Information processing device and information processing method

Abstract

An information processing device (10) comprises: a reception unit (11) that receives portal site generation request information including at least information on a user; an acquisition unit (12) that acquires at least one piece of attribute information or at least one piece of preference information of the user on the basis of information on the user in response to the reception of the portal site generation request information; a determination unit (13) that determines information related to portal site construction for the user on the basis of at least one of the attribute information and the preference information; and an output unit (14) that outputs an input sentence to a prompt for instructing generation of a program language for constructing the portal site for the user on the basis of the information related to portal site construction for the user.

Description

Information processing device and information processing method

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

[0002] The site that a user first visits when accessing the Internet is called a "portal site." There are various types of portal sites, including search engine sites such as Google (registered trademark), portal sites specializing in posting reviews and reservations for food, beauty, travel, etc., and specialized portal sites with extensive content specialized in a particular theme. Thus, when a user wants to view or check specific information, portal sites function effectively to quickly access the site where that information is posted. Patent Document 1 (JP-A-2003-125566) proposes a technology related to such portal sites, which allows users to create a portal site layout that reflects the regional characteristics of a country and the preferences of the general public.

[0003] JP 2013-033320 A

[0004] However, the information that users want to access varies depending on the attributes, preferences, etc. of each individual user, and therefore it is desired to configure the layout of a portal site appropriately according to the attributes, preferences, etc. of each individual user.

[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, in response to input of various pieces of generation request information, generates a generation result (content) in accordance with the instructions, context, questions, and output format indicated in the generation request information, and returns the generation result as response information.

[0006] Taking the above circumstances into consideration, the present disclosure aims to effectively utilize a generative AI model to appropriately configure the layout of a portal site according to user attributes, preferences, etc.

[0007] The information processing device according to the present disclosure includes a reception unit that receives portal site generation request information including at least information about a user; an acquisition unit that acquires at least one piece of attribute information or at least one piece of preference information of the user based on the information about the user in response to the reception of the portal site generation request information; a determination unit that determines information regarding construction of a portal site for the user based on at least one of the attribute information or the preference information; and an output unit that outputs an input sentence to a prompt to instruct the generation of a programming language for constructing a portal site for the user based on the information about construction of the portal site for the user.

[0008] According to the present disclosure, by effectively utilizing a generative AI model, it is possible to appropriately configure the layout of a portal site according to user attributes, preferences, etc.

[0009] It is a block diagram of the entire system including the information processing device. It is a flow diagram of processing executed by the information processing device. (a) is a block diagram showing a first modification regarding the system configuration, and (b) is a block diagram showing a second modification regarding the system configuration. It is a block diagram showing an example of the hardware configuration of 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] FIG. 1 illustrates a configuration diagram of a system 1 including an information processing device 10 according to the present disclosure. As illustrated in FIG. 1 , the system 1 includes a terminal 20 operated by a user, an external server (hereinafter referred to as "LLM" for ease of explanation) 30 running a large-scale language model (LLM), and the information processing device 10. The information processing device 10 is a device constituting a Retrieval-Augmented Generation (RAG) system. The RAG system is a type of prompt extension technology used for, for example, corporate information linkage between LLMs. Specifically, when issuing a generation request to an LLM based on an instruction statement (generation request information), the system searches for similar documents, etc. in a search system in advance, and outputs the obtained similar documents, etc., along with the instruction statement (input text for the prompt) to the LLM to request generation. The present disclosure corresponds to an invention for extending and improving the functions of the RAG system, and has an aspect of enriching and optimizing the instruction statement (input text for the prompt) for the LLM 30.

[0012] The above-mentioned prompt refers to information indicating an instruction or question input to a generative AI model (LLM30 in this embodiment) in an interactive system such as a dialogue with the generative AI model or a command line interface (CLI), and corresponds to an "input sentence" input to the generative AI model. The prompt input to the LLM30 in this embodiment is text data including, for example, instructions to be executed by the LLM30, tasks to be executed by the LLM30, background / context to be considered by the LLM30 (e.g., roles, conditions), questions to be answered by the LLM30, and information indicating the output format of response information from the LLM30. Furthermore, input information to be used as the target of instructions / tasks to be executed by the LLM30 may be added to the prompt. 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.

[0013] In order to realize the functions according to the present disclosure, the information processing device 10 includes a reception unit 11, an acquisition unit 12, a determination unit 13, and an output unit 14. The function of each unit will be described below.

[0014] The reception unit 11 is a functional unit that receives portal site construction request information from the terminal 20 or an external server (not shown). The portal site construction request information is information requesting the generation of a programming language for constructing a portal site for a certain service (e.g., a search service, an information distribution service, an AI service, etc.). For example, a predetermined button (e.g., a "portal site construction request button") may be prepared, and the portal site construction request information may be generated when the button is pressed. For example, this request information may include information regarding the certain service (e.g., a search service, an information distribution service, an AI service, etc.) (e.g., information specifying the service), information specifying the type of programming language, information specifying the hardware, OS, middleware, etc. on which the programming language is implemented, or other information regarding the requirements of the portal site (e.g., the number of accesses, etc.). The portal site construction request information may also include information regarding the user. The information regarding the user is information regarding the user browsing the portal site, and may correspond to, for example, any of the user's identification information, the user's name, the user's attribute information, and the user's preference information.

[0015] Examples of the above-mentioned user attribute information include information that comprehensively includes personal information, the surrounding environment, and behavioral tendencies, such as "age," "gender," "area of ​​residence," "household (whether or not the user has a spouse or children, or the generation of those children)," and "behavioral history, such as past site browsing, video viewing, and purchase history." Furthermore, impressions of previously created portal sites (history information, such as which links and panels were selected) may be added to the attribute information, which can be very useful in generating a portal site layout that is likely to interest the user.

[0016] The user preference information is information about the user's preference for portal sites. Examples of user preference information include information indicating a portal site that the user likes, and information about the layout of a portal site that the user likes (for example, portal site layouts may be presented to the user and information indicating the layout selected by the user, information indicating the amount of information, or information about the order of content). Note that this preference information may be information obtained from internet browsing history or application operation history, or may be information processed from such information (for example, generated using AI technology, etc.).

[0017] This information (attribute information, preference information) may be recorded in association with each user's identification information so that information matching the user's identification information can be extracted in response to an inquiry from the system, or may be extracted using a learning model. Furthermore, preference information may be extracted based on attribute information, as described below. In this way, the attribute information and preference information may be included in the portal site construction request information, or may be information obtained independently of the portal site construction request information.

[0018] The user preference information may include information indicating the degree of preference. Furthermore, the information indicating the degree of preference may be output using AI technology that uses a learning model that has learned the user and the user's preference information. For example, in a learning model that has learned the relationship (relationship between each feature) between the user's preference information and the user (or the user's attribute information) in a neural network (NN), information indicating the degree of preference (score) may be output based on the distance between a node corresponding to the feature of the user's preference information and a node corresponding to the feature of the user's attribute information.

[0019] The storage of preference information is illustrated below. The storage format is as follows, with "user identification information," "information indicating the user's favorite portal site," and "information indicating the level of preference (score)" being stored as one record: (Data Example 1) XXXX12, Site A, 72% (Data Example 2) XXXX12, Site B, 22% (Data Example 3) XXXX12, Site C, 6% The above storage format is just one example. In addition to the above example, for example, instead of user identification information, information indicating the favorite portal site and information indicating the level of preference (score) may be stored in association with at least one attribute information of the user. However, storing the data as in the above example is useful for searching which users have what preferences (portal site preferences) and to what extent. By generating a prompt that inputs this information, information regarding the user's preferences and the extent to which they exist can be passed to the LLM30 (AI model), and the LLM30 generates content (programming language) based on the information regarding the user's preferences and the extent to which they exist, allowing the user to obtain content from the LLM30 that feels as if it were created by a human.

[0020] The acquisition unit 12 is a functional unit that acquires at least one piece of attribute information or at least one piece of preference information of a user based on the information about the user in response to receiving the portal site generation request information. The determination unit 13 is a functional unit that determines information regarding the construction of a portal site for the user based on at least one of the acquired attribute information or preference information. The acquisition unit 12 and the determination unit 13 operate in close cooperation with each other. For example, (1) the acquisition unit 12 may extract the user's preference information from the user's attribute information, and the determination unit 13 may determine information regarding the construction of a portal site for the user based on the extracted preference information. (2) The determination unit 13 may determine information regarding the construction of a portal site for the user based on the attribute information passed from the acquisition unit 12. Alternatively, (3) the acquisition unit 12 may acquire both the user's attribute information and preference information, and the determination unit 13 may determine information regarding the construction of a portal site for the user based on a combination of the attribute information and the preference information. For example, information regarding the construction of a portal site for users may be information regarding the type of content to be posted on the portal site (image files, video files, text, links, search windows, etc.), size, layout (location, design, composition) and / or quantity (for example, information specifying the number of contents, information specifying the degree of content to be displayed on the portal site (large / normal / small), appearance of the amount of content to be displayed on the portal site (detailed / normal / simple)).

[0021] Regarding the extraction of preference information in the above case (1), the acquisition unit 12 may use a learning model that has previously learned the relationship between feature amounts of attribute information and preference information through machine learning, and acquire the user's preference information as an output result from the learning model in response to input of the user's attribute information into the learning model. In this case, appropriate preference information can be acquired using the learning model. As an alternative, the acquisition unit 12 may extract preference information associated with the attribute information from the user's attribute information by referencing a table that previously associates attribute information with preference information. In this case, appropriate preference information can be acquired using the table. Furthermore, the acquisition unit 12 may extract the user's preference information based on at least one of "application usage history information" and "POI (Point of Interest) retention information" included in the user's attribute information. As a specific example, the acquisition unit 12 may determine a selection menu (e.g., a pull-down menu that allows easy selection of favorite applications, favorite POIs, etc.) to be posted on the portal site as "information related to portal site construction" based on the extracted preference information. In this case, the user can select a preferred application, a preferred POI, etc. with a simple operation.

[0022] The output unit 14 is a functional unit that outputs to the LLM 30 an input sentence (instruction statement) to a prompt for instructing the generation of a programming language for constructing a portal site for a user based on information related to the construction of a portal site for a user. Furthermore, in response to the input of the instruction statement to the LLM 30, the output unit 14 receives from the LLM 30 the programming language for constructing the portal site for a user as a generation result output from the LLM 30, and outputs the programming language to the terminal 20.

[0023] The process executed in the information processing device 10 (the process related to the information processing method of the present disclosure) will be described below with reference to the flow diagram of Fig. 2. Fig. 2 illustrates, as an example, a process in which the acquisition unit 12 extracts user preference information from attribute information, and the determination unit 13 determines information related to building a portal site for the user based on the extracted preference information.

[0024] First, the receiving unit 11 receives user attribute information from the terminal 20 or an external server (not shown) (step S1), and the acquiring unit 12 acquires the user attribute information or preference information (step S2). In step S2, as described above, the acquiring unit 12 may use a learning model that has previously learned the relationship between the feature amounts of the attribute information and the preference information through machine learning, and acquire the user preference information as an output result from the learning model in response to input of the user attribute information into the learning model, or may acquire the user preference information by referring to a table in which attribute information and preference information are previously associated with each other.

[0025] Next, the determination unit 13 determines information regarding the construction of a portal site for the user based on at least one of the acquired attribute information and preference information (step S3). For example, as preference information, for a user who likes news, information is determined to make the display panel for news information larger in size so that news information is more easily conveyed. Furthermore, for a user who likes watching videos, information is determined to provide a video introduction panel for genres that the user is likely to be interested in based on past viewing trends. Furthermore, for a user who likes shopping, information is determined to provide a panel introducing multiple products that are likely to interest the user based on past search history, browsing history, purchase history, etc. Furthermore, as a variation of information regarding the construction of a portal site for the user, past revision history information in which "layout information before revision" and "layout information after revision" are previously associated for each preference information can be used. In this case, very useful information (past revision history information) can be input into the prompt of the LLM 30 as reference information.

[0026] Next, the output unit 14 outputs an input sentence (instruction sentence) to a prompt to instruct the generation of a programming language for constructing a portal site for users based on the determined information (information regarding the construction of a portal site for users) (i.e., instructs the LLM 30 to generate it) (step S4).

[0027] Thereafter, if the LLM 30 responds with the generation result (a programming language for building a portal site for users) (YES in step S5), the output unit 14 acquires the generation result from the LLM 30 and outputs the acquired generation result to the terminal 20 (step S6).

[0028] According to the embodiment described above, terminal 20 can execute a programming language for constructing a portal site for users, thereby effectively utilizing LLM 30 to display a portal site with a layout that is appropriately personalized according to the attribute information and preference information of the user of terminal 20, and can quickly access various sites that contain information of interest to the user.

[0029] Below are examples (both excerpts) of (a) HTML (HyperText Markup Language: a programming language for arranging text, images, etc. required for a website) and (b) CSS (Cascading Style Sheets: a programming language for adjusting the appearance (colors, fonts, etc.) of a web page) as examples of the generated results (programming languages ​​for building a portal site) output from LLM 30. Note that the language type may also be a programming language other than HTML or CSS.

[0030] (a) HTML example<!doctype html> <html　lang="ja"> 　 <meta　charset="utf-8"> 　 <title>Sample< / title> 　 <link　rel="stylesheet"　href="style.css"> 　… 　 <div　class="header">MY Portal Site <div　class="main"> <h1> what's new< / h1> … …

[0031] (b) CSS example (file name: style.css) .header { position: fixed; top: 0; width: 100%; height: 50px; background-color: darkgrey;} .main { padding-top: 50px; overflow: auto;} …

[0032] (Variations of System 1) System 1 is not limited to the configuration shown in FIG. 1 . As shown in FIG. 3A, the information processing device 10 may be included in the terminal 20. This configuration can be realized, for example, by installing an application that executes the functions of the information processing device 10 on the terminal 20. The LLM 30 resides externally (e.g., on the cloud). Alternatively, as shown in FIG. 3B, the information processing device 10 and the LLM 30 may be included in the terminal 20. This configuration can be realized, for example, by installing an application that executes the functions of the information processing device 10 and an application that executes the functions of the LLM 30 on the terminal 20. In any of the configurations shown in FIGS. 1, 3A, and 3B, an external server (e.g., an internal server of a company) that can provide documents related to user tasks, educational material information, and the like resides externally (e.g., on a network).

[0033] The gist of the present disclosure lies in the following [1] to [6]. [1] An information processing device comprising: a receiving unit that receives portal site generation request information including at least information about a user; an acquisition unit that acquires at least one piece of attribute information or at least one piece of preference information of the user based on the information about the user in response to the reception of the portal site generation request information; a determination unit that determines information related to construction of a portal site for the user based on at least one of the attribute information or the preference information; and an output unit that outputs an input sentence in response to a prompt for instructing generation of a programming language for constructing a portal site for the user based on the information about the construction of the portal site for the user. [2] The information processing device described in [1], wherein the acquisition unit acquires a degree of preference for each of a plurality of pieces of preference information of the user using a learning model that has learned the relationship between feature amounts of the attribute information and feature amounts of the preference information, and the output unit outputs the input sentence including a request to generate the programming language using the plurality of piece of preference information of the user and the degree of preference for each piece of preference information. [3] The information processing device according to [1] or [2], wherein the acquisition unit extracts the user's preference information based on at least one of application usage history information and POI (Point of Interest) stay information included in the user's attribute information, and the determination unit determines a selection menu to be posted on the portal site as information related to the portal site construction based on the extracted preference information. [4] The information processing device according to any one of [1] to [3], wherein the output unit includes, in the generation request information, revision history information that associates pre-revision layout information with post-revision layout information for each of the preference information. [5] The information processing device according to any one of [1] to [4], wherein the output unit receives and outputs a programming language for constructing a portal site for the user as a generation result output from a generation AI model in response to input of the generation request information.[6] An information processing method comprising: a step in which an information processing device receives portal site generation request information including at least information about a user; a step in which the information processing device, in response to receiving the portal site generation request information, acquires at least one piece of attribute information or at least one piece of preference information of the user based on the information about the user; a step in which the information processing device determines information related to building a portal site for the user based on the attribute information or at least one piece of attribute information; and a step in which the information processing device outputs an input sentence to a prompt for instructing the generation of a programming language for building a portal site for the user based on the information related to building the portal site for the user.

[0034] [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.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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).

[0044] 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).

[0045] 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.

[0046] 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.

[0047] 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.

[0048] 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, UWB (Ultra-Wide Band), Bluetooth (registered trademark), or other suitable systems, and next-generation systems that are extended, modified, created, or defined based on these systems. The present invention may also be applied to a combination of multiple systems (e.g., a combination of LTE and / or LTE-A with 5G).

[0049] 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.

[0050] 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 transmitted to another device.

[0051] 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).

[0052] 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).

[0053] 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.

[0054] 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.

[0055] 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.

[0056] 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.

[0057] 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.

[0058] As used in this disclosure, the terms "system" and "network" are used interchangeably.

[0059] 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.

[0060] 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.

[0061] 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.

[0062] 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."

[0063] 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.

[0064] 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.

[0065] 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.

[0066] 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."

[0067] 1...system, 10...information processing device, 11...reception unit, 12...acquisition unit, 13...decision unit, 14...output unit, 20...terminal, 30...LLM (generative AI model), 1001...processor, 1002...memory, 1003...storage, 1004...communication device, 1005...input device, 1006...output device, 1007...bus. < / link　rel="stylesheet"　href="style.css"> < / meta　charset="utf-8"> < / html　lang="ja">

Claims

1. An information processing device comprising: a reception unit that receives portal site generation request information including at least information about a user; an acquisition unit that acquires at least one attribute information or at least one preference information of the user based on the information about the user in response to the reception of the portal site generation request information; a determination unit that determines information related to the construction of a portal site for the user based on at least one of the attribute information or the preference information; and an output unit that outputs an input sentence to a prompt to instruct the generation of a programming language for constructing a portal site for the user based on the information about the construction of the portal site for the user.

2. The information processing device described in claim 1, wherein the acquisition unit acquires the degree of preference for each of the user's multiple pieces of preference information using a learning model that has learned the relationship between the features of the attribute information and the features of the preference information, and the output unit outputs the input sentence including an instruction to generate the programming language using the user's multiple pieces of preference information and the degree of preference for each piece of preference information.

3. The information processing device described in claim 1, wherein the acquisition unit extracts the user's preference information based on at least one of application usage history information and POI (Point of Interest) stay information contained in the user's attribute information, and the determination unit determines a selection menu to be posted on the portal site based on the extracted preference information as information regarding the construction of the portal site.

4. The information processing device according to claim 1, wherein the output unit includes, in the generation request information, revision history information that associates layout information before revision with layout information after revision for each of the preference information.

5. The information processing device according to claim 1, wherein the output unit receives and outputs a programming language for constructing a portal site for the user as a generation result output from the generation AI model in response to input of the generation request information.

6. An information processing method comprising: a step in which an information processing device receives portal site generation request information including at least information about a user; a step in which the information processing device, in response to receiving the portal site generation request information, acquires at least one piece of attribute information or at least one piece of preference information of the user based on the information about the user; a step in which the information processing device determines information related to the construction of a portal site for the user based on the attribute information or at least one piece of attribute information; and a step in which the information processing device outputs an input sentence to a prompt for instructing the generation of a programming language for constructing a portal site for the user based on the information related to the construction of the portal site for the user.

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