Information processing device and information processing method

Abstract

An information processing device (10) is provided with: a reception unit (11) that receives generation request information which is information for requesting generation of recommendation information pertaining to coordination of furniture in a room, and which includes user information including at least information pertaining to the room; a determination unit (12) that, on the basis of the user information, determines an advice policy including at least the concept of the room; and an output unit (13) that outputs a prompt for indicating to generate recommendation information pertaining to the coordination of the furniture in the room on the basis of the determined advice policy.

Description

Information processing device and information processing method

[0001] The present disclosure relates to an information processing device and an information processing method.

[0002] There is a very high need for recommendations on how to coordinate furniture for a room, and Patent Document 1 below describes a web service that allows users to receive recommendations on how to coordinate furniture for a room without having to go to an actual furniture store. However, the service described in Patent Document 1 requires users to select a taste (design concept) that is the basic idea of ​​the design, and then select detailed content from images of furniture placement candidates that correspond to the selected taste, and the content selected by the user is a very important factor in receiving the final recommendation.

[0003] Japanese Patent Application Laid-Open No. 2021-096545

[0004] However, in reality, there are many cases where a user does not have strong requests or preferences regarding furniture arrangement, and would rather prefer recommendations regarding furniture arrangement that take into consideration information about the room, user attribute information, and coordination condition information (e.g., budget, delivery date, furniture already owned, etc.) without placing a burden on the user to make a selection. In such cases, the service described in Patent Document 1 may cause the user difficulty and stress in making various choices, and as a result, there is a risk that the user will not receive effective suggestions.

[0005] Meanwhile, in recent years, various types of content have been generated using generative artificial intelligence (AI) models. A generative AI model is a model that can generate content (generation results) in response to a prompt containing input information, according to any one or a combination of instructions, context, questions, and output formats indicated by the prompt, and return the generated content as response information.

[0006] Taking the above circumstances into consideration, the present disclosure aims to utilize a generative AI model to easily obtain appropriate recommendation information regarding furniture coordination in a room without placing an excessive burden on the user.

[0007] The information processing device according to the present disclosure includes a reception unit that receives request information for generating recommendation information regarding the coordination of furniture in a room, the request information including user information including at least information regarding the room; a determination unit that determines an advice policy including at least a concept of the room based on the user information; and an output unit that outputs a prompt to instruct the generation of recommendation information regarding the coordination of furniture in the room based on the determined advice policy.

[0008] According to the present disclosure, by utilizing a generative AI model, appropriate recommendation information regarding furniture coordination in a room can be easily obtained without placing an excessive burden on the user.

[0009] It is a block diagram of the entire system including the information processing device It is a flow diagram of the process executed by the information processing device It is a block diagram of another example of the entire system It is a block diagram of the hardware configuration of the information processing device It is a block diagram of the entire system including the information processing device ...

[0010] Hereinafter, an embodiment of an information processing device and an information processing method according to the present disclosure will be described with reference to the drawings. In the following embodiment, a form will be described in which a large language model (LLM) that is mainly used for text generation is used as an example of a generative AI model.

[0011] [Configuration of a system including an information processing device] Fig. 1 shows a configuration diagram of a system 1 including an information processing device 10 according to the present disclosure. As shown in Fig. 1, the system 1 includes an external server 30A on which a large-scale language model (LLM) 30 runs, the information processing device 10, and an external server 20A on which a reference system runs. The external server 20A includes a reference database (reference DB) 20 that stores various data referenced in the reference system.

[0012] The reference DB 20 stores various information such as the following. For example, the reference DB 20 stores (1) various user attribute information (e.g., age, gender, address, hobbies, preferences, etc.) in association with user identification information (user ID), and is configured to allow attribute information to be retrieved using the user ID as a key. The reference DB 20 also stores (2) classification rule information indicating classification rules for multiple personas, in which various users are pre-classified into multiple types based on their preferences regarding furniture coordination. Here, "persona" refers to various user profiles (user characteristics) established based on detailed conditions assuming specific situations. For example, user characteristics include "a financially well-off person in their 50s" and "a person in their 50s who is busy with work and values ​​practicality and efficiency." By referencing the classification rule information, a persona is uniquely determined based on a combination of the user's attribute information and coordination condition information. For example, examples of classification rule information include: Persona A: age group 50s, high budget, no existing furniture, and... Persona B: age group 50s, low budget, two existing pieces of furniture, and... Persona C: age group 30s, high budget, no existing furniture, and... Persona D: age group 30s, medium budget, two existing pieces of furniture, and... Persona E: age group 20s, medium budget, no existing furniture, and...

[0013] In addition, the reference DB 20 stores (3) a concept correspondence table such as the one below, in which concept information corresponding to personas is associated in tabular form, and by referring to this concept correspondence table, a concept can be uniquely determined according to the user's persona.

[0014] Furthermore, the reference DB 20 stores (4) candidate information for coordinated outfit suggestions corresponding to concept information, etc. Specifically, the candidate information for coordinated outfit suggestions corresponding to at least one of concept information, persona information, and attribute information includes, for example, the following: For a concept including the keyword "calm," it is recommended to use indirect lighting with a warm white light. For personas C and E, wallpaper should be △△ manufactured by S company or □□ manufactured by T company. For attribute information including the hobby "gardening," it is recommended to place a vase ○○ manufactured by K company on an L-size table □□ manufactured by K company placed in the center of the room. These candidate information for coordinated outfit suggestions are included in prompts to the LLM 30, which determines and outputs coordinated outfit suggestions based on the candidate information.

[0015] The information processing device 10 may employ various information processing devices (smartphones, mobile phones, smartwatches, wearable devices, notebook computers, desktop computers, servers, etc.) as hardware.

[0016] An RAG (Retrieval-Augmented Generation) system application is installed on the information processing device 10, and the RAG system operates. The RAG system is a type of prompt extension technology used for, for example, corporate information collaboration between LLMs. Specifically, when a generation request is made to an LLM via a prompt based on a content generation request, the system searches for related information (reference information) in advance if necessary and requests the LLM to generate the obtained information along with an instruction statement. The present disclosure corresponds to an invention that extends and improves the functions of the RAG system, and has an aspect of enriching and optimizing prompts for the LLM 30 using various information stored in a reference DB 20 in an external server 20A that cannot be directly accessed by the LLM 30 or various information obtained by searching an external server (not shown).

[0017] The above-mentioned prompt refers to information indicating an instruction or question input to a generative AI model (LLM 30 in this embodiment) in an interactive system such as a dialogue with the generative AI model or a command line interface (CLI). The prompt input to the LLM 30 in this embodiment is text data including, for example, information indicating the command to be executed by the LLM 30, the task to be executed by the LLM 30, the background / context to be considered by the LLM 30 (e.g., role, condition), the question to be answered by the LLM 30, and the output format of the response information from the LLM 30. The prompt may also include input information that is the target of the command / task to be executed by the LLM 30. Examples of such input information include data files with file names including a predetermined extension, such as text data, image data, application-related data, audio data, video data, and still image data. The above-mentioned application-related data refers to data such as document data, table data, and graph data that can be processed by a default application program.

[0018] In order to realize the functions according to the present disclosure, the information processing device 10 includes a receiving unit 11, a determining unit 12, and an output unit 13. The functions of each unit will be described below.

[0019] The reception unit 11 is a functional unit that receives generation request information for recommendation information regarding furniture coordination in a room. The generation request information includes user information including at least information about the room. Specifically, the user information may include (a) information about the room, (b) a user ID or user attribute information (e.g., age, gender, address, hobbies, preferences (what they tend to spend most money on), etc.), and (c) information about coordination conditions (e.g., budget, deadline, use and purpose of the room, information about existing furniture, timing, etc.).

[0020] (a) Information about the room includes, for example, information indicating the room layout, wallpaper color, etc., and may also include information about furniture already placed in the room. Furthermore, it is not limited to text information, but may also include image information and video information. Regarding (b) above, if (b) above includes only a "user ID," the reception unit 11 acquires the user's attribute information from various user attribute information stored in the reference DB 20 using the user ID as a key. Regarding (c) information about coordination conditions, for example, the "budget" may be a budget for the entire interior, a maximum price for each piece of furniture, or a budget for furniture added to existing furniture. Examples of the "room use" include a workroom (e.g., for telecommuting, store use, office use, etc.), a living room, a child's room, etc. Examples of the "purpose" include moving to a new home or rearranging furniture in the same home. Examples of the "time" include seasons (spring, summer, fall, winter), summer vacation, the Christmas season, the first month of the new fiscal year (April), etc.

[0021] The above-mentioned generation request information is notified to the reception unit 11, for example, when a generation request button provided on a web page or application page displayed on the display of the information processing device 10 is pressed, and the reception unit 11 accepts the generation request information.

[0022] The determination unit 12 is a functional unit that determines an advice policy including at least a room concept based on user information. For example, the determination unit 12 refers to the classification rule information stored in the reference DB 20 and determines which of the multiple personas previously classified into multiple types the user corresponds to based on at least one of "user attribute information" or "condition information related to coordination" included in the user information. Note that, in addition to determining the persona based on rules using the predetermined classification rule information as described above, a method of determining the persona using a learning model that has learned the relationship between at least one of "user attribute information" or "condition information related to coordination" and various personas may also be adopted.

[0023] Furthermore, the determination unit 12 determines an advice policy including a room concept based on preferences corresponding to the determined persona of the user. For example, the determination unit 12 refers to the above-mentioned concept correspondence table stored in the reference DB 20 to identify an appropriate concept corresponding to the user's persona, and determines an advice policy based on the identified concept. Note that, in addition to determining the advice policy by referring to the predetermined concept correspondence table as described above, a method of determining the advice policy using a learning model that has learned the relationships between various personas and concepts may also be adopted.

[0024] The content determined by the determination unit 12, i.e., the advice policy information including the room concept, may be information indicating the concept of each piece of furniture or the coordination of the entire room. For example, it may be selection information that selects at least one from multiple categories such as "Type 1: Modern-style furniture / interior coordination," "Type 2: Hotel-like-style furniture / interior coordination," "Type 3: Natural-style furniture / interior coordination," "Type 4: Resort-style furniture / interior coordination," and "Type 5: Asian-style furniture / interior coordination." It may also be information such as Brooklyn style, mid-century style, or European antique style. The advice policy information may also include information regarding budget, such as the estimated budget, upper limit, and allocation for each piece of furniture. The advice policy information may also include information regarding timing, such as a specific delivery date and the desired time for moving (specific dates, information regarding whether it is urgent, etc.).

[0025] The output unit 13 is a functional unit that outputs a prompt for instructing the generation of recommendation information regarding furniture coordination in a room based on the determined advice policy. For example, the output unit 13 outputs a prompt for instructing the generation of recommendation information regarding furniture coordination in a room based on an "advice policy including a room concept" determined based on preferences corresponding to the user's persona.

[0026] An example of a prompt that can be output is: "Role: You are a furniture interior coordinator. Task: Generate a recommendation sentence for furniture to place in a room. Conditions: - The room is a rectangle measuring XX meters in length and △△ meters in width. - The total budget is □□ yen. - Recommend furniture that fits within the budget. - The delivery date is XX month △ day. - Meeting the delivery date is a must. - Suggest an interior design that suits the room. - Present furniture that goes well with the two existing pieces of furniture. - You may also include an image (layout) of how the furniture will be arranged in the room. - Explain the concept behind the furniture recommendation. - Explain the reason for the recommendation."

[0027] The output unit 13 also receives and outputs recommendation information as a generation result output from the LLM 30 (generative AI model) in response to the input of a prompt. Specific examples of the recommendation information that is output will be described later, but the contents include at least one or more types of furniture, information that identifies the furniture, information associated with the furniture (price, size, URL of the furniture sales website, etc.), a description of how to arrange the furniture in a room (or an image of the same), an explanation of the concept, and the reason for the recommendation.

[0028] As a variation of the above embodiment, the user information may include preference level information, which is information indicating the degree of preference for each of a plurality of preferences held by the user, and the determination unit 12 may determine an advice policy including the preference level information. Specifically, the determination unit 12 may determine "recommendation level information," which is information indicating the degree of recommendation for each of a plurality of types of furniture to be placed in the room, based on the preference level information, and determine an advice policy including the determined recommendation level information. Note that in this case, the determination of the persona described above is not a required requirement. For example, an advice policy including preference level information such as "resort taste = 70%, Asian taste = 30%" may be determined, or an advice policy including recommendation level information for each of a plurality of types of furniture, such as "Thai-made table X = 70%, Indian-made sofa Y = 40%, Vietnamese-made chair Z = 20%, based on the preference level information, may be determined.

[0029] In the above modification, the output unit 13 may output a prompt including an instruction to generate recommendation information by using preference degree information included in the advice policy. Specifically, the output unit 13 may output a prompt including an instruction to generate recommendation information regarding a plurality of types of furniture by using recommendation degree information included in the advice policy.

[0030] By outputting a prompt that includes an instruction to generate recommendation information using the above-mentioned preference level information (e.g., resort taste = 70%, Asian taste = 30%) or recommendation level information (e.g., Thai-made table X = 70%, Indian-made sofa Y = 40%, Vietnamese-made chair Z = 20%), it is possible to freely instruct the generation of content based on recommendation levels related to multiple elements, as if a human had thought about it. Note that the information indicating the levels may be information determined by the determination unit 12 as described above, information received from the user, or information registered in advance by the operator.

[0031] [Regarding Processing Executed in Information Processing Apparatus] Hereinafter, processing executed in the information processing apparatus 10 (processing related to the information processing method of the present disclosure) will be described with reference to the flow diagram of FIG.

[0032] When a user presses a generation request button provided on a web page or application page displayed on the display of the information processing device 10, a request for generation of recommended information regarding furniture coordination in a room is notified, and the reception unit 11 accepts the request for generation, which triggers the start of the processing of Figure 2.

[0033] In response to receiving the creation request information, the reception unit 11 acquires user information included in the creation request information (step S1). Specifically, the reception unit 11 acquires user information including the above-mentioned (a) information about the room, (b) user ID or user attribute information (e.g., age, gender, address, hobbies, preferences (what the user tends to spend most money on), etc.), and (c) information about coordination conditions (e.g., budget, delivery date, room use, purpose, information about existing furniture, timing, etc.). If the above (b) includes only the "user ID," the reception unit 11 acquires the user's attribute information from various user attribute information stored in the reference DB 20 of the external server 20A using the user ID as a key.

[0034] Next, the determination unit 12 determines an advice policy including the concept of the room as follows (step S2). Specifically, the determination unit 12 refers to the "classification rule information" stored in the reference DB 20 and determines which of the multiple personas previously classified into multiple types the user belongs to, based on at least one of the "user attribute information" and the "coordination condition information" included in the user information. Furthermore, the determination unit 12 refers to the "concept correspondence table" stored in the reference DB 20 and determines an appropriate advice policy according to the preferences corresponding to the user's persona.

[0035] Next, the output unit 13 outputs a prompt for instructing the generation of recommendation information related to the coordination of furniture in the room based on the advice policy as described above (step S3).

[0036] The LLM 30 then outputs, as a generated result, recommendation information regarding the coordination of furniture in the room, generated based on the prompt. The output unit 13 then acquires and outputs the generated result (recommendation information) from the LLM 30 (step S4). Examples of the output recommendation information include: "Why not place table A, made in Thailand, in the center and sofa B, made in India, by the window? Recommended table A is priced at XX, large size, and has a sales website URL of "www.xxxx.com." Recommended sofa B is priced at △△, medium size, and has a sales website URL of "www.yyyy.com." The concept is "Evenly arrange multiple new, luxurious pieces of furniture throughout the room. Emphasize a sense of spaciousness, comfort, and calmness..." The reason for the recommendation is that your budget is sufficiently high, so you have purchased new, luxurious furniture. I recommend these pieces because I think they are perfect for you, who value spaciousness, comfort, and calmness."

[0037] According to the embodiment described above, by utilizing the generative AI model (LLM30), it is possible to easily obtain appropriate recommendation information regarding the coordination of furniture in a room that is appropriately customized according to the user's attribute information, condition information, etc., without placing an excessive burden on the user.

[0038] Furthermore, as in the modified example described above, by outputting a prompt that includes instructions to generate recommendation information using preference level information (e.g., resort taste = 70%, Asian taste = 30%) or recommendation level information (e.g., Thai-made table X = 70%, Indian-made sofa Y = 40%, Vietnamese-made chair Z = 20%), a further effect can be obtained in that content can be freely generated based on recommendation levels related to multiple elements, as if thought by a human being.

[0039] (Modification of System 1) System 1 is not limited to the configuration shown in FIG. 1 , and may be configured as shown in FIG. 3 , in which LLM 30 is implemented inside information processing device 10. As described above, information processing device 10 may be a mobile terminal such as a smartphone, mobile phone, smartwatch, or wearable device, and LLM 30 may be implemented in such a mobile terminal. This configuration can be realized by installing an application that executes the functions of LLM 30 on information processing device 10. Furthermore, while FIG. 1 shows an example in which reference DB 20 is implemented outside information processing device 10 (e.g., on a network), reference DB 20 may also be implemented inside information processing device 10.

[0040] The gist of the present disclosure lies in the following [1] to [6]. [1] An information processing device comprising: a receiving unit that receives generation request information for recommendation information related to furniture coordination in a room, the generation request information including user information including at least information related to the room; a determining unit that determines an advice policy including at least a concept of the room based on the user information; and an output unit that outputs a prompt to instruct generation of recommendation information related to furniture coordination in the room based on the determined advice policy. [2] The information processing device described in [1], wherein the determining unit determines to which persona the user corresponds from a plurality of personas that are pre-classified into a plurality of types according to preferences related to furniture coordination, based on at least one of attribute information of the user or condition information related to the coordination included in the user information, and determines the advice policy including the concept of the room based on the preference corresponding to the determined persona of the user. [3] The information processing device according to [1] or [2], wherein the user information includes preference degree information that is information indicating a degree of preference for each of a plurality of preferences held by the user, the determination unit determines the advice policy that includes the preference degree information, and the output unit uses the preference degree information included in the advice policy to output the prompt that includes a command to generate the recommendation information. [4] The information processing device according to [3], wherein the determination unit determines recommendation degree information that is information indicating a degree of recommendation for each of a plurality of types of furniture to be placed in the room based on the preference degree information, and determines the advice policy that includes the determined recommendation degree information, and the output unit outputs the prompt that includes a command to generate the recommendation information for the plurality of types of furniture using the recommendation degree information included in the advice policy. [5] The information processing device according to any one of [1] to [4], wherein the output unit receives and outputs the recommendation information as a generation result output from a generative AI model in response to input of the prompt.[6] An information processing method comprising: a step of receiving, by an information processing device, request information for generating recommendation information regarding furniture coordination in a room, the request information including user information including at least information regarding the room; a step of determining, by the information processing device, an advice policy including at least a concept of the room based on the user information; and a step of outputting, by the information processing device, a prompt for instructing the generation of recommendation information regarding furniture coordination in the room based on the determined advice policy.

[0041] [Explanation of Terms, Explanation of Hardware Configuration (FIG. 4), etc.] The block diagrams used in the description of the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of at least one of hardware and software. Furthermore, the method for realizing each functional block is not particularly limited. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are directly or indirectly connected (e.g., wired, wireless, etc.) and these multiple devices. The functional block may also be realized by combining software with the single device or multiple devices.

[0042] Functions include, but are not limited to, judgment, determination, assessment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, consideration, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assignment. For example, a functional block (component) that performs transmission is called a transmitting unit or transmitter. As mentioned above, there are no particular limitations on how these functions are implemented.

[0043] For example, an information processing device according to an embodiment of the present disclosure may function as a computer that executes the processes of the present disclosure. Fig. 4 is a diagram illustrating an example of a hardware configuration of an information processing device 10 according to an embodiment of the present disclosure. The information processing device 10 described above may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, etc.

[0044] In the following description, the term "apparatus" can be interpreted as a circuit, a device, a unit, etc. The hardware configuration of the information processing device 10 may be configured to include one or more of the apparatuses shown in the drawings, or may be configured to exclude some of the apparatuses.

[0045] Each function of the information processing device 10 is realized by loading specified software (programs) onto hardware such as the processor 1001 and memory 1002, causing the processor 1001 to perform calculations, control communication via the communication device 1004, and control at least one of reading and writing data in the memory 1002 and storage 1003.

[0046] The processor 1001 controls the entire computer by running, for example, an operating system, and may be configured as a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, a register, etc.

[0047] The processor 1001 also reads programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002 and executes various processes in accordance with these. The programs used are those that cause a computer to execute at least some of the operations described in the above-described embodiments. While the various processes have been described as being executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented by one or more chips. The programs may be transmitted from a network via a telecommunications line.

[0048] The memory 1002 is a computer-readable recording medium and may be configured by, for example, at least one of a read-only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a random access memory (RAM), etc. The memory 1002 may also be called a register, a cache, a main memory (primary storage device), etc. The memory 1002 can store executable programs (program codes), software modules, etc. for implementing a wireless communication method according to an embodiment of the present disclosure.

[0049] Storage 1003 is a computer-readable recording medium, and may be composed of at least one of, for example, an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray (registered trademark) disk), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy (registered trademark) disk, a magnetic strip, etc. Storage 1003 may also be referred to as an auxiliary storage device. The above-mentioned storage medium may be, for example, a database, a server, or other appropriate medium including at least one of memory 1002 and storage 1003.

[0050] The communication device 1004 is hardware (transmission / reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as, for example, a network device, a network controller, a network card, a communication module, etc. The communication device 1004 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc. to realize at least one of frequency division duplex (FDD) and time division duplex (TDD).

[0051] The input device 1005 is an input device (e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that receives input from the outside. The output device 1006 is an output device (e.g., a display, a speaker, an LED lamp, etc.) that outputs to the outside. The input device 1005 and the output device 1006 may be integrated into one device (e.g., a touch panel).

[0052] Furthermore, each device, such as the processor 1001 and the memory 1002, is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses between each device.

[0053] The information processing device 10 may also be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized by the hardware. For example, the processor 1001 may be implemented using at least one of these pieces of hardware.

[0054] The notification of information is not limited to the aspects / embodiments described in the present disclosure and may be performed using other methods. For example, the notification of information may be performed by physical layer signaling (e.g., Downlink Control Information (DCI) and Uplink Control Information (UCI)), higher layer signaling (e.g., Radio Resource Control (RRC) signaling, Medium Access Control (MAC) signaling, broadcast information (Master Information Block (MIB) and System Information Block (SIB))), other signals, or a combination thereof. Furthermore, the RRC signaling may be referred to as an RRC message, and may be, for example, an RRC Connection Setup message, an RRC Connection Reconfiguration message, or the like.

[0055] Each aspect / embodiment described in the present disclosure may be implemented using any of the following standards: LTE (Long Term Evolution), LTE-Advanced (LTE-A), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), 5G (5th generation mobile communication system), 6th generation mobile communication system (6G), xth generation mobile communication system (xG) (xG (x is, for example, an integer or a decimal number)), FRA (Future Radio Access), NR (new Radio), New radio access (NX), Future generation radio access (FX), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.17 (WiMAX (registered trademark)), IEEE 802.19 (WiMAX (registered trademark)), IEEE 802.20 (WiMAX (registered trademark)), IEEE 802.21 (Wi-Fi (registered trademark)), IEEE 802.22 (WiMAX (registered trademark)), IEEE 802.23 (WiMAX (registered trademark)), IEEE 802.24 (WiMAX (registered trademark)), IEEE 802.25 (WiMAX (registered trademark)), IEEE 802.26 (WiMAX (registered trademark)), IEEE 802.27 (WiMAX (registered trademark)), IEEE 802.28 (WiMAX (registered trademark)), IEEE 802.29 (WiMAX (registered trademark)), IEEE 802.30 (WiMAX (registered trademark)), IEEE 802.31 (Wi-Fi (registered trademark)), IEEE 802.32 (WiMAX (registered trademark)), IEEE 802.33 (WiMAX (registered trademark)), IEEE 802.34 ( The present invention may be applied to at least one of systems using 802.20, Ultra-Wideband (UWB), Bluetooth, or other suitable systems, and next-generation systems that are extended, modified, created, or defined based on these systems. It may also be applied to a combination of multiple systems (e.g., a combination of LTE and / or LTE-A with 5G).

[0056] The order of the procedures, sequences, flowcharts, etc. of each aspect / embodiment described in this disclosure may be changed unless it is consistent. For example, the methods described in this disclosure present elements of various steps using an example order, and are not limited to the particular order presented.

[0057] Input and output information may be stored in a specific location (for example, memory) or may be managed using a management table. Input and output information may be overwritten, updated, or added to. Output information may be deleted. Input information may be sent to another device.

[0058] The determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a numerical comparison (e.g., comparison with a predetermined value).

[0059] The aspects / embodiments described in this disclosure may be used alone, in combination, or switched depending on the implementation. Notification of predetermined information (e.g., notification that "X is true") is not limited to explicit notification, but may be implicit (e.g., not notifying the predetermined information).

[0060] Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described herein. The present disclosure can be implemented in modified and altered forms without departing from the spirit and scope of the present disclosure as defined by the claims. Therefore, the description of the present disclosure is intended to be illustrative and does not have any limiting meaning on the present disclosure.

[0061] Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.

[0062] Software, instructions, information, etc. may also be transmitted or received over a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and / or wireless technologies (such as infrared, microwave), then these wired and / or wireless technologies are included within the definition of transmission media.

[0063] The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0064] Note that terms described in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings. For example, at least one of a channel and a symbol may be a signal (signaling). Furthermore, a signal may be a message. Furthermore, a component carrier (CC) may be called a carrier frequency, a cell, a frequency carrier, etc.

[0065] As used in this disclosure, the terms "system" and "network" are used interchangeably.

[0066] Furthermore, the information, parameters, etc. described in the present disclosure may be expressed using absolute values, may be expressed using relative values ​​from a predetermined value, or may be expressed using other corresponding information. For example, a radio resource may be indicated by an index.

[0067] The names used for the above-described parameters are not intended to be limiting in any way. Furthermore, the mathematical expressions using these parameters may differ from those explicitly disclosed in this disclosure. The various channels (e.g., PUCCH, PDCCH, etc.) and information elements may be identified by any suitable names, and therefore the various names assigned to these various channels and information elements are not intended to be limiting in any way.

[0068] As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (e.g., searching in a table, database, or other data structure), ascertaining, and the like. "Determining" and "determining" may also include receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), and the like. Furthermore, "judgment" and "decision" can include regarding resolving, selecting, choosing, establishing, comparing, etc. as having been "judged" or "decided." In other words, "judgment" and "decision" can include regarding some action as having been "judged" or "decided." Furthermore, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

[0069] As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

[0070] As used in this disclosure, any reference to an element using a designation such as "first," "second," etc. does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, a reference to a first and a second element does not imply that only two elements may be employed or that the first element must in some way precede the second element.

[0071] When the terms "include," "including," and variations thereof are used in this disclosure, these terms are intended to be inclusive, similar to the term "comprising." Furthermore, when the term "or" is used in this disclosure, it is not intended to be an exclusive or.

[0072] In this disclosure, where articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are in the plural form.

[0073] In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "coupled" may also be interpreted in the same way as "different."

[0074] 1...system, 10...information processing device, 11...reception unit, 12...determination unit, 13...output unit, 20A...external server, 20...reference DB, 30...LLM, 30A...external server, 1001...processor, 1002...memory, 1003...storage, 1004...communication device, 1005...input device, 1006...output device, 1007...bus.

Claims

1. An information processing device comprising: a reception unit that receives request information for generating recommendation information regarding furniture coordination in a room, the request information including user information including at least information regarding the room; a determination unit that determines an advice policy including at least a concept of the room based on the user information; and an output unit that outputs a prompt to instruct the generation of recommendation information regarding furniture coordination in the room based on the determined advice policy.

2. The information processing device described in claim 1, wherein the determination unit determines which of a plurality of personas, which have been pre-classified into a plurality of types according to preferences regarding furniture coordination, the user corresponds to based on at least one of the user's attribute information or the condition information regarding the coordination contained in the user information, and determines the advice policy including the room concept based on the preferences corresponding to the determined persona of the user.

3. The information processing device described in claim 1, wherein the user information includes preference degree information that indicates the degree of preference for each of a plurality of preferences held by the user, the determination unit determines the advice policy that includes the preference degree information, and the output unit outputs the prompt that includes an instruction to generate the recommendation information using the preference degree information included in the advice policy.

4. The information processing device described in claim 3, wherein the determination unit determines recommendation level information, which is information indicating the degree of recommendation for each of multiple types of furniture to be placed in the room, based on the preference level information, and determines the advice policy including the determined recommendation level information; and the output unit outputs the prompt including an instruction to generate the recommendation information for the multiple types of furniture using the recommendation level information included in the advice policy.

5. The information processing device according to claim 1, wherein the output unit receives and outputs the recommendation information as a generation result output from the generative AI model in response to input of the prompt.

6. An information processing method comprising: a step in which an information processing device receives request information for generating recommendation information regarding furniture coordination in a room, the request information including user information including at least information regarding the room; a step in which the information processing device determines an advice policy including at least a concept of the room based on the user information; and a step in which the information processing device outputs a prompt to instruct the generation of recommendation information regarding furniture coordination in the room based on the determined advice policy.