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

Abstract

To provide an information processing apparatus capable of allowing a user to easily determine whether a housing environment is appropriate for the user in the future.SOLUTION: The information processing apparatus includes an acquisition unit configured to acquire user information related to a user, a determination unit configured to determine one or more housing environments to be recommended to the user after a predetermined period, and an output unit configured to output housing environment information indicating the one or more housing environments and recommendation reason information indicating a reason for recommendation of each of the one or more housing environments.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] BACKGROUND ART There is known a technique for predicting a user's future situation and proposing a future home environment to the user based on the predicted situation.

[0003] For example, Patent Document 1 describes a housing provision support system that selects properties based on personal information about a target person, such as age and family structure, and presents the selected properties to the target person. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2003-30302 Summary of the Invention [Problem to be solved by the invention]

[0005] The housing provision support system described in Patent Document 1 presents only selected properties (housing environments) to the target person (user). Therefore, in this housing provision support system, the target person cannot recognize why the presented property was selected. Since the target person cannot recognize why the presented property was selected, the housing provision support system has a problem in that it is difficult for the target person to determine whether the presented property is appropriate for the target person in the future.

[0006] The present disclosure has been made in consideration of the above-mentioned problems, and one exemplary purpose thereof is to provide a technology that allows a user to easily determine whether a home environment is suitable for a future user. [Means for solving the problem]

[0007] An information processing device according to an exemplary aspect of the present disclosure includes an acquisition means for acquiring user information related to a user, a determination means for referring to the user information to determine one or more residential environments to recommend to the user, which are residential environments after a predetermined period of time, and an output means for outputting residential environment information indicating the one or more residential environments and recommendation reason information indicating the reason for recommending each of the one or more residential environments.

[0008] An information processing method according to an exemplary aspect of the present disclosure includes an acquisition process in which at least one processor acquires user information related to a user; a determination process in which, by referring to the user information, one or more residential environments to recommend to the user, which are residential environments after a predetermined period of time; and an output process in which residential environment information indicating the one or more residential environments and recommendation reason information indicating reasons for recommending each of the one or more residential environments are output.

[0009] A program according to an exemplary aspect of the present disclosure is a program that causes a computer to function as an information processing device, and causes the computer to function as an acquisition means that acquires user information related to a user, a determination means that refers to the user information and determines one or more residential environments that are residential environments after a predetermined period of time and that are to be recommended to the user, and an output means that outputs residential environment information indicating the one or more residential environments and recommendation reason information indicating the reason for recommending each of the one or more residential environments. [Effects of the Invention]

[0010] According to an exemplary aspect of the present disclosure, an exemplary effect is achieved in that a technology can be provided that allows a user to easily determine whether a home environment is suitable for a future user. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a block diagram illustrating a configuration of an information processing device according to the present disclosure. [Figure 2]FIG. 1 is a flow diagram showing the flow of an information processing method according to the present disclosure. [Figure 3] 1 is a block diagram illustrating a configuration of an information processing device according to the present disclosure. [Figure 4] FIG. 10 is a diagram illustrating an example of an image output by an output unit according to the present disclosure. [Figure 5] 10A and 10B are diagrams illustrating examples of images output by an output unit according to the present disclosure. [Figure 6] FIG. 10 is a diagram illustrating an example of recommendation reason information according to the present disclosure. [Figure 7] FIG. 10 is a diagram illustrating another example of recommendation reason information according to the present disclosure. [Figure 8] FIG. 1 is a flowchart showing a flow of processing executed by an information processing device according to the present disclosure. [Figure 9] 1 is a block diagram illustrating a configuration of an information processing device according to the present disclosure. [Figure 10] FIG. 10 is a diagram showing a flow of processing executed by a decision unit according to the present disclosure. [Figure 11] FIG. 1 is a block diagram illustrating a configuration of a computer that functions as an information processing device according to the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0012] The following are examples of embodiments of the present invention. However, the present invention is not limited to the exemplary embodiments shown below, and various modifications are possible within the scope of the claims. For example, embodiments obtained by appropriately combining the technical means employed in the exemplary embodiments shown below may also be included in the scope of the present invention. Furthermore, embodiments obtained by appropriately omitting some of the technical means employed in the exemplary embodiments shown below may also be included in the scope of the present invention. Furthermore, the effects mentioned in the exemplary embodiments shown below are examples of effects expected in the exemplary embodiments, and do not define the scope of the present invention. In other words, embodiments that do not exhibit the effects mentioned in the exemplary embodiments shown below may also be included in the scope of the present invention.

[0013] First Exemplary Embodiment A first exemplary embodiment, which is one example of an embodiment of the present invention, will be described in detail with reference to the drawings. This exemplary embodiment is the basic form of each exemplary embodiment described later. Note that the scope of application of each technical means employed in this exemplary embodiment is not limited to this exemplary embodiment. That is, each technical means employed in this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure to the extent that no particular technical obstacles arise. Furthermore, each technical means shown in the drawings referred to in describing this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure to the extent that no particular technical obstacles arise.

[0014] (Configuration of information processing device 1) The configuration of the information processing device 1 will be described with reference to Fig. 1. Fig. 1 is a block diagram showing the configuration of the information processing device 1. As shown in Fig. 1, the information processing device 1 includes an acquisition unit 11, a determination unit 12, and an output unit 13. In this exemplary embodiment, the acquisition unit 11, the determination unit 12, and the output unit 13 respectively realize an acquisition means, a determination means, and an output means.

[0015] (Acquisition part 11) The acquisition unit 11 acquires user information related to a user. The acquisition unit 11 supplies the acquired user information to the determination unit 12.

[0016] (Decision Unit 12) The determination unit 12 determines one or more residential environments to recommend to the user, which are residential environments after a predetermined period of time, by referring to the user information acquired by the acquisition unit 11. The determination unit 12 supplies the output unit 13 with residential environment information indicating the determined one or more residential environments and recommendation reason information indicating the reason for recommending each of the one or more residential environments.

[0017] (Output section 13) The output unit 13 outputs residential environment information indicating the one or more residential environments determined by the determination unit 12, and recommendation reason information indicating the reason for recommending each of the one or more residential environments.

[0018] (Effects of information processing device 1) As described above, the information processing device 1 is configured to include an acquisition unit 11 that acquires user information related to the user, a determination unit 12 that refers to the user information acquired by the acquisition unit 11 and determines one or more residential environments to recommend to the user as residential environments after a predetermined period of time, and an output unit 13 that outputs residential environment information indicating the one or more residential environments determined by the determination unit 12 and recommendation reason information indicating the reason for recommending each of the one or more residential environments.

[0019] Therefore, according to the information processing device 1, the user can be notified of the recommended home environment after a predetermined period of time and the reason for the recommendation, thereby enabling the user to easily determine whether the home environment is appropriate for the future user.

[0020] (Flow of information processing method S1) The flow of the information processing method S1 will be described with reference to Fig. 2. Fig. 2 is a flow diagram showing the flow of the information processing method S1. As shown in Fig. 2, the information processing method S1 includes an acquisition process S11, a determination process S12, and an output process S13.

[0021] (Acquisition process S11) In the acquisition process S11, the acquisition unit 11 acquires user information related to the user. The acquisition unit 11 supplies the acquired user information to the determination unit 12.

[0022] (Decision process S12) In the determination process S12, the determination unit 12 determines one or more residential environments to be recommended to the user after a predetermined period of time, with reference to the user information acquired by the acquisition unit 11. The determination unit 12 supplies the output unit 13 with residential environment information indicating the determined one or more residential environments and recommendation reason information indicating the reason for recommending each of the one or more residential environments.

[0023] (Output process S13) In the output process S13, the output unit 13 outputs residential environment information indicating one or more residential environments determined by the determination unit 12, and recommendation reason information indicating the reason for recommending each of the one or more residential environments.

[0024] (Effect of information processing method S1) As described above, the information processing method S1 employs a configuration including an acquisition process S11 in which the acquisition unit 11 acquires user information related to the user, a decision process S12 in which the determination unit 12 refers to the user information acquired by the acquisition unit 11 and determines one or more residential environments to be recommended to the user as residential environments after a predetermined period of time, and an output process S13 in which the output unit 13 outputs residential environment information indicating the one or more residential environments determined by the determination unit 12 and recommendation reason information indicating the reason for recommending each of the one or more residential environments.

[0025] Therefore, according to the information processing method S1, the same effects as those of the information processing device 1 described above can be obtained.

[0026] Second Exemplary Embodiment A second exemplary embodiment, which is one example of an embodiment of the present invention, will be described in detail with reference to the drawings. Components having the same functions as those described in the above exemplary embodiment will be assigned the same reference numerals, and their description will be omitted as appropriate. The scope of application of each technical means employed in this exemplary embodiment is not limited to this exemplary embodiment. That is, each technical means employed in this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical obstacles arise. Furthermore, each technical means shown in each drawing referenced to explain this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical obstacles arise.

[0027] (Overview of information processing device 2) The information processing device 2 is a device that refers to user information USI, which is information related to the user, recommends one or more home environments suitable for the user in the future (after a predetermined period of time), and further presents the reason for recommending each of the one or more home environments to the user. Specific examples of the configuration of the information processing device 2 include, but are not limited to, a server, a PC (Personal Computer), and a quantum computer.

[0028] The "residential environment suitable for the future user" refers to a residential environment that is estimated to allow the user to live comfortably based on the predicted future state and environment of the user. The "residential environment" may be the environment surrounding the house, or a specific house. For example, the information processing device 2 may recommend to the user a "spacious house near a general hospital" or a "XX apartment in Setagaya Ward, Tokyo." Examples of information output by the information processing device 2 will be described later.

[0029] The predetermined period is not particularly limited, but in this exemplary embodiment, the period until the user reaches old age (age 65) will be described as an example. That is, the information processing device 2 recommends a housing environment for the user in old age and presents the reason for the recommendation to the user.

[0030] (Configuration of information processing device 2) The configuration of the information processing device 2 will be described with reference to Fig. 3. Fig. 3 is a block diagram showing the configuration of the information processing device 2. As shown in Fig. 3, the information processing device 2 includes a control unit 20, a storage unit 21, an input / output unit 22, and a communication unit 23.

[0031] (Storage unit 21) The storage unit 21 stores data referenced by the control unit 20. Examples of the storage unit 21 include, but are not limited to, a flash memory, a hard disk drive (HDD), a solid state drive (SSD), or a combination thereof.

[0032] Examples of data stored in the storage unit 21 include, but are not limited to, user information USI related to each of one or more users, home environment information HEI indicating a recommended home environment, recommendation reason information RRI indicating a reason for recommendation, and a trained estimation model EM, as shown in Fig. 3. The estimation model EM being stored in the storage unit 21 means that parameters defining the estimation model EM are stored in the storage unit 21.

[0033] The user information USI may include a plurality of pieces of information related to the user. As an example, the user information USI may include the following information: Information about user attributes (e.g., age, gender, place of employment, occupation, job title, family structure, community affiliation, and hobbies) Information about your assets (income, expenses, savings, real estate ownership) - Information about the user's health (smoking status, drinking status, exercise status, height, weight, blood pressure, medical history) Information about the residential environment in which the user currently lives (address, size, layout, individual home / rental home, age of building, useful life, surrounding facilities) Information about the user's purchase history (receipts, online shopping purchase history) Information about the user's behavioral history (location history based on the GPS (Global Positioning System) of the user's device, stores visited by the user) The housing environment information HEI, recommendation reason information RRI, and estimation model EM will be described later.

[0034] (Input / output section 22) The input / output unit 22 is an interface for connecting to an input device that accepts data input or an output device that outputs data. Examples of input devices include, but are not limited to, a microphone, a camera, an eye-gaze input device, a keyboard, and a touchpad. Examples of output devices include, but are not limited to, a speaker and a liquid crystal display.

[0035] As one example, the input / output unit 22 accepts input of user information. As another example, the input / output unit 22 outputs an image including the home environment information HEI and the recommendation reason information RRI.

[0036] (Communications Department 23) The communication unit 23 is an interface for transmitting and receiving data via a network. Examples of the communication unit 23 include, but are not limited to, communication chips for various communication standards such as Ethernet (registered trademark), Wi-Fi (Wireless Fidelity (registered trademark), and wireless communication standards for mobile data communication networks, and USB-compliant connectors.

[0037] The specific configuration of the network is not particularly limited, but examples include a wireless LAN (Local Area Network), a wired LAN, a WAN (Wide Area Network), a public line network, a mobile data communication network, or a combination of these networks.

[0038] As one example, the communication unit 23 accepts input of user information from another device via a network. As another example, the communication unit 23 outputs an image including the home environment information HEI and the recommendation reason information RRI to another device via a network.

[0039] (Control unit 20) The control unit 20 controls each component included in the information processing device 2. As shown in Fig. 3, the control unit 20 also includes an acquisition unit 11, a determination unit 12, an output unit 13, and a reception unit 14. In this exemplary embodiment, the acquisition unit 11, the determination unit 12, the output unit 13, and the reception unit 14 respectively realize an acquisition means, a determination means, an output means, and a reception means.

[0040] (Acquisition part 11) The acquisition unit 11 acquires data from the input / output unit 22 or the communication unit 23. As an example, the acquisition unit 11 acquires user information USI of one or more users. The acquisition unit 11 stores the acquired user information USI in the storage unit 21.

[0041] (Decision Unit 12) The determination unit 12 determines a residential environment to recommend to the user. As an example, the determination unit 12 receives user information USI as input and uses an estimation model EM that estimates a residential environment to be recommended to the user after a predetermined period of time to determine one or more residential environments to recommend to the user after a predetermined period of time. The determination unit 12 stores, in the memory unit 21, residential environment information HEI indicating the determined one or more residential environments and recommendation reason information RRI indicating the reason for recommending each of the determined one or more residential environments.

[0042] More specifically, the determination unit 12 inputs the user information USI stored in the storage unit 21 into the estimation model EM. Next, the determination unit 12 determines the residential environment indicated by the estimation result output from the estimation model EM as the residential environment to be recommended to the user. Then, the determination unit 12 stores residential environment information HEI indicating the determined residential environment in the storage unit 21.

[0043] The estimation model EM may be a model generated to output the reason for recommending the estimated recommended residential environment together with the estimation result of the recommended residential environment. In this case, the determination unit 12 stores, in the storage unit 21, recommendation reason information RRI indicating the reason for recommendation output from the estimation model EM.

[0044] The estimation model EM may also be configured to be able to refer to information on the Internet. In this case, the estimation model EM may be configured to refer to information on vacant houses, information on local governments that support relocation, etc.

[0045] In addition, when the user information USI stored in the memory unit 21 is the user information USI of each of multiple users, the determination unit 12 may refer to the similarity between the user information of each of the multiple users and determine one or more residential environments to recommend to each of the multiple users.

[0046] Furthermore, when the user information USI includes multiple pieces of information related to a user, the estimation model EM may be configured to estimate a residential environment to be recommended to the user by prioritizing at least one piece of information related to the multiple users. In other words, the estimation model EM may be configured to allow setting of weights indicating the degree of importance to be attached to each piece of information related to the multiple users. In this case, the determination unit 12 determines a residential environment that prioritizes at least one piece of information by changing the weights of the estimation model EM.

[0047] An example of the process executed by the determination unit 12 will be described later.

[0048] (Output section 13) The output unit 13 outputs data to the input / output unit 22 or via the communication unit 23. As an example, the output unit 13 outputs the home environment information HEI and the recommendation reason information PPI stored in the storage unit 21. In this case, the output unit 13 may output an image including the home environment information HEI and the recommendation reason information PPI.

[0049] As another example, when the user information USI includes a plurality of pieces of information related to the user, the output unit 13 outputs an image for accepting input of the degree of importance to be attached to each of the pieces of information related to the plurality of users.

[0050] Examples of images output by the output unit 13 will be described later.

[0051] (Reception Section 14) The receiving unit 14 receives input from a user. As an example, when the user information USI includes multiple pieces of information related to the user, the receiving unit 14 receives input of the weighting ratio for each of the pieces of information related to the multiple users. The receiving unit 14 supplies information indicating the received input to the determining unit 12.

[0052] (Example 1 of processing executed by the determination unit 12) An example of the process executed by the determination unit 12 will be described.

[0053] In this example, it is assumed that the acquisition unit 11 has acquired user information USI including information indicating that the user's hobby is "surfing," information regarding the user's assets, which indicates "savings, income, and expenses," information indicating the user's family composition, which is "a couple and two children (a high school student and a middle school student)," and information regarding the residential environment in which the user currently lives, which indicates that the floor plan is "3LDK."

[0054] In addition, in this example, the determination unit 12 uses the trained estimation model EM to refer to information about vacant houses on the Internet.

[0055] In this case, the determination unit 12 inputs the user information USI acquired by the acquisition unit 11 into the estimation model EM. For example, assume that the estimation result output from the estimation model EM is "XX Apartment in Kanagawa Prefecture," which was posted on the Internet as a vacant house, and the reason for recommendation is "The size of XX Apartment in Kanagawa Prefecture is perfect for a couple to live in when they are old and their children have left home. In addition, the rent for XX Apartment is cheap at YY yen. In addition, Kanagawa Prefecture is an ideal area for enjoying the hobby of surfing."

[0056] In this case, the decision unit 12 stores in the memory unit 21 the housing environment information HEI indicating "XX Apartment in Kanagawa Prefecture" and the recommendation reason information RRI indicating "The size of XX Apartment in Kanagawa Prefecture is perfect for a couple to live in after they have grown old and their children have left home. In addition, the rent for XX Apartment is cheap at YY yen. Furthermore, Kanagawa Prefecture is an ideal area for enjoying the hobby of surfing."

[0057] That is, the determination unit 12 determines the recommended residential environment to be a house in an area where the user can enjoy the hobby of "surfing," with a rent that can be paid with the user's assets in retirement and a size that takes into account the user's family structure in retirement (only a married couple living).

[0058] In this way, the decision unit 12 can recommend suitable vacant houses to future users by using the trained estimation model EM to refer to information about vacant houses on the Internet.

[0059] (Example 2 of processing executed by the determination unit 12) Another example of the process executed by the determination unit 12 will be described.

[0060] In this example, it is assumed that the acquisition unit 11 acquires user information USI including information about the user's health, which indicates that the user has asthma, information about the user's purchasing history, which indicates that the user has purchased a book about immigration, and information about the user's behavioral history, which indicates that the user has gone to the beach three times a week.

[0061] In this example, the determination unit 12 uses a trained estimation model EM to refer to information on local governments on the Internet.

[0062] Even in this case, the determination unit 12 inputs the user information USI acquired by the acquisition unit 11 into the estimation model EM. For example, assume that the estimation result output from the estimation model EM is "△△ Residence" in XX City, a local government that supports relocation over the Internet, and the reason for recommendation is "XX City has clean air, so your asthma is expected to improve. Also, if you move to XX City, you will receive support of ZZ yen. Also, you can see the ocean from △△ Residence."

[0063] Even in this case, the decision unit 12 stores in the memory unit 21 the housing environment information HEI indicating "XX City's △△ Residence" and the recommendation reason information RRI indicating "XX City has clean air, so your asthma is expected to improve. Also, if you move to XX City, you will receive ZZ yen in support. Also, you can see the ocean from △△ Residence."

[0064] That is, the determination unit 12 determines, as the recommended residential environment for a user who is interested in relocating, a home in an area that is easy to relocate to, taking into consideration the user's illness and the user's frequent visits to the sea.

[0065] The estimation model EM may be a model that estimates a recommended housing environment, taking into consideration that the number of residents in municipalities that support relocation increases and that other municipalities do not become depopulated.

[0066] In this way, the decision unit 12 can recommend a housing environment in a municipality that is appropriate for a future user by using the trained estimation model EM to refer to information about the municipality on the Internet.

[0067] (Example 3 of processing executed by the determination unit 12) Another example of the process executed by the determination unit 12 will now be described.

[0068] In this example, it is assumed that the acquisition unit 11 acquires user information USI of multiple users. Below, a description is given of a case where the acquisition unit 11 acquires user information USI_A of user A and user information USI_B of user B and stores them in the storage unit 21. Furthermore, the user information USI_A includes information indicating that the user will retire from X Corporation in 10 years, and the user information USI_B includes information indicating that the user will retire from X Corporation in 10 years and 1 month.

[0069] In addition, in this example, the determination unit 12 receives user information USI of multiple users as input, refers to the mutual similarity of the user information USI of each of the multiple users, and uses a trained estimation model EM to estimate one or more residential environments to recommend to each of the multiple users.

[0070] Even in this case, the determination unit 12 inputs the user information USI_A and the user information USI_B acquired by the acquisition unit 11 into the estimation model EM. For example, assume that the estimation result output from the estimation model EM is that the residential environment recommended for both user A and user B is "XX Apartment" and the reason for recommendation is "XX Apartment is home to many people of the same generation."

[0071] Even in this case, the determination unit 12 stores in the memory unit 21, for both user A and user B, the housing environment information HEI indicating "□□ Apartment" and the recommendation reason information RRI indicating "□□ Apartment is home to many people of the same generation."

[0072] That is, the determination unit 12 refers to the degree of similarity between the user information USI_A of user A and the user information USI_B of user B. In this case, the user information USI_A and the user information USI_B each contain information indicating that they will be leaving the same company at the same time, so the degree of similarity is high. If the degree of similarity is high, the determination unit 12 determines the residential environment so that user A and user B can belong to the same community (for example, their houses are close to each other). As another example, the determination unit 12 determines the residential environment so that users with similar hobbies and preferences can belong to the same circle. As yet another example, the determination unit 12 determines the residential environment so that users with similar asset situations can live in an area where many users with similar asset situations live.

[0073] In this way, the determination unit 12 refers to the mutual similarity of the user information USI of each of the multiple users, and recommends a similar residential environment to users whose user information USI is similar. Therefore, the determination unit 12 can recommend an appropriate residential environment taking into consideration the relationship between the multiple users.

[0074] (Example 4 of the process executed by the determination unit 12) Another example of the process executed by the determination unit 12 will now be described.

[0075] In this example, it is assumed that the user information USI includes a plurality of pieces of information related to the user, and the receiving unit 14 receives input of the degree of importance to be attached to each of the pieces of information related to the plurality of users. The user information USI also includes information indicating the user's hobbies and preferences (camping, mountain climbing), information about the user's health, information about the user's financial situation, information about the user's family structure, and information about the community to which the user belongs.

[0076] In this example, the determination unit 12 uses an estimation model EM that can set weights indicating the degree of importance to be attached to each piece of information related to a plurality of users. Note that the determination unit 12 sets the same degree of importance to each piece of information related to a plurality of users until it receives an input from the user.

[0077] First, when the acquisition unit 11 acquires user information USI including multiple pieces of information related to a user, the output unit 13 outputs information indicating each piece of information related to the multiple users included in the user information USI and the degree of importance to which each piece of information related to the multiple users is to be emphasized. As an example, the output unit 13 outputs an image including each piece of information related to the multiple users included in the user information USI and the degree of importance to which each piece of information related to the multiple users is to be emphasized. An example of the image output by the output unit 13 is shown in FIG. 4. FIG. 4 is a diagram showing an example of the image output by the output unit 13.

[0078] 4, the output unit 13 outputs an image including a pie chart and a table indicating that the information included in the user information USI is information indicating the user's hobbies and preferences, information about the user's health, information about the user's financial situation, information about the user's family structure, and information about the community to which the user belongs. The output unit 13 also outputs an image indicating that the respective pieces of information related to multiple users are given the same degree of importance (20% each).

[0079] The image shown on the left side of Fig. 4 may be an image that accepts input of the degree of importance to be attached to each piece of information related to a plurality of users. For example, the output unit 13 outputs an image including a button UI_B for inputting the degree of importance to be attached to hobbies and preferences, as shown in the pie chart of Fig. 4. Similarly, the output unit 13 outputs an image including an item UI_I for inputting the degree of importance to be attached to hobbies and preferences, as shown in the table of Fig. 4.

[0080] When the user operates button UI_B or inputs a value into item UI_I to change the degree of importance placed on hobbies and preferences to 60% as shown on the right side of Fig. 4, the receiving unit 14 receives an input indicating that the degree of importance placed on hobbies and preferences is 60%. Note that this configuration is also similar for information other than information indicating hobbies and preferences.

[0081] When the receiving unit 14 receives an input indicating that the degree to which hobbies and preferences are emphasized is 60%, the determining unit 12 changes the weight indicating the degree to which the information indicating hobbies and preferences of the estimated model EM is emphasized to 60%.

[0082] Then, the determination unit 12 inputs user information USI, including information indicating the user's hobbies and preferences, information on the user's health, information on the user's financial situation, information on the user's family structure, and information on the community to which the user belongs, into the estimation model EM. For example, assume that the estimation result output from the estimation model EM is "Gujo City, Gifu Prefecture," and the reason for recommendation is "Gujo City, Gifu Prefecture, is a place where you can enjoy camping and mountain climbing, which are the user's hobbies."

[0083] In this case, too, the determination unit 12 stores in the memory unit 21 the residential environment information HEI indicating "Gujo City, Gifu Prefecture" and the recommendation reason information RRI indicating "Gujo City, Gifu Prefecture is a place where you can enjoy the user's hobbies of camping and mountain climbing."

[0084] That is, if the reception unit 14 receives input indicating that the user places importance on the hobbies and preferences of "camping and mountain climbing," the determination unit 12 determines "Gujo City, Gifu Prefecture," which is an easy place to go camping and mountain climbing, as the recommended residential environment.

[0085] In other words, when the receiving unit 14 receives an input of the ratio of importance to be attached to each piece of information related to the user, the determining unit 12 refers to the input and determines one or more residential environments based on the ratio of each piece of information related to the multiple users. Therefore, the determining unit 12 can recommend a residential environment appropriate for a future user while taking into account the user's wishes.

[0086] Here, the receiving unit 14 may be configured to have the user directly input the percentages to be weighted for each piece of information related to the user, as shown in Fig. 4 above, or may have the user input a request, and the determining unit 12 may set the percentages to be weighted for each piece of information related to a plurality of users based on the request. Examples of user requests include "I want to eat high-quality ingredients every day" and "I don't mind simple meals, but I want to live in a large room with a garden."

[0087] For example, if the receiving unit 14 receives an input indicating that "I want to eat high-quality ingredients every day," the determining unit 12 sets a high degree of importance to information indicating the user's expenditures and a low degree of importance to information regarding the user's health.

[0088] Furthermore, when the reception unit 14 receives an input indicating that "I would like to live in a large room with a garden and I don't mind simple meals," the determination unit 12 sets a high degree of importance to be placed on information indicating the user's hobbies and preferences, and a low degree of importance to be placed on information indicating the user's expenses.

[0089] (Example of an image output by the output unit 13) Examples of images output by the output unit 13 will be described with reference to Fig. 5 to Fig. 7. Fig. 5 is a diagram showing an example of an image output by the output unit 13. Fig. 6 is a diagram showing an example of recommendation reason information RRI. Fig. 7 is a diagram showing another example of recommendation reason information RRI.

[0090] The output unit 13 displays an image including an area R_HEI displaying home environment information HEI indicating one or more home environments on the display device DP, as shown in Fig. 5. The output unit 13 may also display an image that allows selection of one or more home environments in the area R_HEI displaying home environment information HEI indicating one or more home environments.

[0091] When the receiving unit 14 receives an input indicating the selection of one or more residential environments, the output unit 13 may display recommendation reason information RRI indicating the reason for recommending the selected residential environment in the area R_RRI, as shown in Fig. 5. The output unit 13 may also display a photo of the selected residential environment in the area R_PIC, and display basic information about the selected residential environment in the area R_BI.

[0092] In addition, the output unit 13 may switchably display, for example, an image shown in Figure 4 that accepts input of the degree of importance to be attached to each piece of information related to multiple users, and an image shown in Figure 5 that includes an area R_HEI that displays home environment information HEI and an area R_RRI that displays recommendation reason information RRI.

[0093] As an example, when the receiving unit 14 receives an input indicating that the proportion of "hobbies and preferences" (motorcycle touring) shown in FIG. 4 should be increased, the output unit 13 displays recommendation reason information RRI in the area R_RRI when "hobbies and preferences" (motorcycle touring) is emphasized, as shown in FIG. 6.

[0094] As another example, when the receiving unit 14 receives an input indicating that the proportion of "asset status" (assets for retirement) shown in Figure 4 is to be increased, the output unit 13 displays recommendation reason information RRI in the area R_RRI when emphasis is placed on "asset status," as shown in Figure 7.

[0095] Furthermore, the recommendation reason information RRI may include information indicating the relationship between the user and the residential environment, such as "There are many areas that are ideal for enjoying motorcycle touring, which you value," as shown in Fig. 6. In this example, the recommendation reason information RRI includes information that indicates the user's value of motorcycle touring, which is a hobby or preference. With this configuration, the information processing device 2 can notify the user of the relationship between the recommended residential environment and the user.

[0096] Furthermore, the recommendation reason information RRI may include information indicating the characteristics of the residential environment, such as "Nagano Prefecture is the prefecture with the highest forest coverage in Japan, and is rich in areas that are ideal for enjoying motorcycle touring, which is important to you, such as beautiful mountains, rivers, and forests," as shown in Fig. 6. With this configuration, the information processing device 2 can notify the user of the characteristics of the recommended residential environment.

[0097] (Flow of processing executed by information processing device 2) The flow of the process (information processing method S2) executed by the information processing device 2 will be described with reference to Fig. 8. Fig. 8 is a flow diagram showing the flow of the process executed by the information processing device 2. The process flow shown in Fig. 8 is a process flow when the user information USI acquired by the acquisition unit 11 includes multiple pieces of information related to the user.

[0098] (Step S21) In step S21, the acquisition unit 11 acquires user information USI including a plurality of pieces of information related to the user. The acquisition unit 11 stores the acquired user information USI in the storage unit 21.

[0099] (Step S22) In step S22, the output unit 13 displays an image for accepting input of the degree of importance to be attached to each piece of information related to a plurality of users.

[0100] (Step S23) In step S23, the receiving unit 14 receives input of the degree of importance to be attached to each piece of information related to a plurality of users. The receiving unit 14 supplies the determining unit 12 with information indicating the received input.

[0101] (Step S24) In step S24, the determination unit 12 refers to the input received by the reception unit 14 and sets weights in the estimation model EM indicating the degree of importance to be attached to each piece of information related to multiple users. Then, the determination unit 12 receives the user information USI as input and uses the estimation model EM that estimates a residential environment recommended to the user after a predetermined period of time to determine one or more residential environments to recommend to the user after a predetermined period of time. The determination unit 12 stores, in the memory unit 21, residential environment information HEI indicating the determined one or more residential environments and recommendation reason information RRI indicating the reason for recommending each of the determined one or more residential environments.

[0102] (Step S25) In step S25, the output unit 13 outputs the home environment information HEI and the recommendation reason information PPI stored in the storage unit 21.

[0103] (Effects of information processing device 2) As described above, the information processing device 2 uses the trained estimation model EM to determine one or more residential environments to recommend to the user after a predetermined period of time, and outputs the determined one or more residential environment information HEI and recommendation reason information RRI indicating the reason for the recommendation. Therefore, the information processing device 2 can recommend a residential environment appropriate for a future user, and further allows the user to easily determine whether the residential environment is appropriate for the future user.

[0104] Third Exemplary Embodiment A third exemplary embodiment, which is an example of an embodiment of the present invention, will be described in detail with reference to the drawings. Components having the same functions as those described in the above exemplary embodiment will be assigned the same reference numerals, and their description will be omitted as appropriate. The scope of application of each technical means employed in this exemplary embodiment is not limited to this exemplary embodiment. That is, each technical means employed in this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical obstacles arise. Furthermore, each technical means shown in each drawing referenced to explain this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical obstacles arise.

[0105] (Overview of information processing device 3) Similar to the information processing device 2 described above, the information processing device 3 is a device that refers to user information USI, which is information related to the user, recommends one or more home environments suitable for the user in the future (after a predetermined period of time), and further presents the reason for recommending each of the one or more home environments to the user. Also in this exemplary embodiment, an example will be described in which the information processing device 3 recommends a home environment for the user's retirement and presents the reason for the recommendation to the user.

[0106] (Configuration of information processing device 3) The configuration of the information processing device 3 will be described with reference to Fig. 9. Fig. 9 is a block diagram showing the configuration of the information processing device 3. As shown in Fig. 9, the information processing device 3 includes a control unit 30, a storage unit 31, an input / output unit 22, and a communication unit 23. The input / output unit 22 and the communication unit 23 are as described above.

[0107] (Storage unit 31) The storage unit 31 stores data that the control unit 30 refers to, similar to the storage unit 21 described above.

[0108] Examples of data stored in the storage unit 31 include, but are not limited to, user information USI, home environment information HEI, recommendation reason information RRI, and estimation model M. The user information USI, home environment information HEI, and recommendation reason information RRI are as described above.

[0109] The estimation model EM is a trained model that estimates a residential environment to be recommended to a user after a predetermined period of time, using as input user information USI, asset information indicating the user's asset status after a predetermined period of time, and living expense information indicating the user's living expenses (expenses necessary for living, such as food expenses, housing expenses, etc.) after the predetermined period of time. The estimation model EM is also a model generated to output the estimation result of the recommended residential environment, along with the reason for recommending the estimated recommended residential environment.

[0110] 9, the estimation model EM includes a lifespan estimation model LEM, an attribute extension model AEM, a residential area candidate estimation model REM, a residential environment estimation model HEM, and a combinatorial optimization model OM. Each model included in the estimation model EM may be configured to be able to refer to information on the Internet.

[0111] The specific configurations of the lifespan estimation model LEM, attribute extension model AEM, residential area candidate estimation model REM, residential environment estimation model HEM, and combinatorial optimization model OM are not particularly limited, but one example is a general-purpose LLM (Large Language Model).

[0112] The lifespan estimation model LEM is a model that takes user information USI as input and outputs the estimation result of the user's lifespan.

[0113] The attribute extension model AEM is a model that takes user information USI as input and outputs the extension results of the user's attributes.

[0114] The residential area candidate estimation model REM is a model that takes user information USI and the extension results of the attribute extension model AEM as input, and outputs estimation results of one or more residential areas that will be recommended to the user as residential areas after a specified period of time.

[0115] The residential environment estimation model HEM is a model that takes the estimation results from the residential area candidate estimation model REM and living expense information as input, and outputs estimation results of one or more residential environments that will be recommended to the user after a specified period of time.

[0116] The combinatorial optimization model OM is a model that takes as input user information USI of one or more users, the estimation results from the housing environment estimation model HEM, and living expense information, and outputs an optimized housing environment that is recommended to one or more users.

[0117] More specifically, for example, when user information USI indicating a desire to live in a less populated area in retirement is input, the combinatorial optimization model OM outputs the less populated residential environment from among one or more residential environments indicated by the estimation results of the residential environment estimation model HEM as the optimized residential environment.

[0118] On the other hand, when user information USI of multiple users that is highly similar to each other (for example, has the same hobbies and preferences) is input, the combinatorial optimization model OM outputs, as the optimized residential environment, the residential environment that is closest to the homes of the multiple users from among one or more residential environments indicated by the estimation results of the residential environment estimation model HEM.

[0119] An example of processing using the estimation model EM will be described later.

[0120] (control unit 30) The control unit 30 controls each component included in the information processing device 3. The control unit 30 also 9, the system includes an acquisition unit 11, a determination unit 12, an output unit 13, and a reception unit 14. The acquisition unit 11, the output unit 13, and the reception unit 14 are as described above.

[0121] In addition to the above-mentioned processing, the determination unit 12 executes an asset calculation process that refers to the user information USI and calculates the user's assets after a predetermined period of time, and a living expenses calculation process that refers to the user information USI and the assets calculated in the asset calculation process and calculates the user's living expenses after a predetermined period of time.

[0122] 9, the determination unit 12 includes an asset calculation unit 121 and a living expenses calculation unit 122. The asset calculation unit 121 executes the asset calculation process, and the living expenses calculation unit 122 executes the living expenses calculation process.

[0123] (Flow of processing executed by the decision unit 12) The flow of processing executed by the determination unit 12 will be described with reference to Fig. 10. Fig. 10 is a diagram showing the flow of processing executed by the determination unit 12. As described above, the determination unit 12 in this embodiment also determines the residential environment in step S24 shown in Fig. 8.

[0124] (Step S241) In step S241, the asset calculation unit 121 refers to the user information USI and calculates the asset of the user after a predetermined period of time.

[0125] As an example, the asset calculation unit 121 refers to user information USI including information about assets (for example, the user's age, income, savings (investments, regular savings, etc.)) and calculates the user's assets for retirement.

[0126] (Step S242) In step S242, the determination unit 12 inputs user information USI including health-related information (e.g., the user's age, health checkup results, and predicted results of a simulation of the user's health condition in old age predicted from the health checkup results) into the lifespan estimation model LEM, and predicts the user's lifespan.

[0127] (Step S243) In step S243, the determination unit 12 inputs the user information USI including information on the user's attributes (for example, the user's age, family structure, etc.) into the attribute extension model AEM, and estimates the user's family structure after retirement.

[0128] For example, if the information about a user's attributes indicates that the user is 40 years old and his or her family consists of a wife and a high school-aged child, the attribute extension model AEM is a model trained to estimate that the user's family will consist of just the wife in his or her old age.

[0129] (Step S244) In step S244, the living expenses calculation unit 122 calculates the user's living expenses in retirement by referring to the user's assets in retirement calculated by the asset calculation unit 121, the user's lifespan estimated based on the user information USI, and the user's family composition in retirement.

[0130] For example, if a user's assets in retirement are 50 million yen, the user's estimated life expectancy is 85 years, and the estimated family structure in retirement is the user and his wife, the living expenses calculation unit 122 calculates monthly living expenses as 100,000 yen (1.2 million yen per year), living expenses until age 85 as 24 million yen, and housing expenses as the remaining 26 million yen.

[0131] (Step S245) In step S245, the determination unit 12 inputs the user information USI, which includes information on the user's purchase history and information on the user's behavior history, into the attribute extension model AEM, and estimates the user's interests and preferences.

[0132] For example, in the case of user information USI that shows a purchase history indicating that a user has purchased camping equipment and a behavioral history indicating that the user has visited a campsite, the attribute extension model AEM is a model that has been trained to infer that the user's hobby or preference is camping.

[0133] (Step S246) In step S246, the determination unit 12 inputs the user information USI including information indicating the hobbies and preferences and the hobbies and preferences estimated by the attribute extension model AEM into the residential area candidate estimation model REM, and estimates one or more residential areas to be recommended to the user as residential areas after a predetermined period of time.

[0134] For example, if a user's hobby is camping, the residential area candidate estimation model REM is a model trained to estimate areas with many campsites as one or more residential areas to recommend to the user.

[0135] As described above, in step S246, the residential area candidate estimation model REM may refer to information on the Internet (for example, information on local governments that support relocation).

[0136] (Step S247) In step S247, the determination unit 12 inputs the living expenses calculated by the living expenses calculation unit 122 and one or more residential areas estimated by the residential area candidate estimation model REM to be recommended to the user into the residential environment estimation model HEM, and estimates one or more residential environments to be recommended to the user after a specified period of time.

[0137] For example, in Gifu Prefecture, where the average housing cost is 26 million yen and the residential area has many campsites, the housing environment estimation model HEM is a model that estimates homes priced at 26 million yen or less as one or more housing environments to recommend to the user.

[0138] (Step S248) In step S248, the determination unit 12 inputs the user information USI, the estimation results from the housing environment estimation model HEM, and the living expenses information into the combinatorial optimization model OM, and determines an optimized housing environment that is recommended to one or more users.

[0139] Here, the output unit 13 may output the results of each step performed by the determination unit 12. For example, the output unit 13 may output the user's assets in retirement calculated in step S241.

[0140] (Example of processing executed by the decision unit 12) An example of the process executed by the determination unit 12 will be described.

[0141] As in the above-described embodiment, the receiving unit 14 may receive input of the proportion of importance to be attached to each piece of information related to multiple users, and the determination unit 12 may refer to the input and determine one or more residential environments based on the proportion of importance to be attached to each piece of information related to the multiple users.

[0142] For example, if the receiving unit 14 receives an input indicating that "I want to eat high-quality ingredients every day," the living expenses calculation unit 122 calculates the user's living expenses in retirement to be high.

[0143] Furthermore, if the reception unit 14 receives an input indicating that "I don't mind simple meals, but I would like to live in a large room with a garden," the living expenses calculation unit 122 will calculate the user's food expenses in retirement to be low and their housing expenses to be high.

[0144] Furthermore, similarly to the above-described embodiment, the output unit 13 may display the image shown in FIG. 4, and the receiving unit 14 may receive input of the degree of importance to be attached to each piece of information related to a plurality of users.

[0145] For example, when the receiving unit 14 receives an input indicating that hobbies and preferences are important, the determining unit 12 sets a high weight indicating the degree to which the residential area candidate estimation model REM places importance on information indicating hobbies and preferences.

[0146] (Effects of information processing device 3) As described above, in the information processing device 3, the determination unit 12 executes asset calculation processing and living expense calculation processing. The determination unit 12 also uses the estimation model EM, which includes the lifespan estimation model LEM, the attribute extension model AEM, the residential area candidate estimation model REM, and the residential environment estimation model HEM. Even in this configuration, the information processing device 3 recommends a residential environment appropriate for a future user and allows the user to easily determine whether the residential environment is appropriate for the future user.

[0147] Furthermore, in the information processing device 3, the determination unit 12 uses an estimation model EM that further includes a combinatorial optimization model OM. Therefore, the information processing device 3 can recommend, to each of the multiple users, a residential environment that is appropriate for a future user, in accordance with the multiple users.

[0148] [Software implementation example] Some or all of the functions of the information processing devices 1, 2, and 3 (hereinafter also referred to as "each of the above devices") may be realized by hardware such as an integrated circuit (IC chip), or by software.

[0149] In the latter case, each of the above devices is realized by, for example, a computer that executes instructions of a program, which is software that realizes each function. An example of such a computer (hereinafter referred to as computer C) is shown in Figure 11. Figure 11 is a block diagram showing the hardware configuration of computer C that functions as each of the above devices.

[0150] The computer C includes at least one processor C1 and at least one memory C2. The memory C2 stores a program P for causing the computer C to operate as each of the above-mentioned devices. In the computer C, the processor C1 reads and executes the program P from the memory C2, thereby realizing the functions of each of the above-mentioned devices.

[0151] The processor C1 may be, for example, a central processing unit (CPU), a graphic processing unit (GPU), a digital signal processor (DSP), a micro processing unit (MPU), a floating point number processing unit (FPU), a physics processing unit (PPU), a tensor processing unit (TPU), a quantum processor, a microcontroller, or a combination thereof. The memory C2 may be, for example, a flash memory, a hard disk drive (HDD), a solid state drive (SSD), or a combination thereof.

[0152] The computer C may further include a RAM (Random Access Memory) for expanding the program P during execution and for temporarily storing various data. The computer C may also include a communication interface for transmitting and receiving data to and from other devices. The computer C may also include an input / output interface for connecting input / output devices such as a keyboard, mouse, display, and printer.

[0153] Furthermore, the program P can be recorded on a non-transitory tangible recording medium M that can be read by the computer C. Such a recording medium M can be, for example, a tape, a disk, a card, a semiconductor memory, or a programmable logic circuit. The computer C can acquire the program P via such a recording medium M. The program P can also be transmitted via a transmission medium. Such a transmission medium can be, for example, a communication network or broadcast waves. The computer C can also acquire the program P via such a transmission medium.

[0154] [Appendix A] This disclosure includes the techniques described in the following appendices. However, the present invention is not limited to the techniques described in the following appendices, and various modifications are possible within the scope of the claims.

[0155] (Appendix A1) acquiring means for acquiring user information related to a user; a determination means for determining one or more residential environments to be recommended to the user after a predetermined period of time by referring to the user information; an output means for outputting residential environment information indicating the one or more residential environments and recommendation reason information indicating a reason for recommending each of the one or more residential environments; An information processing device comprising:

[0156] (Appendix A2) the determination means determines one or more residential environments to be recommended to the user after a predetermined period of time using an estimation model that estimates residential environments to be recommended to the user after a predetermined period of time, based on user information related to the user as an input; 10. The information processing device according to claim 1,

[0157] (Appendix A3) The user information includes a plurality of pieces of information related to the user, further comprising a receiving means for receiving an input of a weighting ratio for each of the plurality of pieces of information related to the user; the determining means determines the one or more residential environments based on the ratio of each of the plurality of pieces of information related to the users, with reference to the input; An information processing device according to appendix A1 or A2.

[0158] (Appendix A4) the acquiring means acquires user information of each of a plurality of users; the determining means refers to the degree of similarity between the user information of each of the plurality of users and determines the home environment to be recommended to each of the plurality of users. An information processing device according to any one of appendices A1 to A3.

[0159] (Appendix A5) The recommendation reason information includes information indicating a relationship between the user and the home environment. An information processing device according to any one of appendices A1 to A4.

[0160] (Appendix A6) The user information includes information about the user's hobbies and preferences. An information processing device according to any one of appendices A1 to A5.

[0161] (Appendix A7) The user information includes information about the user's purchase history. An information processing device according to any one of appendices A1 to A6.

[0162] (Appendix A8) The user information includes information about the user's behavior history. An information processing device according to any one of appendices A1 to A7.

[0163] (Appendix A9) The user information includes information about the attributes of the user. An information processing device according to any one of appendices A1 to A8.

[0164] (Appendix A10) The user information includes information about the user's assets. An information processing device according to any one of appendices A1 to A9.

[0165] (Appendix A11) The user information includes information about the user's health. An information processing device according to any one of appendices A1 to A10.

[0166] (Appendix A12) The user information includes information about the residential environment in which the user currently lives. An information processing device according to any one of appendices A1 to A11.

[0167] (Appendix A13) The recommendation reason information includes information indicating characteristics of the home environment. An information processing device according to any one of appendices A1 to A12.

[0168] (Appendix A14) The determining means an asset calculation process that refers to the user information and calculates the asset of the user after the predetermined period; and a living expenses calculation process that calculates the user's living expenses after the predetermined period by referring to the user information and the assets calculated in the asset calculation process; Run a lifespan estimation model that estimates the user's lifespan using the user information as an input; an attribute expansion model that expands the attributes of the user using the user information as an input; a residential area candidate estimation model that estimates one or more residential areas to be recommended to the user as residential areas after the predetermined period of time using the user information and the extension results of the attribute extension model as inputs; and a residential environment estimation model that estimates one or more residential environments to be recommended to a user after a predetermined period of time using the estimation result by the residential area candidate estimation model and the living expenses as inputs; determining one or more home environments to recommend to the user after a predetermined period of time using the 10. The information processing device according to claim 1,

[0169] (Appendix A15) the determination means uses the user information, the estimation result by the housing environment estimation model, and the living expenses as inputs to generate a combinatorial optimization model that estimates a community to be recommended to one or more users; and determining one or more home environments to recommend to the user after a predetermined period of time using the above information. 10. The information processing device according to claim 9, wherein the information processing device is a

[0170] [Appendix B] This disclosure includes the techniques described in the following appendices. However, the present invention is not limited to the techniques described in the following appendices, and various modifications are possible within the scope of the claims.

[0171] (Appendix B1) At least one processor an acquisition process for acquiring user information related to the user; a determination process for determining one or more residential environments to be recommended to the user after a predetermined period of time by referring to the user information; an output process for outputting residential environment information indicating the one or more residential environments and recommendation reason information indicating a reason for recommending each of the one or more residential environments; An information processing method including:

[0172] (Appendix B2) In the determination process, the at least one processor determines one or more residential environments to be recommended to the user after a predetermined period of time using an estimation model that estimates residential environments to be recommended to the user after a predetermined period of time, with user information related to the user as an input. 1. The information processing method described in Appendix B1.

[0173] (Appendix B3) The user information includes a plurality of pieces of information related to the user, The at least one processor further includes a receiving process for receiving an input of a weighting ratio for each of the plurality of pieces of information related to the user; In the determination process, the at least one processor refers to the input and determines the one or more residential environments based on the ratio of each of the plurality of pieces of information related to the users. 1. An information processing method as described in Appendix B1 or B2.

[0174] (Appendix B4) In the acquisition process, the at least one processor acquires user information of each of a plurality of users; In the determination process, the at least one processor refers to a degree of similarity between pieces of user information of the plurality of users, and determines a home environment to be recommended to each of the plurality of users. 1. An information processing method according to any one of appendices B1 to B3.

[0175] (Appendix B5) The recommendation reason information includes information indicating a relationship between the user and the home environment. 1. An information processing method according to any one of appendices B1 to B4.

[0176] (Appendix B6) The user information includes information about the user's hobbies and preferences. 1. An information processing method according to any one of Appendices B1 to B5.

[0177] (Appendix B7) The user information includes information about the user's purchase history. 10. An information processing method according to any one of appendices B1 to B6.

[0178] (Appendix B8) The user information includes information about the user's behavior history. 10. An information processing method according to any one of appendices B1 to B7.

[0179] (Appendix B9) The user information includes information about the attributes of the user. 10. An information processing method according to any one of appendices B1 to B8.

[0180] (Appendix B10) The user information includes information about the user's assets. 10. An information processing method according to any one of appendices B1 to B9.

[0181] (Appendix B11) The user information includes information about the user's health. 10. The information processing method according to any one of appendices B1 to B10.

[0182] (Appendix B12) The user information includes information about the residential environment in which the user currently lives. 10. The information processing method according to any one of appendices B1 to B11.

[0183] (Appendix B13) The recommendation reason information includes information indicating characteristics of the home environment. 10. The information processing method according to any one of appendices B1 to B12.

[0184] (Appendix B14) In the determination process, the at least one processor: an asset calculation process that refers to the user information and calculates the asset of the user after the predetermined period; and a living expenses calculation process that calculates the user's living expenses after the predetermined period by referring to the user information and the assets calculated in the asset calculation process; Run a lifespan estimation model that estimates the user's lifespan using the user information as an input; an attribute expansion model that expands the attributes of the user using the user information as an input; a residential area candidate estimation model that estimates one or more residential areas to be recommended to the user as residential areas after the predetermined period of time using the user information and the extension results of the attribute extension model as inputs; and a residential environment estimation model that estimates one or more residential environments to be recommended to a user after a predetermined period of time using the estimation result by the residential area candidate estimation model and the living expenses as inputs; determining one or more home environments to recommend to the user after a predetermined period of time using the 1. The information processing method described in Appendix B1.

[0185] (Appendix B15) In the determination process, the at least one processor uses the user information, the estimation result by the residential environment estimation model, and the living expenses as inputs to generate a combinatorial optimization model that estimates communities to be recommended to one or more users; and determining one or more home environments to recommend to the user after a predetermined period of time using the above information. 1. The information processing method described in Appendix B14.

[0186] [Appendix C] This disclosure includes the techniques described in the following appendices. However, the present invention is not limited to the techniques described in the following appendices, and various modifications are possible within the scope of the claims.

[0187] (Appendix C1) A program that causes a computer to function as an information processing device, The computer acquiring means for acquiring user information related to a user; a determination means for determining one or more residential environments to be recommended to the user after a predetermined period of time by referring to the user information; an output means for outputting residential environment information indicating the one or more residential environments and recommendation reason information indicating a reason for recommending each of the one or more residential environments; An information processing program that functions as a

[0188] (Appendix C2) the determination means determines one or more residential environments to be recommended to the user after a predetermined period of time using an estimation model that estimates residential environments to be recommended to the user after a predetermined period of time, based on user information related to the user as an input; An information processing program as described in Appendix C1.

[0189] (Appendix C3) The user information includes a plurality of pieces of information related to the user, The computer is further configured to function as a receiving unit that receives an input of a weighting ratio for each of the plurality of pieces of information related to the user; the determining means determines the one or more residential environments based on the ratio of each of the plurality of pieces of information related to the users, with reference to the input; An information processing program according to appendix C1 or C2.

[0190] (Appendix C4) the acquiring means acquires user information of each of a plurality of users; the determining means refers to the degree of similarity between the user information of each of the plurality of users and determines the home environment to be recommended to each of the plurality of users. An information processing program according to any one of appendices C1 to C3.

[0191] (Appendix C5) The recommendation reason information includes information indicating a relationship between the user and the home environment. An information processing program according to any one of appendices C1 to C4.

[0192] (Appendix C6) The user information includes information about the user's hobbies and preferences. An information processing program according to any one of appendices C1 to C5.

[0193] (Appendix C7) The user information includes information about the user's purchase history. An information processing program according to any one of appendices C1 to C6.

[0194] (Appendix C8) The user information includes information about the user's behavior history. An information processing program according to any one of appendices C1 to C7.

[0195] (Appendix C9) The user information includes information about the attributes of the user. An information processing program according to any one of appendices C1 to C8.

[0196] (Appendix C10) The user information includes information about the user's assets. An information processing program according to any one of appendices C1 to C9.

[0197] (Appendix C11) The user information includes information about the user's health. An information processing program according to any one of appendices C1 to C10.

[0198] (Appendix C12) The user information includes information about the residential environment in which the user currently lives. An information processing program according to any one of appendices C1 to C11.

[0199] (Appendix C13) The recommendation reason information includes information indicating characteristics of the home environment. An information processing program according to any one of appendices C1 to C12.

[0200] (Appendix C14) The determining means an asset calculation process that refers to the user information and calculates the asset of the user after the predetermined period; and a living expenses calculation process that calculates the user's living expenses after the predetermined period by referring to the user information and the assets calculated in the asset calculation process; Run a lifespan estimation model that estimates the user's lifespan using the user information as an input; an attribute expansion model that expands the attributes of the user using the user information as an input; a residential area candidate estimation model that estimates one or more residential areas to be recommended to the user as residential areas after the predetermined period of time using the user information and the extension results of the attribute extension model as inputs; and a residential environment estimation model that estimates one or more residential environments to be recommended to a user after a predetermined period of time using the estimation result by the residential area candidate estimation model and the living expenses as inputs; determining one or more home environments to recommend to the user after a predetermined period of time using the An information processing program as described in Appendix C1.

[0201] (Appendix C15) the determination means uses the user information, the estimation result by the housing environment estimation model, and the living expenses as inputs to generate a combinatorial optimization model that estimates a community to be recommended to one or more users; and determining one or more home environments to recommend to the user after a predetermined period of time using the above information. An information processing program as described in Appendix C14.

[0202] [Appendix D] This disclosure includes the techniques described in the following appendices. However, the present invention is not limited to the techniques described in the following appendices, and various modifications are possible within the scope of the claims.

[0203] (Appendix D1) at least one processor, an acquisition process for acquiring user information related to the user; a determination process for determining one or more residential environments to be recommended to the user after a predetermined period of time by referring to the user information; an output process for outputting residential environment information indicating the one or more residential environments and recommendation reason information indicating a reason for recommending each of the one or more residential environments; An information processing device that executes the above.

[0204] The information processing device may further include a memory, and the memory may store a program for causing the at least one processor to execute each of the processes.

[0205] (Appendix D2) In the determination process, the at least one processor determines one or more residential environments to be recommended to the user after a predetermined period of time using an estimation model that estimates residential environments to be recommended to the user after a predetermined period of time, with user information related to the user as an input. 10. The information processing device according to claim 9, wherein the information processing device is a device for processing information.

[0206] (Appendix D3) The user information includes a plurality of pieces of information related to the user, the at least one processor: further performing a receiving process of receiving an input of a weighting ratio for each of the plurality of pieces of information related to the user; In the determination process, the at least one processor refers to the input and determines the one or more residential environments based on the ratio of each of the plurality of pieces of information related to the users. An information processing device according to appendix D1 or D2.

[0207] (Appendix D4) In the acquisition process, the at least one processor acquires user information of each of a plurality of users; In the determination process, the at least one processor refers to a degree of similarity between pieces of user information of the plurality of users, and determines a home environment to be recommended to each of the plurality of users. An information processing device according to any one of appendices D1 to D3.

[0208] (Appendix D5) The recommendation reason information includes information indicating a relationship between the user and the home environment. An information processing device according to any one of appendices D1 to D4.

[0209] (Appendix D6) The user information includes information about the user's hobbies and preferences. An information processing device according to any one of appendices D1 to D5.

[0210] (Appendix D7) The user information includes information about the user's purchase history. An information processing device according to any one of appendices D1 to D6.

[0211] (Appendix D8) The user information includes information about the user's behavior history. An information processing device according to any one of appendices D1 to D7.

[0212] (Appendix D9) The user information includes information about the attributes of the user. An information processing device according to any one of appendices D1 to D8.

[0213] (Appendix D10) The user information includes information about the user's assets. An information processing device according to any one of appendices D1 to D9.

[0214] (Appendix D11) The user information includes information about the user's health. An information processing device according to any one of appendices D1 to D10.

[0215] (Appendix D12) The user information includes information about the residential environment in which the user currently lives. An information processing device according to any one of appendices D1 to D11.

[0216] (Appendix D13) The recommendation reason information includes information indicating characteristics of the home environment. An information processing device according to any one of appendices D1 to D12.

[0217] (Appendix D14) In the determination process, the at least one processor: an asset calculation process that refers to the user information and calculates the asset of the user after the predetermined period; and a living expenses calculation process that calculates the user's living expenses after the predetermined period by referring to the user information and the assets calculated in the asset calculation process; Run a lifespan estimation model that estimates the user's lifespan using the user information as an input; an attribute expansion model that expands the attributes of the user using the user information as an input; a residential area candidate estimation model that estimates one or more residential areas to be recommended to the user as residential areas after the predetermined period of time using the user information and the extension results of the attribute extension model as inputs; and a residential environment estimation model that estimates one or more residential environments to be recommended to a user after a predetermined period of time using the estimation result by the residential area candidate estimation model and the living expenses as inputs; determining one or more home environments to recommend to the user after a predetermined period of time using the 10. The information processing device according to claim 9, wherein the information processing device is a device for processing information.

[0218] (Appendix D15) In the determination process, the at least one processor uses the user information, the estimation result by the residential environment estimation model, and the living expenses as inputs to generate a combinatorial optimization model that estimates communities to be recommended to one or more users; and determining one or more home environments to recommend to the user after a predetermined period of time using the above information. 10. The information processing device according to claim 9, wherein the information processing device is an information processing device according to claim 14.

[0219] [Appendix E] This disclosure includes the techniques described in the following appendices. However, the present invention is not limited to the techniques described in the following appendices, and various modifications are possible within the scope of the claims.

[0220] (Appendix E1) A non-transitory recording medium on which a program that causes a computer to function as an information processing device is recorded, The program causes the computer to: an acquisition process for acquiring user information related to the user; a determination process for determining one or more residential environments to be recommended to the user after a predetermined period of time by referring to the user information; an output process for outputting residential environment information indicating the one or more residential environments and recommendation reason information indicating a reason for recommending each of the one or more residential environments; A non-transitory recording medium on which an information processing program for executing the above is recorded. [Explanation of symbols]

[0221] 1, 2, 3 Information processing equipment 11 Acquisition Department 12 Decision Section 13 Output section 14 Reception Department 121 Asset Calculation Department 122 Living Cost Calculation Department USI User Information HEI housing environment information RRI recommendation reason information EM estimation model LEM Life Estimation Model AEM Attribute Extension Model REM residential area candidate estimation model HEM Residential Environment Estimation Model OM Combinatorial Optimization Model

Claims

1. acquiring means for acquiring user information related to a user; a determination means for determining one or more residential environments to be recommended to the user after a predetermined period of time by referring to the user information; an output means for outputting residential environment information indicating the one or more residential environments and recommendation reason information indicating a reason for recommending each of the one or more residential environments; An information processing device comprising:

2. the determination means determines one or more residential environments to be recommended to the user after a predetermined period of time using an estimation model that estimates residential environments to be recommended to the user after a predetermined period of time, based on user information related to the user as an input; The information processing device according to claim 1 .

3. The user information includes a plurality of pieces of information related to the user, further comprising a receiving means for receiving an input of a weighting ratio for each of the plurality of pieces of information related to the user; the determining means determines the one or more residential environments based on the ratio of each of the plurality of pieces of information related to the users, with reference to the input; 3. The information processing device according to claim 1.

4. the acquiring means acquires user information of each of a plurality of users; the determining means determines a home environment to be recommended to each of the plurality of users by referring to a degree of similarity between pieces of user information of the plurality of users; 3. The information processing device according to claim 1.

5. The recommendation reason information includes information indicating a relationship between the user and the home environment.

3. The information processing device according to claim 1.

6. The user information includes information about the user's hobbies and preferences.

3. The information processing device according to claim 1.

7. The user information includes information about the user's purchase history.

3. The information processing device according to claim 1.

8. The user information includes information about the user's behavior history.

3. The information processing device according to claim 1.

9. At least one processor an acquisition process for acquiring user information related to the user; a determination process for determining one or more residential environments to be recommended to the user after a predetermined period of time by referring to the user information; an output process for outputting residential environment information indicating the one or more residential environments and recommendation reason information indicating a reason for recommending each of the one or more residential environments; An information processing method including:

10. A program that causes a computer to function as an information processing device, The computer acquiring means for acquiring user information related to a user; a determination means for determining one or more residential environments to be recommended to the user after a predetermined period of time by referring to the user information; an output means for outputting residential environment information indicating the one or more residential environments and recommendation reason information indicating a reason for recommending each of the one or more residential environments; An information processing program that functions as a

Images