDT, linear regression, or logistic regression instead of a neural network.

[0033] The item identification model is generated using learning information including, for example, image information and item information. In the learning information, the item information is used as a label. The item identification model may be included in a belongings organization app.

[0034] In addition, the terminal device 1 can also send a similar image search request including the received image information to an external image search server, and obtain organized item information from item information on a web page that includes a similar image included in the similar image search results sent from the image search server.

[0035] In step S1, the terminal device 1 can also acquire, for example, from an external information processing device or an internal storage unit, product purchase history information that is information on the product purchase history of the user U, and extract information on the organized products from the acquired product purchase history information. In this case, the terminal device 1 acquires the extracted information on the organized products as organized product information.

[0036] The information on the organized items extracted by the terminal device 1 from the item purchase history information may be all items included in the item purchase history information, or may be the same item that the user U purchased in a predetermined period (e.g., a period of one day or one week). Also, the information on the organized items extracted by the terminal device 1 from the item purchase history information may be the same item that the user U purchased multiple times in a predetermined period.

[0037] The terminal device 1 can also use the organized goods estimation model to extract information on organized goods from the goods purchase history information. The organized goods estimation model receives, for example, user information, information identifying the goods, and information indicating the period of time since the goods were purchased, and outputs a score indicating the likelihood that the goods are organized goods. The higher the likelihood that the goods are organized, the higher the score.

[0038] The terminal device 1 inputs information including, for example, user information, information identifying an item included in the item purchase history information, and information indicating the period of time that has elapsed since the item was purchased into a sorting item estimation model, and determines as a sorting item an item whose score output from the sorting item estimation model is equal to or greater than a threshold value.

[0039] The sorting item estimation model is generated using learning information including, for example, user information, information identifying the item, information indicating the time period since the item was purchased, and information indicating whether the item has become a sorting item. The information indicating whether the item has become a sorting item is label information, and for example, 1 is set if the item has become a sorting item, and 0 is set if not.

[0040] The organizing item estimation model is a model generated by machine learning, for example, but not limited to, machine learning using a neural network. For example, the organizing item estimation model may be generated using machine learning using a learning algorithm such as GBDT, linear regression, or logistic regression instead of a neural network.

[0041] The terminal device 1 can display information on one or more items obtained by an item identification model, a similar image search result, or a sorting item estimation model, etc., as information on one or more candidate items for sorting, and can also obtain information on a candidate item for sorting selected by a user U from the one or more candidate items for sorting as information on the items for sorting.

[0042] Next, the terminal device 1 uses the function of the belongings organizing app to generate organizing method information, which is information indicating the organizing method of the items to be organized indicated by the organizing item information, from the input information including the user information acquired in step S1 and the organizing item information acquired in step S2 (step S3).

[0043] The sorting method determination model is a model that learns the relationship between the item, the owner of the item, and the sorting method of the item. The types of sorting methods of the items include, but are not limited to, sorting using a merchandise buying and selling intermediary service, sorting using a used goods buying service, and sorting using a waste collection service. The waste collection service includes, but is not limited to, waste collection services mainly provided by municipalities and waste collection services mainly provided by businesses.

[0044] In addition, the type of item sorting method may be a type for each item buying and selling intermediation service if there are multiple item buying and selling intermediation services, may be a type for each used item buying service if there are multiple secondhand goods buying services, or may be a type for each waste collection service if there are multiple waste collection services.

[0045] The terminal device 1 inputs the input information including the user information and organizing item information acquired in steps S1 and S2 to the organizing method determination model, and performs a process of acquiring organizing method information output from the organizing method determination model for each organizing item information (for each organizing item). The organizing method determination model is generated using learning information including, for example, item information, item owner information, and information indicating the organizing method of the item for each item.

[0046] For example, the organizing method determination model calculates a score for each type of organizing method for organizing items based on input information including user information and organizing item information acquired in steps S1 and S2, and outputs information indicating the type of organizing method with the highest score that is above a threshold as organizing method information.

[0047] The organizing method determination model can also calculate a score for each type of organizing method for organizing items based on input information including the user information and organizing item information acquired in steps S1 and S2, and output information indicating the organizing methods for the types with scores equal to or greater than a threshold as organizing method information. If there are multiple types with scores equal to or greater than the threshold, organizing method information including information indicating multiple types of organizing methods is output from the organizing method determination model.

[0048] The learning information is, for example, information obtained from a questionnaire about organizing methods filled out by the owner of the item. For example, the information included in the learning information is information collected by having the owner of the item (including user U) answer questions in a questionnaire format about the items they want to organize and the organizing method they want to use, or information obtained from such information.

[0049] The information contained in the learning information may be information obtained based on past history instead of or in addition to the information described above. In this case, the information contained in the learning information may include, for example, information about the owner of the organized item, information identifying the item, and information indicating how the item was organized.

[0050] The organizing method determination model is a model generated by machine learning, for example, but not limited to, machine learning using a neural network. For example, the organizing method determination model may be generated using machine learning using a learning algorithm such as GBDT, linear regression, or logistic regression instead of a neural network.

[0051] The organizing method determination model may be a language model. The language model is, for example, a model such as a transformer that is trained to estimate and output the next token from an input token string. Such a language model is stored in an internal storage unit or an external information processing device, and is created independently by an operator of the information processing device (not shown). It is preferable that the information input to the language model is trained so as not to be used as a new answer, thereby concealing the input information such as personal information.

[0052] In this case, the language model takes as input information, for example, information (instruction information) such as the string "Please tell us the appropriate organizing method when user U, as indicated by the user information below, organizes the items to be organized, as indicated by the organizing item information below.", as well as information including user information and organizing item information, and outputs organizing method information.

[0053] The terminal device 1 can also input information further including information on related items that are the same items or similar items as the organized items in the services corresponding to various organizing methods to the language model as input information, and use the information output from the language model as organizing method information. In this case, the instruction information input to the language model further includes information such as the character string "Please refer to the information on related items" and further includes information on the related items as input information.

[0054] Next, the terminal device 1 presents the organizing method indicated by the organizing method information generated in step S3 to the user U who is the owner of the items to be organized (step S4). For example, the terminal device 1 presents the organizing method indicated by the organizing method information generated in step S3 to the user U by displaying information indicating the organizing method indicated by the organizing method information generated in step S3.

[0055] 1, perfume A, baby tableware H, and washing machine C are shown as items to be organized in terminal device 1, and methods for organizing each item are shown. For example, the method for organizing perfume A is shown to be using a product buying and selling intermediary service, the method for organizing baby tableware H is shown to be using a waste collection service, and the method for organizing washing machine C is shown to be using a secondhand goods buying service.

[0056] In this way, the terminal device 1 acquires organizing item information, which is information on the items to be organized, and user information, which is information on the user who owns the items to be organized, and generates organizing method information, which is information indicating how to organize the items to be organized, from input information including the organizing item information and the user information using a model that has learned the relationship between the items, the owners of the items, and the organizing methods of the items, and presents the organizing method indicated by the generated organizing method information to the owner of the items to be organized. In this way, the terminal device 1, as an information processing device, can improve the convenience of the user U.

[0057] The configuration of an information processing system including the terminal device 1 that performs such processing, the item buying and selling intermediation site 2, and the secondhand goods buying and selling site 3 will be described in detail below.

[0058] 2. Configuration of the Information Processing System Fig. 2 is a diagram showing an example of the configuration of an information processing system according to an embodiment. As shown in Fig. 2, the information processing system 100 according to an embodiment includes a plurality of terminal devices 1, an item buying and selling intermediary site 2, a secondhand goods buying and selling site 3, and an information processing device 4. The item buying and selling intermediary site 2, the secondhand goods buying and selling site 3, and the information processing device 4 are sites of the same operator as the operator that provides the belongings organization app.

[0059] The multiple terminal devices 1 are used by different users U. The terminal devices 1 are, for example, a notebook PC (Personal Computer), a desktop PC, a smartphone, a tablet PC, a wearable device, or a car navigation device compatible with AppleCarPlay (registered trademark). The wearable device is, for example, smart glasses or a smart watch, but is not limited to such examples.

[0060] The terminal device 1, the item buying and selling intermediary site 2, the secondhand goods buying and selling site 3, and the information processing device 4 are each connected to each other via a network N in a wired or wireless manner so as to be able to communicate with each other. Note that the information processing system 100 shown in Fig. 2 may also include an item buying and selling intermediary site, a secondhand goods buying and selling site, and an information processing device, etc., provided by a business operator other than the business operator that provides the belongings organization app.

[0061] The network N includes, for example, a Wide Area Network (WAN) such as the Internet and mobile communication networks such as Long Term Evolution (LTE), 4th Generation (4G), and 5th Generation (5G: fifth generation mobile communication system).

[0062] The terminal device 1 can connect to a network N via short-range wireless communication such as a mobile communication network, Bluetooth (registered trademark), or wireless LAN (Local Area Network), and can communicate with an item buying and selling intermediation site 2, a used goods buying and selling site 3, an information processing device 4, etc.

[0063] [3. Terminal Device 1] Fig. 3 is a diagram showing an example of the configuration of the terminal device 1 according to the embodiment. As shown in Fig. 3, the terminal device 1 according to the embodiment includes a communication unit 10, a display unit 11, an operation unit 12, an audio input unit 13, an audio output unit 14, an imaging unit 15, a sensor unit 16, a storage unit 17, and a processing unit 18.

[0064] [3.1. Communication unit 10] The communication unit 10 is realized by, for example, a communication module, a NIC (Network Interface Card), etc. The communication unit 10 is connected to a network N by wire or wirelessly, and transmits and receives information to and from an item buying and selling intermediary site 2, a used item buying and selling site 3, an information processing device 4, etc. via the network N.

[0065] [3.2. Display section 11] The display unit 11 is, for example, an LCD (Liquid Crystal Display) or an organic EL (Electro Luminescence) display.

[0066] [3.3. Operation unit 12] The operation unit 12 includes, for example, a keyboard including keys for inputting letters, numbers, and spaces, an enter key, and arrow keys, a mouse, a power button, etc. When the display unit 11 is a display device that is a touch panel display, the operation unit 12 may include a touch panel.

[0067] [3.4. Audio input unit 13] The voice input unit 13 converts a voice signal, which is a voice signal uttered by the user U, into a digital signal, and outputs the converted digital signal, which is a voice digital signal, as voice information to the processing unit 18. The voice input unit 13 includes, for example, a microphone and an AD (Analog to Digital) converter that converts the voice signal, which is an electrical analog signal output from the microphone, into a digital signal.

[0068] [3.5. Audio output unit 14] The audio output unit 14 includes, for example, a DA (Digital to Analog) converter that converts a digital audio signal, which is the audio information output from the processing unit 18, into an analog audio signal, and a speaker that converts the analog audio signal output from the DA converter into sound and outputs it.

[0069] [3.6. Imaging unit 15] The imaging unit 15 is an image sensor (camera) that captures an image of a subject. For example, the imaging unit 15 is a CMOS (Complementary Metal Oxide Semiconductor) image sensor or a CCD (Charge-Coupled Device) image sensor. The imaging unit 15 is not limited to a built-in camera, and may be a wireless camera capable of communicating with the terminal device 1 or an external camera such as a Web camera.

[0070] [3.7. Sensor section 16] The sensor unit 16 includes a position sensor, a gyro sensor, an acceleration sensor, a geomagnetic sensor, an illuminance sensor, an atmospheric pressure sensor, a biosensor, etc. The position sensor detects, for example, the position of the terminal device 1, which is the current position of the user U, and outputs information indicating the detected current position of the user U to the processing unit 18. The position sensor receives a plurality of positioning signals transmitted from a plurality of positioning satellites in the Global Navigation Satellite System (GNSS), and detects the current position of the user U based on the received plurality of positioning signals.

[0071] The gyro sensor is a sensor that detects the attitude of the terminal device 1, such as the tilt and rotation. The acceleration sensor is a sensor that detects the acceleration of the terminal device 1. The geomagnetic sensor is a sensor that detects geomagnetism. The illuminance sensor is a sensor that detects illuminance indicating the brightness or darkness around the terminal device 1. The air pressure sensor is a sensor that detects the air pressure around the terminal device 1.

[0072] The biosensor is, for example, a heartbeat sensor, a blood pressure sensor, etc. The heartbeat sensor detects the heart rate and the like of the user U. The blood pressure sensor detects the blood pressure of the user U.

[0073] [3.8. Storage section 17] The storage unit 17 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.

[0074] Various types of information are stored in the storage unit 17. For example, the storage unit 17 stores information on captured images captured by the imaging unit 15, information on the operation history of the user U, detection results by the sensor unit 16, and the like.

[0075] The storage unit 17 also stores information about the user U. The information about the user U is, for example, one or more pieces of attribute information and behavioral history of the user U, and information indicating an organizing persona that is a persona related to organizing of the user U.

[0076] The attribute information of user U is information on the attributes of user U, and includes psychographic attribute information, demographic attribute information, etc. Demographic attributes are, for example, gender, age, occupation, place of residence, family structure, etc., and psychographic attributes are interests such as travel, clothes, cars, religion, etc., lifestyle, thoughts, and ideological tendencies, etc.

[0077] The behavior history of the user U includes, for example, a movement history by the user U and a behavior history of the user U. Information on the movement history by the user U includes, for example, information on the route traveled by the user U and information on the places visited by the user U.

[0078] The behavioral history of the user U includes, for example, the purchase history of the user U, the search history of the user U, and the browsing history of the user U. The purchase history of the user U includes, for example, the purchase history of various items by the user U, and the purchase history of items includes, for example, information indicating the purchase frequency of various items, information indicating the elapsed time since the last purchase of various items, and the like.

[0079] The search history of the user U includes, for example, a search history of content by the user U in a web search service, etc. The browsing history of the user U includes, for example, a browsing history of content by the user U in an online service, etc.

[0080] The organizing persona is, for example, a person profile related to organizing of the user U. The types of organizing personas include, for example, a person who does not want to take the time to organize the items and is willing to sell the items at a low price, a person who does not want to take the time to organize the items and is willing to sell the items at a high price, a person who is willing to take the time to organize the items but is willing to sell the items at a high price, and a person who is willing to take the time and effort to organize the items and is willing to sell the items at a high price, but is not limited to such examples.

[0081] The memory unit 17 also stores information transmitted from the item buying and selling intermediary site 2, the used goods buying and selling site 3, and other external devices such as the information processing device 4, and acquired by the acquisition unit 30 of the processing unit 18 (described later) via the network N and the communication unit 10.

[0082] [3.9. Processing section 18] The processing unit 18 is a controller, and is realized, for example, by a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) executing various programs stored in a storage device inside the terminal device 1 using the RAM as a working area.

[0083] Furthermore, the processing unit 18 may be realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The processing unit 18 includes an acquisition unit 30, a reception unit 31, an estimation unit 32, an extraction unit 33, a generation unit 34, and a presentation unit 35. The acquisition unit 30, the reception unit 31, the estimation unit 32, the extraction unit 33, the generation unit 34, and the presentation unit 35 are realized by, for example, a belongings organization application (corresponding to an example of an information processing program).

[0084] [3.9.1. Acquisition part 30] The acquisition unit 30 acquires various pieces of information. The acquisition unit 30 acquires various pieces of information from the storage unit 17. The acquisition unit 30 acquires a detection result by the sensor unit 16, and causes the storage unit 17 to store the acquired detection result.

[0085] The acquisition unit 30 can receive various information from external information processing devices via the communication unit 10. The acquisition unit 30 causes the storage unit 17 to store the various information received from the external information processing devices including the information processing device 4.

[0086] The acquisition unit 30 also acquires various information from the storage unit 17. For example, the acquisition unit 30 acquires organized item information, which is information on the items to be organized. The acquisition unit 30 acquires the organized item information from information input or selected by the user U operating the operation unit 12, or acquires information on the items to be organized accepted by the acceptance unit 31 as the organized item information.

[0087] The acquisition unit 30 also acquires, as organized item information, information on the organized items identified by received image information, which is image information accepted by the acceptance unit 31. For example, the acquisition unit 30 transmits the received image information to an external information processing device via the communication unit 10, causes the external information processing device to extract information on the organized items from the received image information, and acquires the extracted information on the organized items from the external information processing device via the communication unit 10 as organized item information.

[0088] The external information processing device has, for example, an item specifying model that receives image information as input information and outputs information on the items to be organized, and extracts information on the items to be organized from the received image information using the item specifying model.

[0089] The item identification model is a model generated by machine learning, for example, but not limited to, machine learning using a neural network. For example, the item identification model may be generated using machine learning using a learning algorithm such as GBDT, linear regression, or logistic regression instead of a neural network.

[0090] The item identification model is generated using learning information including, for example, image information and item information. In the learning information, the item information is used as a label. The item identification model may be included in the acquisition unit 30.

[0091] In addition, the acquisition unit 30 can send a similar image search request including received image information to an external image search server via the communication unit 10, and acquire organized item information via the communication unit 10 from information about items on a web page that includes similar images included in the similar image search results sent from the image search server.

[0092] The acquisition unit 30 also acquires, as organized item information, information on the organized items extracted by the extraction unit 33. For example, the acquisition unit 30 acquires item purchase history information, which is information on the purchase history of items by the user U, from an external information processing device or an internal storage unit, and acquires, from the extraction unit 33, information on the organized items extracted by the extraction unit 33 from the acquired item purchase history information, as organized item information.

[0093] The acquisition unit 30 can also acquire information on one or more items obtained by an item identification model, a similar image search result, or a sorted item estimation model, etc., and information on an item selected by a user U from one or more items displayed on the display unit 11 by the presentation unit 35, as information on sorted items.

[0094] The acquisition unit 30 also acquires user information, which is information about the user U who has items to organize. For example, the acquisition unit 30 acquires information indicating the persona of the user U regarding organization estimated by the estimation unit 32 from the estimation unit 32 as the user information. The acquisition unit 30 can also acquire one or more pieces of information of the attribute information and the behavioral history of the user U from the storage unit 17 as the user information.

[0095] [3.9.2. Reception Unit 31] The reception unit 31 receives various inputs and selections. For example, the reception unit 31 receives information on items to be organized that is input or selected by the user U operating the operation unit 12.

[0096] The reception unit 31 also receives image information that is information on an image of the items to be organized. For example, the reception unit 31 receives image information that is information on an image of the items to be organized that is captured by the imaging unit 15 through an operation of the operation unit 12 by the user U.

[0097] Furthermore, the reception unit 31 receives, as an item to be organized, a candidate item to be organized selected by the user U from among one or more candidate items to be organized displayed on the display unit 11.

[0098] [3.9.3. Estimation part 32] The estimation unit 32 can estimate the organizing persona of the user U based on, for example, one or more pieces of information among the attribute information and the behavioral history of the user U. The estimation unit 32 stores information indicating the estimated organizing persona of the user U in the storage unit 17 as information of the user U.

[0099] For example, the estimation unit 32 uses a persona estimation model to estimate the organizing persona of the user U. The persona estimation model estimates the persona of the user U regarding organizing by using one or more pieces of information such as attribute information and behavioral history of the user U as input information.

[0100] The persona estimation model, for example, calculates the score of the persona related to organization of the user U for each type of persona, and estimates the persona type with the highest score or a type with a score equal to or greater than a threshold as the persona related to organization of the user U. The higher the score, the more likely it is to be a persona of the user U. The persona estimation model is generated by learning using learning information including, for each person, one or more pieces of attribute information and behavioral history, and information indicating the type of organization persona.

[0101] The persona estimation model is, for example, a model generated by machine learning, for example, by machine learning using a neural network such as a convolutional neural network, a recurrent neural network, or a deep neural network, but is not limited to such examples.

[0102] For example, the persona estimation model may be generated using machine learning with a learning algorithm such as GBDT, linear regression, or logistic regression instead of a neural network. Also, the persona estimation model may be a language model, which will be described later.

[0103] [3.9.4. Extraction part 33] The extraction unit 33 extracts information on the items to be organized from item purchase history information, which is information on the purchase history of items acquired by the acquisition unit 30.

[0104] The information on the organized items extracted from the item purchase history information by the extraction unit 33 may be all items included in the item purchase history information, or may be the same item that the user U purchased multiple times in a predetermined period (e.g., a period of one day or one week). Also, the information on the organized items extracted from the item purchase history information by the terminal device 1 may be the same item that the user U purchased multiple times in a predetermined period.

[0105] The extraction unit 33 can also extract information on organized items from the item purchase history information using a organized item estimation model. The organized item estimation model receives, for example, user information, information identifying the item, and information indicating the period of time since the item was purchased, and outputs a score indicating the likelihood that the item is an organized item. The higher the likelihood that the item is an organized item, the higher the score.

[0106] The extraction unit 33 inputs information including, for example, user information, information identifying an item included in the item purchase history information, and information indicating the period of time that has elapsed since the item was purchased into a sorting item estimation model, and determines as a sorting item an item whose score output from the sorting item estimation model is equal to or greater than a threshold value.

[0107] The sorting item estimation model is generated using learning information including, for example, user information, information identifying the item, information indicating the time period since the item was purchased, and information indicating whether the item has become a sorting item. The information indicating whether the item has become a sorting item is label information, and for example, 1 is set if the item has become a sorting item, and 0 is set if not.

[0108] The organizing item estimation model is a model generated by machine learning, for example, but not limited to, machine learning using a neural network. For example, the organizing item estimation model may be generated using machine learning using a learning algorithm such as GBDT, linear regression, or logistic regression instead of a neural network.

[0109] [3.9.5. Generation unit 34] The generating unit 34 generates various information. For example, the generating unit 34 generates organizing method information, which is information indicating a method of organizing the organizing items, from input information including the user information and organizing item information acquired by the acquiring unit 30, using a model that has learned the relationship between the items, the owners of the items, and the organizing methods of the items.

[0110] The sorting method determination model is a model that learns the relationship between the item, the owner of the item, and the sorting method of the item. The types of sorting methods of the items include, but are not limited to, sorting using a merchandise buying and selling intermediary service, sorting using a used goods buying service, sorting using a waste collection service, etc.

[0111] In addition, the type of item sorting method may be a type for each item buying and selling intermediation service if there are multiple item buying and selling intermediation services, may be a type for each used item buying service if there are multiple secondhand goods buying services, or may be a type for each waste collection service if there are multiple waste collection services.

[0112] The generating unit 34 inputs the input information including the user information and organized item information acquired by the acquiring unit 30 into the organizing method determination model, and performs a process for the organized item information (for each organized item) to acquire organizing method information output from the organizing method determination model. Such an organizing method determination model is generated using learning information including, for example, information on the item, information on the owner of the item, and information indicating the organizing method of the item for each item.

[0113] Such an organizing method judgment model calculates a score for each type of organizing method for organizing items based on input information including user information and organizing item information acquired by the acquisition unit 30, and outputs information indicating the type of organizing method having the highest score above a threshold as organizing method information.

[0114] The organizing method determination model can also calculate a score for each type of organizing method for organizing items based on input information including user information and organizing item information acquired by the acquisition unit 30, and output information indicating the organizing methods for the types with scores equal to or greater than a threshold as organizing method information. When there are multiple types with scores equal to or greater than the threshold, organizing method information including information indicating multiple types of organizing methods is output from the organizing method determination model.

[0115] The learning information is, for example, information obtained from a questionnaire about organizing methods filled out by the owner of the item. For example, the information included in the learning information is information collected by having the owner of the item (including user U) answer questions in a questionnaire format about the items they want to organize and the organizing method they want to use, or information obtained from such information.

[0116] The information contained in the learning information may be information obtained based on past history instead of or in addition to the information described above. In this case, the information contained in the learning information may include, for example, information about the owner of the organized item, information identifying the item, and information indicating how the item was organized.

[0117] The organizing method determination model is a model generated by machine learning, for example, but not limited to, machine learning using a neural network. For example, the organizing method determination model may be generated using machine learning using a learning algorithm such as GBDT, linear regression, or logistic regression instead of a neural network.

[0118] The organizing method determination model may be a language model. The language model is, for example, a model such as a transformer that is trained to estimate and output the next token from an input token string. Such a language model is stored in an internal storage unit or an external information processing device, and is created independently by the operator of the information processing device 4. It is preferable that the information input to the language model is trained so as not to be used as a new answer, thereby concealing the input information such as personal information.

[0119] In this case, the language model takes as input information, for example, information (instruction information) such as the string "Please tell us the appropriate organizing method when user U, as indicated by the user information below, organizes the items to be organized, as indicated by the organizing item information below.", as well as information including user information and organizing item information, and outputs organizing method information.

[0120] The generation unit 34 can also input information further including information on related items that are the same items or similar items as the organized items in the services corresponding to various organizing methods to the language model as input information, and use the information output from the language model as organizing method information. In this case, the instruction information input to the language model further includes, for example, the character string "Please refer to the information on related items" and further includes information on the related items as input information.

[0121] [3.9.6. Presentation part 35] The presentation unit 35 presents the organizing method indicated by the organizing method information generated by the generation unit 34 to the user U who is the owner of the item to be organized.

[0122] For example, the presentation unit 35 presents to the user U the organizing method indicated in the organizing method information generated by the generation unit 34 by displaying information indicating the organizing method indicated in the organizing method information generated by the generation unit 34 on the display unit 11.

[0123] Furthermore, the presentation unit 35 can display on the display unit 11 information on one or more items obtained by the item identification model, the similar image search result, or the organized item estimation model as information on one or more candidates for organized items.

[0124] 4 is a diagram showing an example of an item organizing proposal screen showing an organizing method for each item to be organized, which is displayed on the terminal device 1 according to the embodiment. The item organizing proposal screen 60 shown in FIG. 4 includes a button 61 for purchasing items to be organized and a list 62 of items to be organized.

[0125] The sorting item purchase buttons 61 include an image capture button 611, an image acquisition button 612, a barcode button 613, and a purchase history button 614, and these buttons are selected by the user U operating the operation unit 12.

[0126] The image capturing button 611 is a button for starting the image capturing unit 15. When the user U operates the operation unit 12 to select the image capturing button 611, the image capturing unit 15 is started. After that, the user U operates the operation unit 12, whereby the image of the item to be organized can be captured by the image capturing unit 15. As a result, the captured image of the item to be organized is received by the reception unit 31.

[0127] The image acquisition button 612 is a button for acquiring image information from the storage unit 17 by the acquisition unit 30. When the user U operates the operation unit 12 to select the image acquisition button 612, the image stored in the storage unit 17 is displayed on the display unit 11. When the user U selects an image of an item to be organized from the images displayed on the display unit 11, the image information, which is information on the selected image, is acquired by the acquisition unit 30.

[0128] The barcode button 613 is a button for starting the imaging unit 15 and reading a barcode attached to an item. When the user U operates the operation unit 12 to select the barcode button 613, the imaging unit 15 is started. After that, the user U operates the operation unit 12, which causes the imaging unit 15 to capture an image of the barcode of the item, and the acquisition unit 30 acquires information about the sorted item from the barcode.

[0129] The purchase history button 614 is a button for acquiring the purchase history of the user U. When the user U operates the operation unit 12 to select the purchase history button 614, the acquisition unit 30 acquires the purchase history of the user U from the storage unit 17 or an external information processing device, etc. The extraction unit 33 extracts information on the items to be organized from the purchase history of the user U.

[0130] The organized item list 62 includes organized item areas 621, 622, and 623. The organized item area 621 includes organized item information 621a, organizing method information 621b, and a listing button 621c. The organized item information 621a is information indicating perfume A, and the organizing method information 621b is information indicating the use of an item buying and selling intermediary service.

[0131] The put up for sale button 621c is a button for arranging the items to be sorted, which are indicated in the sorting item information 621a, using the sorting method indicated in the sorting method information 621b, and is a button for putting perfume A up for sale on an item buying and selling intermediary service.

[0132] The organizing item area 622 includes organizing item information 622a, organizing method information 622b, and a request button 622c. The organizing item information 622a is information indicating baby tableware H, and the organizing method information 622b is information indicating the use of a waste collection service. The request button 622c is a button for organizing the organizing items indicated in the organizing item information 622a using the organizing method indicated in the organizing method information 622b, and for sending the baby tableware H to the waste collection service.

[0133] The organizing item area 623 includes organizing item information 623a, organizing method information 623b, and a selling button 623c. The organizing item information 623a is information indicating a washing machine C, and the organizing method information 623b is information indicating use of a secondhand goods buying service. The selling button 623c is a button for organizing the organizing items indicated in the organizing item information 623a by the organizing method indicated in the organizing method information 623b, and is a button for putting the washing machine C up for sale to the secondhand goods buying service.

[0134] When the user U selects the selling button 621c by operating the operation unit 12, the presentation unit 35 causes the display unit 11 to display a selling screen for arranging the items to be organized indicated in the item to be organized information 621a using the organizing method indicated in the organizing method information 621b. The selling screen includes information on the items to be organized indicated in the item to be organized information 621a, and from the selling screen, it is possible to organize the items using the organizing method indicated in the organizing method information 621b.

[0135] Furthermore, when the user U selects the selling button 623c by operating the operation unit 12, the presentation unit 35 causes the display unit 11 to display a selling screen for arranging the items to be organized indicated in the item to be organized information 623a using the organizing method indicated in the organizing method information 623b. The selling screen includes information on the items to be organized indicated in the item to be organized information 623a, and from the selling screen, it is possible to organize the items using the organizing method indicated in the organizing method information 623b.

[0136] Furthermore, when the user U selects the request button 622c by operating the operation unit 12, the presentation unit 35 causes the display unit 11 to display a collection request screen for organizing the items to be organized indicated in the organizing item information 622a using the organizing method indicated in the organizing method information 622b. The collection request screen includes a button for transmitting information indicating the items to be organized to a waste collection service provider in order to request collection of the items to be organized indicated in the organizing item information 622a.

[0137] 4. Processing Procedure Next, a procedure of information processing by the processing unit 18 of the terminal device 1 according to the embodiment will be described. Fig. 5 is a flowchart showing an example of information processing by the processing unit 18 of the terminal device 1 according to the embodiment.

[0138] 5, the processing unit 18 of the terminal device 1 acquires user information, which is information about the user U (step S10). The processing unit 18 also acquires organized item information, which is information about organized items owned by the user U (step S11).

[0139] Next, the processing unit 18 uses a model that has learned the relationship between items, the owners of the items, and the methods for organizing the items to generate organizing method information, which is information indicating the method for organizing the items to be organized, from input information including the user information acquired in step S10 and the organizing item information acquired in step S11 (step S12).

[0140] Next, the processor 18 presents the organizing method indicated by the organizing method information generated in step S11 to the user U (step S13). When the process of step S13 ends, the processor 18 determines whether or not it is time to end the operation (step S14). The processor 18 determines that it is time to end the operation when, for example, the power supply of the terminal device 1 is turned off.

[0141] If the processing unit 18 determines that the operation end time has not arrived (step S14: No), it transitions to step S10, and if the processing unit 18 determines that the operation end time has arrived (step S14: Yes), it terminates the processing shown in FIG. 5.

[0142] 5. Modifications A part or all of the above-mentioned processing of the terminal device 1 may be performed by an information processing device (not shown). In this case, the information processing device (not shown) has a part or all of the functions of the acquisition unit 30, the reception unit 31, the estimation unit 32, the extraction unit 33, the generation unit 34, and the presentation unit 35.

[0143] The estimation unit 32 can also estimate the persona related to organizing of the user U from input information further including, for example, a detection result by the sensor unit 16. The types of organizing methods may include, for example, in addition to or instead of the above-mentioned types, organizing methods such as offering at a bazaar free of charge, giving to family or acquaintances (free of charge or for a fee), and the like.

[0144] In addition, the generation unit 34 can also generate organizing method information, which is information indicating a method of organizing items, by using, for example, an organizing method determination model corresponding to a combination of season, region, etc., immediately before the generation of the organizing method information, among each combination of season, region, etc.

[0145] [6. Hardware Configuration] The terminal device 1 according to the embodiment described above is realized by a computer 80 having a configuration as shown in Fig. 6. Fig. 6 is a hardware configuration diagram showing an example of the computer 80 that realizes the functions of the terminal device 1 according to the embodiment. The computer 80 has a CPU 81, a RAM 82, a ROM (Read Only Memory) 83, a HDD (Hard Disk Drive) 84, a communication interface (I / F) 85, an input / output interface (I / F) 86, and a media interface (I / F) 87.

[0146] The CPU 81 operates and controls each part based on a program stored in the ROM 83 or the HDD 84. The ROM 83 stores a boot program executed by the CPU 81 when the computer 80 is started up, and programs that depend on the hardware of the computer 80.

[0147] The HDD 84 stores programs executed by the CPU 81, data used by such programs, etc. The communication interface 85 receives data from other devices via the network N (see FIG. 2) and sends it to the CPU 81, and transmits data generated by the CPU 81 to other devices via the network N.

[0148] The CPU 81 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse, via the input / output interface 86. The CPU 81 acquires data from the input devices via the input / output interface 86. The CPU 81 also outputs data generated via the input / output interface 86 to the output devices.

[0149] The media interface 87 reads a program or data stored in a recording medium 88 and provides it to the CPU 81 via the RAM 82. The CPU 81 loads the program from the recording medium 88 onto the RAM 82 via the media interface 87 and executes the loaded program. The recording medium 88 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase change rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0150] For example, when the computer 80 functions as the terminal device 1 according to the embodiment, the CPU 81 of the computer 80 executes a program loaded onto the RAM 82 to realize the function of the processing unit 18. In addition, the data in the storage unit 17 is stored in the HDD 84. The CPU 81 of the computer 80 reads and executes these programs from a recording medium 88, but as another example, these programs may be obtained from another device via the network N.

[0151] [7. Other] In addition, 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.

[0152] 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.

[0153] For example, the above-mentioned terminal device 1 may be realized as an information processing device by a terminal device and a server computer, or by multiple server computers. Also, depending on the functions, the configuration can be flexibly changed, such as by calling an external platform using an API or network computing.

[0154] Furthermore, the above-described embodiments and modifications can be appropriately combined as long as the processing contents are not contradictory.

[0155] 8. Effects As described above, the terminal device 1 according to the embodiment is an example of an information processing device, and includes an acquisition unit 30, a generation unit 34, and a presentation unit 35. The acquisition unit 30 acquires organized item information, which is information on the items to be organized, and user information, which is information on a user U who owns the items to be organized. The generation unit 34 generates organizing method information, which is information indicating a method of organizing the items to be organized, from input information including the organized item information and user information acquired by the acquisition unit 303, using a model that has learned the relationship between the items, the owners of the items, and the organizing methods of the items. The presentation unit 35 presents the organizing method indicated by the organizing method information generated by the generation unit 34 to the owner of the items to be organized. As a result, the terminal device 1, as an information processing device, can improve the convenience of the user U.

[0156] The information processing device 4 also includes a receiving unit 31 that receives image information, which is information on an image of the organized items, and the acquiring unit 30 acquires information on the organized items identified by the image information as organized item information. This allows the terminal device 1 to improve the convenience of the user U.

[0157] The information processing device 4 also includes an extraction unit 33 that extracts information on the organized items from information on the purchase history of the items, and the acquisition unit 30 acquires, as organized item information, the information on the organized items extracted by the extraction unit 33. This allows the terminal device 1 to improve the convenience of the user U.

[0158] The sorting method includes one or more sorting methods among a plurality of sorting methods including use of an item buying and selling intermediary service, use of a used goods buying service, and use of a waste collection service. This allows the terminal device 1 to improve the convenience of the user U.

[0159] Moreover, the information processing device 4 includes an estimation unit 32 that estimates a persona related to organization of the user U, and the acquisition unit 30 acquires, as user information, information indicating the persona estimated by the estimation unit 32. This allows the terminal device 1 to accurately determine the organization method.

[0160] Furthermore, the estimation unit 32 estimates the persona related to organization of the user U based on one or more pieces of information among the attribute information and the behavioral history of the user U. This allows the terminal device 1 to accurately estimate the persona related to organization of the user U.

[0161] The model is generated using learning information including, for each item, information indicating the item, information indicating the item arrangement method, and information indicating the item owner's persona regarding arrangement. This allows the terminal device 1 to accurately determine the arrangement method.

[0162] The learning information also includes information obtained from a questionnaire about the organizing method filled in by the owner of the item, which allows the terminal device 1 to accurately determine the organizing method.

[0163] The above describes the embodiment of the present application in detail based on the drawings, but this is merely an example, and the present invention can be implemented in other forms that include various modifications and improvements based on the knowledge of those skilled in the art, including the forms described in the Disclosure of the Invention section.

[0164] Furthermore, the above-mentioned "section, module, unit" can be read as "means" or "circuit", etc. For example, an acquisition section can be read as an acquisition means or an acquisition circuit. [Explanation of symbols]

[0165] 1 Terminal equipment 2. Product sales intermediary site 3. Second-hand goods purchase sites 4. Information processing equipment 10. Communications Department 11 Display section 12 Control section 13 Audio input section 14 Audio output section 15 Imaging unit 16 Sensor section 17 Memory section 18 Processing section 30 Acquisition Department 31 Reception 32 Estimation part 33 Extraction part 34 Generation part 35 Presentation section 100 Information Processing Systems N Network

Claims

1. An acquisition unit that acquires user information, which is information about a user who has an item to be organized, and organized item information, which is information about the item to be organized; a generation unit that generates organizing method information, which is information indicating a method of organizing the items to be organized, from input information including the organized item information and the user information acquired by the acquisition unit, using a model that has learned a relationship between an item, an owner of the item, and a method of organizing the item; a presentation unit that presents the organizing method indicated by the organizing method information generated by the generation unit to an owner of the item to be organized.

23. An information processing apparatus comprising:

2. A reception unit is provided for receiving image information, which is information on an image of the item to be organized, The acquisition unit is Information on the organized items identified by the image information is acquired as the organized item information.

2. The information processing apparatus according to claim 1,

3. An extraction unit that extracts information on the organized items from information on purchase history of the items, The acquisition unit is The information on the organized items extracted by the extraction unit is acquired as the organized item information.

2. The information processing apparatus according to claim 1,

4. The arrangement method includes: This includes one or more of a number of sorting methods, including the use of an item buying and selling intermediary service, the use of a used goods buying service, and the use of a waste collection service.

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

5. An estimation unit that estimates a persona related to organization of the user, The acquisition unit is Information indicating the persona estimated by the estimation unit is acquired as the user information.

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

6. The estimation unit is A persona regarding organization of the user is estimated based on one or more pieces of information of attribute information and behavioral history of the user.

6. The information processing apparatus according to claim 5,

7. The model is The model is generated using learning information including, for each item, information indicating an item, information indicating a method of organizing the item, and information indicating a persona regarding organization of the owner of the item.

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

8. The learning information is Includes information obtained from questionnaires filled out by owners of items regarding their organizing methods.

8. The information processing apparatus according to claim 7,

9. 1. A computer-implemented information processing method, comprising: An acquisition step of acquiring user information, which is information about a user who has an item to be organized, and organized item information, which is information about the item to be organized; a generation step of generating organizing method information indicating a method for organizing the items to be organized from input information including the organized item information and the user information acquired by the acquisition step, using a model that has learned a relationship between the items, the owners of the items, and the organizing methods of the items; and a presentation step of presenting the organizing method indicated by the organizing method information generated by the generation step to an owner of the item to be organized.

23. An information processing method comprising:

10. An acquisition step of acquiring user information, which is information about a user who has an item to be organized, and organized item information, which is information about the item to be organized; a generation step of generating organizing method information, which is information indicating a method of organizing the items to be organized, from input information including the organized item information and the user information acquired by the acquisition step, using a model that has learned a relationship between an item, an owner of the item, and a method of organizing the item; a presentation step of presenting the organizing method indicated by the organizing method information generated by the generation step to an owner of the item to be organized.

2. An information processing program comprising:

Images