Information processing device and information processing method

Abstract

This invention provides a technology that utilizes large-scale language models to more effectively prioritize users' schedules. [Solution] An information processing device according to one embodiment includes a reception unit that receives input of multiple schedules relating to a user, an acquisition unit that acquires behavioral information relating to the user's past actions, a priority request unit that requests a large-scale language model to assign a priority to each of the multiple schedules using the behavioral information, and an output unit that outputs schedule data relating to the multiple schedules to which the large-scale language model has assigned a priority in response to the request.

Description

【Technical Field】 【0001】 The present invention relates to a technology for assisting user task management. 【Background Art】 【0002】 Technologies for managing user schedules are known. For example, Patent Document 1 discloses an invention that decomposes various tasks into subtasks and assigns tasks to the user's schedule according to priorities according to importance in order to manage personal schedules. Patent Document 2 discloses an invention that identifies the location where a target schedule is to be performed from past action results and notifies the user of the schedule for the user's schedule. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2006-146530 【Patent Document 2】 Japanese Patent Application Laid-Open No. 2020-061100 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 The invention described in Patent Document 1 merely uses priorities to simply assign tasks to a schedule or decomposes tasks into subtasks using existing technologies. The invention described in Patent Document 2 was not capable of effectively proposing the execution of tasks according to the user's situation. 【0005】 In contrast, the present invention provides a technology that utilizes a large language model to more effectively assign priorities to the user's schedule. 【Means for Solving the Problems】 【0006】 An information processing device according to one aspect of the present disclosure includes: a receiving unit that receives input of multiple schedules relating to a user; an acquisition unit that acquires behavioral information relating to the user's past actions; a priority request unit that requests a large-scale language model to assign a priority to each of the multiple schedules using the behavioral information; and an output unit that outputs schedule data relating to the multiple schedules to which the large-scale language model has assigned a priority in response to the request. 【0007】 An information processing method according to another aspect of the present disclosure includes the steps of: a computer receiving input of a plurality of appointments relating to a user; acquiring behavioral information relating to the user's past actions; requesting a large language model to assign a priority to each of the plurality of appointments using the behavioral information; and outputting appointment data relating to the plurality of appointments to which the large language model has assigned a priority in response to the request. [Effects of the Invention] 【0008】 According to the present invention, it is possible to utilize a large-scale language model to more effectively prioritize users' schedules. [Brief explanation of the drawing] 【0009】 [Figure 1] A diagram illustrating the system configuration of an information processing system 1 according to one embodiment. [Figure 2] A diagram illustrating the functional configuration of information processing system 1. [Figure 3] A diagram illustrating the hardware configuration of the information processing device 10. [Figure 4] A sequence chart illustrating the operation method of the task management assistant in Information Processing System 1. [Figure 5] A diagram illustrating prompts related to priority requests. [Figure 6] A diagram illustrating user schedule database 1000. [Figure 7] A diagram illustrating prompts for decomposition requests and the results generated by LLM90. [Figure 8] A diagram illustrating Task Database 2000. [Figure 9] A diagram illustrating prompts related to the Request for Proposals and the results generated by LLM90. [Modes for carrying out the invention] 【0010】 1. Structure Figure 1 is a diagram illustrating the system configuration of an information processing system 1 according to one embodiment. In this example, the information processing system 1 (or simply referred to as the system) is a system relating to a service for efficiently managing a user's schedule and tasks (hereinafter referred to as the "task management assistant"). A dedicated application that provides the task management assistant easily obtains the user's schedule via a terminal or the like and effectively manages various tasks associated with the schedule. In this example, "schedule" refers to an action to be performed by the user among the information related to the user's schedule, and "task" refers to the work required to achieve the schedule as defined for each schedule. In this invention, these terms are distinguished from each other. A schedule includes one or more tasks. 【0011】 Existing services such as calendars, scheduling apps, and task management functions, which are widely used, have pursued more convenient features in response to user demands and technological advancements. On the other hand, with the recent rapid development of the field of generative AI, many challenges remain in realizing more efficient task management services by introducing such AI technology. In particular, there is room for development in introducing task management technology based on language processing functions using large language models (LLMs). 【0012】 Conventional related technologies require users to manually set priorities representing the priority of their appointments, which is time-consuming and laborious. Furthermore, they cannot flexibly adapt to the user's situation. In this case, there is a need for the system to consider the individual user's state or situation and automatically assign more appropriate priorities. However, there are limitations to a uniform system constantly and accurately recognizing the user's state and responding flexibly. Therefore, the present invention provides a technology that utilizes a large-scale language model to more effectively assign priorities to a user's appointments. 【0013】 Information processing system 1 comprises an information processing device 10, a user terminal 20, a learning support means 30, and an LLM 90. In this example, each component of the system is connected to one another via a network 9. In this example, network 9 is a computer network such as the Internet or a mobile network. 【0014】 The information processing device 10 is an information processing device or server device in the information processing system 1. In this example, the information processing device 10 provides various functions related to a task management assistant. The information processing device 10 can work in conjunction with the LLM 90 to provide functions such as setting priorities for appointments, breaking down appointments into multiple tasks (referred to here as "task decomposition"), and making suggestions regarding task execution. The information processing device 10 works in conjunction with the learning support means 30 to execute requests to the LLM 90 according to the user's past behavior history or the user's real-time situation. As a result, the information processing device 10 supports the execution of appointments by having the LLM analyze the user's past behavior history or real-time situation and autonomously suggest tasks to the user. 【0015】 The user terminal 20 is a terminal possessed and used by a user who utilizes the information processing system 1. The user terminal 20 includes, for example, a smartphone, a tablet, or a personal computer. In this example, the user terminal 20 has previously installed an application related to the service provided by the present invention (hereinafter simply referred to as "this application"). The user can utilize various functions related to the task management assistant via this application. The user terminal 20 can receive an input of a schedule from the user and output data related to the schedule to the information processing device 10. The user terminal 20 can record and hold data related to the user's schedule or actions and share the data with the information processing device 10 or the learning assistance means 30. 【0016】 The learning assistance means 30 is a functional means that provides the personal data of the user in response to a request to the LLM 90 in the information processing system 1. The learning assistance means 30 is a device, computer, machine, or software that can cooperate with the information processing device 10. In this example, the learning assistance means 30 can record contract information, location information, and settlement information in the database by cooperating with various services via the user terminal 20. In this example, the contract information is the basic personal information of the user obtained according to the contract status of the user related to the communication service. The location information is information indicating the terminal location or its history of the user terminal 20 specified using a communication infrastructure such as a base station network. The settlement information is information related to the history of transactions or settlements such as online shopping executed using the user terminal 20. 【0017】 The LLM 90 is a generative AI including an LLM. In this example, the LLM 90 has various functions related to, for example, language processing ability using natural language, analysis ability, and a huge database. The LLM 90 can generate various data in response to requests for each function provided by the information processing device 10. The cooperation with the LLM 90 is usually performed based on information processing via an instruction sentence usually called a "prompt". The LLM 90 outputs the generated data to the information processing device 10 via the network 9. 【0018】 FIG. 2 is a diagram illustrating the functional configuration of the information processing system 1. In this embodiment, the information processing apparatus 10 includes functional blocks (or components) such as a reception unit 11, an acquisition unit 12, a priority request unit 13, a decomposition request unit 14, a proposal request unit 15, an output unit 181, a proposal unit 182, a registration unit 183, a notification unit 184, a storage unit 191, and a control unit 192. In this example, the storage unit 191 stores various data, programs, and software including, for example, a database. In this example, the control unit 192 performs various controls. 【0019】 The reception unit 11 receives inputs of a plurality of schedules related to the user. The input of the schedule is performed via the user terminal 20. In this example, the user can input the schedule in various ways using the functions implemented in the user terminal 20. This includes, for example, methods such as acquiring schedule data input into a calendar application, uploading an image of a document (including, for example, a memo) in which the details of the schedule are described, or directly manually inputting the schedule data. The reception unit 11 acquires the user's schedule via the application installed on the user terminal 20. 【0020】 The acquisition unit 12 acquires behavior information related to the user's past behavior. In this example, the behavior information is various information related to the user's behavior acquired via the user terminal 20 and is recorded for each user in a database managed by the information processing apparatus 10 or the learning assistance means 30. The behavior information includes, for example, a history of location information of places the user has visited in the past. In addition, the behavior information includes message information such as the user's SNS posts or settlement information such as a payment history. The learning assistance means 30 manages the user's personal information, location information, or settlement information in a database. The acquisition unit 12 can acquire this information by requesting the learning assistance means 30. 【0021】 Of the functional units controlled by the information processing device 10, the priority request unit 13, the decomposition request unit 14, and the proposal request unit 15 are connected to the LLM 90 and make various requests. The interaction with the LLM 90 is performed by an application program that implements the so-called RAG (Retrieval-Augmented Generation) function. Therefore, requests to the LLM 90 are executed via prompts automatically generated by the information processing device 10. 【0022】 The priority request unit 13 requests the LLM 90 to assign a priority to each of the multiple appointments using behavioral information. In this example, priority is an indicator of appointment priority tailored to each user, and is comprehensively evaluated based on, for example, the user's past behavior and trends, the user's personal living environment, or lifestyle. Priority may include, for example, a three-level evaluation such as low, medium, and high, a score defined within a specific numerical range, or points according to various perspectives. The priority request unit 13 works in cooperation with the LLM 90 to obtain the priority for each appointment. 【0023】 For example, if a user's schedule prioritizes aspects related to their family situation, the priority request unit 13 can request that priorities be assigned to multiple schedules based on information about the user's family structure. Additionally, if each of the multiple schedules includes information specifying the time and location, the priority request unit 13 can request that priorities be assigned considering the travel time between each schedule. The content of the request from the priority request unit 13 is determined more effectively depending on the user's state or actions. 【0024】 The decomposition request unit 14 requests the LLM 90 to decompose the schedule into multiple tasks. For example, in relation to cooperation with the priority request unit 13, if the reception unit 11 receives input of multiple schedules, the decomposition request unit 14 requests that the schedules whose assigned priorities meet the conditions be decomposed into multiple tasks. In this example, the conditions set for priority include conditions for specifying a particular priority from a three-level evaluation of low, medium, and high. The decomposition request unit 14 can also request that the schedule be decomposed into multiple tasks using information about the user's family structure. 【0025】 Requests from the decomposition request unit 14 are executed via prompts automatically generated by the RAG described above. In this example, the request includes information specifying the number of tasks to be decomposed. Alternatively, the request includes information specifying the order in which multiple tasks will be output. The content of the request is determined appropriately through cooperation between the decomposition request unit 14 and the RAG. 【0026】 The suggestion request unit 15 requests the LLM 90 to suggest which of several tasks the user should perform, according to the given situation. In this example, the tasks the user should perform may change depending on the given situation. Therefore, the suggestion request unit 15 and the LLM 90 can cooperate with each other to control a series of processes related to task suggestions. 【0027】 The following describes some typical processes that the suggestion request unit 15 performs depending on the given situation. The suggestion request unit 15 requests suggestions using information about the user's family structure. The suggestion request unit 15 requests suggestions using behavioral information that shows actions the user has taken in the past. The suggestion request unit 15 requests suggestions using location information that shows the user's current location. The suggestion request unit 15 requests suggestions including the timing of notifying the user of the suggestions. The suggestion request unit 15 requests suggestions including websites related to the suggestions. The detailed functions of the suggestion request unit 15 will be described later. 【0028】 The output unit 181 outputs schedule data for multiple appointments that have been assigned priorities by the LLM 90 upon request. In this example, the information processing device 10 records the prioritized schedule data in a database. Alternatively, the information processing device 10 transmits this schedule data to the display screen of the user terminal 20. The user on the user terminal 20 can perform editing operations to change or modify the priority of the schedule data. In this example, the acquisition unit 12 receives editing instructions for prioritized appointments from the user via the user terminal 20. 【0029】 In addition, the output unit 181 outputs schedule data that includes information indicating multiple tasks generated by the LLM 90 in response to a request. This is made possible by the cooperation between the output unit 181 and the decomposition request unit 14. 【0030】 The suggestion unit 182 proposes tasks that the user should perform from among multiple tasks based on the schedule data. In this example, the suggestion unit 182 works in cooperation with the decomposition request unit 14 and the suggestion request unit 15 to effectively propose tasks from among multiple tasks that have been decomposed for each schedule, according to the user's situation. Furthermore, the results of the task proposal to the user (including feedback) are appropriately recorded in the database of the information processing device 10 and stored for each user. For example, the action information may include information that identifies the tasks that the user has completed from among the proposed tasks. 【0031】 The registration unit 183 registers the results of each of the multiple tasks performed by the user in the database. Alternatively, the registration unit 183 registers the results of the tasks performed by the user in the database. As a result, the database accumulates results related to the user's past actions and results related to suggestions from the information processing system 1. 【0032】 The notification unit 184 notifies the user of the proposal generated by the LLM 90 in response to a request from the proposal unit 182. The notification to the user is performed based on the context of the user's actions. In this example, the acquisition unit 12 acquires the context of the user's actions, which triggers the processing by the notification unit 184. Furthermore, the notification unit 184 notifies the user of the proposal when the context satisfies certain conditions. The conditions related to the context are predefined in the information processing system 1. 【0033】 Figure 3 illustrates the hardware configuration of the information processing device 10. Physically, the information processing device 10 is configured as a computer including a processor 101, memory 102, storage 103, communication device 104, input device (optional), display device (optional), and a bus connecting these. Each of these devices operates on power supplied from a battery (not shown). In the following description, the term "device" can be read as a circuit, device, unit, etc. The hardware configuration of the information processing device 10 may include one or more of the devices shown in Figure 3, or it may be configured without some of the devices. Alternatively, multiple devices with different enclosures may be connected via communication to constitute the information processing device 10. 【0034】 Each function in the information processing device 10 is realized by loading predetermined software (programs) onto hardware such as the processor 101 and memory 102, which allows the processor 101 to perform calculations, control communication by the communication device 104, and control at least one of the reading and writing of data in the memory 102 and storage 103. 【0035】 The processor 101 controls the entire computer, for example, by running the operating system. The processor 101 may consist of a central processing unit (CPU) that includes interfaces with peripheral devices, control units, arithmetic units, registers, etc. Alternatively, a baseband signal processing unit or a call processing unit may be implemented by the processor 101. 【0036】 The processor 101 reads programs (program code), software modules, data, etc., from at least one of the storage 103 and the communication device 104 into the memory 102 and executes various processes accordingly. The program used is one that causes the computer to execute at least a part of the operations described later. The functional blocks of the information processing device 10 are stored in the memory 102 and may be realized by control programs that run on the processor 101. Various processes may be executed by one processor 101, or they may be executed simultaneously or sequentially by two or more processors 101. The processor 101 may be implemented by one or more chips. The program may also be transmitted to the information processing device 10 via a telecommunications line. 【0037】 Memory 102 is a computer-readable recording medium and may consist of at least one of the following: ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), RAM (Random Access Memory), etc. Memory 102 may also be called a register, cache, main memory, etc. Memory 102 can store executable programs (program code), software modules, etc., for carrying out the method according to this embodiment. 【0038】 The storage 103 is a computer-readable recording medium and may consist of at least one of the following: an optical disc such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disc, a digital multipurpose disc, a Blu-ray® disc), a smart card, flash memory (e.g., a card, a stick, a key drive), a floppy® disk, a magnetic strip, etc. The storage 103 may also be called an auxiliary storage device. 【0039】 The communication device 104 is hardware (transceiver / receiver device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as a network device, network controller, network card, communication module, etc. 【0040】 Each device, such as the processor 101 and memory 102, is connected by a bus for communicating information. The bus may be configured using a single bus, or different buses may be used for each device. 【0041】 The information processing device 10 may include hardware such as a microprocessor, a digital signal processor (DSP), an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), or an FPGA (Field Programmable Gate Array), and some or all of the functional blocks may be implemented by such hardware. For example, the processor 101 may be implemented using at least one of these hardware components. 【0042】 In this example, the program stored in storage 103 includes a program (hereinafter referred to as the "server program") that causes the computer to function as a server in the information processing system 1. When the processor 101 is executing the server program, the processor 101, memory 102, storage 103, and communication device 104 are examples of functional blocks for operating the information processing device 10. The processor 101 is an example of a priority request unit 13, a decomposition request unit 14, a proposal request unit 15, a registration unit 183, and a control unit 192. At least one of the memory 102 and storage 103 is an example of a storage unit 191. The communication device 104 is an example of a reception unit 11, an acquisition unit 12, an output unit 181, a proposal unit 182, and a notification unit 184. 【0043】 While a detailed explanation will be omitted, the user terminal 20 is a computer having a processor, memory, storage, communication device, input device, and output device; specifically, it is, for example, a smartphone, tablet terminal, or personal computer. In this example, the program stored in the storage of the user terminal 20 includes a program that causes the computer to function as a client in the information processing system 1 (hereinafter referred to as the "client program"). The configuration of the information processing system 1 has now been described. Next, the operation of the information processing system 1 will be described. 【0044】 2. Operation Figure 4 is a sequence chart illustrating the operation method of the task management assistant in the information processing system 1. In this example, the functions provided by the task management assistant are provided as a function of this application (an example of a client program) that is pre-installed on the user terminal 20. Hereafter, actions related to a specific event concerning the information processing system 1 will be referred to as "event E," and processes executed by entities belonging to the information processing system 1 will be referred to as "step S." 【0045】 The following process begins when the information processing device 10 receives schedule input from the user. In this example, the information processing device 10 receives schedule data input from a user terminal 20 (not shown). For example, the user can use the camera installed in the user terminal 20 to take a picture of a document containing the schedule and input (i.e., upload) the image data related to the schedule to the information processing device 10. The document may include, for example, a printout listing schedules for school events such as parent-teacher meetings for the user's child. The user may also upload data for multiple schedules at once. 【0046】 In step S101, the information processing device 10 outputs a request to extract schedule data to the LLM 90. In this example, the information processing device 10 generates a prompt to output the above request to the LLM 90 according to the form of the schedule input received from the user terminal 20. This prompt includes, for example, a request or instruction expressed in text and schedule data obtained from the user terminal 20. For example, if image data of a document is obtained from the user terminal 20, the information processing device 10 can attach the image data to the generated prompt. The extraction request input to the LLM 90 includes this prompt. 【0047】 The LLM90 extracts various schedule data based on the input prompt. In this example, the extraction of schedule data may be performed in combination with mechanical processing such as the results of OCR (Optical Character Reader) processing of image data or the extraction of text information from email distribution. 【0048】 In step S102, the information processing device 10 retrieves schedule data from the LLM 90. In this example, the information processing device 10 can record the schedule data retrieved from the LLM 90 in the database. Here, the following processing describes the operation when performed on the extracted schedule. 【0049】 The information processing device 10 detects event E1 as a priority setting trigger. Event E1 is predefined and may include, for example, the user terminal 20 being in a specific location, a specific application being launched, or a set time arriving. In this example, "trigger" refers to an event that triggers an entity related to the information processing system 1 to perform a specific process. Priority setting triggers are pre-recorded in the database of the information processing device 10 according to the content of event E1. For example, the information processing device 10 can cooperate with a user terminal 20 (not shown) to acquire information about the user's real-time behavior and family structure, and input it into the LLM 90. Subsequent processing is initiated when the information processing device 10 detects event E1 as a priority setting trigger. 【0050】 In step S103, the information processing device 10 requests the LLM 90 to assign a priority to each of the extracted schedule data (hereinafter referred to as the "priority request"). In this example, the priority request includes a prompt automatically generated by the information processing device 10. This prompt includes the user's real-time information as described above. The information processing device 10 works in conjunction with the user terminal 20 to obtain information about the user's real-time activities and family structure. This enables the information processing device 10 to autonomously set priorities according to the user's situation. 【0051】 Alternatively, the prompt may include information about the user's past actions. The information processing device 10 works in conjunction with the learning support means 30 to obtain action information about the user's past actions. In this example, the action information is the result of whether or not the user performed tasks related to the scheduled data, as recorded in a database managed by the information processing device 10 or the learning support means 30. 【0052】 Here, the user behavior information that the information processing device 10 refers to when constructing a prompt consists of a triplicate, for example, time, location information, and behavior type. The information processing device 10 refers to a database and obtains data corresponding to these combinations. Specific examples of behavior information will be described later. Now, regarding priority requests, the prompts generated by the information processing device 10 will be explained. 【0053】 Figure 5 illustrates a prompt related to priority requests. Figure 5 is a schematic diagram including an example of a prompt automatically generated based on the RAG function of the information processing device 10. Prompt P1 includes text such as, "Based on user U1's activity history and location information, please set the priority of the following appointments to three levels: low, medium, and high. 1. December 4, 2024, 10:00 AM: Parent-teacher meeting at child's school (Location: school)..." In this example, activity history and location information are shown as examples of activity information. In this example, the priority is defined in three levels: low, medium, and high in prompt P1. The priority may be defined using any indicator, including indicators available to the user in this application. Appointment data includes the content of the appointment, date and time, or location, and is automatically entered into prompt P1 based on various information extracted in step S102, for example. 【0054】 Figure 5 illustrates a simplified example of inputting natural language text as a prompt into LLM90. However, the prompt format can be anything; for example, a JSON (JavaScript Object Notation) prompt is also acceptable. In this case, instead of the text mentioned above, a string such as "{"action": "determine_priority","data": {"event": "***","date": "****-**-**","time": "****","context": "Time:Location:Activity Type."}}" could be constructed as the prompt. In this example, "action" represents the priority setting, "event," "date," and "time" represent the content and date / time of the event, and "context" represents the background or activity information of the event (time, location, and activity type). Note that this is merely an example of a general data format, and the prompt format can be anything. 【0055】 In addition, information regarding user U1's family structure and travel time to the location where the scheduled event will take place is entered into prompt P1 as appropriate. Family structure information refers to information indicating the family structure, including information indicating the relationship from the user's perspective, such as "husband, son 1, son 2." Family structure information may also include attribute information such as each person's age and occupation. LLM90 performs a process to assign a priority to each event according to the priority request. Here, we will explain how to obtain the activity information. 【0056】 Returning to Figure 4, in step S104, the learning support means 30 inputs additional learning data to the LLM 90. Here, the information processing device 10 instructs the learning support means 30 to input additional user U1 behavior information to the LLM 90. In this example, the additional learning data includes user behavior information, such as the history of location information of places the user has visited in the past, tasks suggested by the system to the user, or data on tasks the user has completed. 【0057】 These data are identified as training data to be provided to LLM90, according to the schedule subject to priority requests. For example, in this embodiment, the additional training data output by the training support means 30 is classified into Table 1 below. [Table 1] 【0058】 In Table 1, the information types are predefined in the database of the learning support device 30 and include, for example, scheduled data, activity history, location information, and task completion history. Of these, the scheduled data is the same data as the schedule entered in prompt P1. Activity history, location information, and task completion history are examples of activity information related to the user's past actions. Of these, the task completion history includes feedback on the execution results of tasks recorded in the database, etc. Activity history and location information are estimated as time-series actions and locations based on analysis software programs implemented in the learning support device 30. 【0059】 In this example, the learning support means 30 estimates the behavioral history and location information through three processes: (1) matching with map data, (2) analyzing the user's behavior, and (3) generating natural language. Regarding (1) matching with map data, the learning support means 30 compares the acquired coordinate data of the user terminal 20 (i.e., a set of coordinates and time) with existing map data (so-called geocoding) to estimate the specific location of the user (for example, "Tokyo Station"). 【0060】 Furthermore, (2) Regarding user behavior analysis, the learning support means 30 analyzes the user's behavior based on basic information about the individual user (e.g., place of residence or place of work) and the user's past behavioral trends. Alternatively, after identifying location information, the learning support means 30 estimates a detailed location such as an office, restaurant, or home according to a predetermined category classification of facilities. 【0061】 Furthermore, (3) with respect to natural language generation, the learning support means 30 applies NLG (Natural Language Generation) technology to the analysis results regarding the user's behavior and location to generate more natural sentences (hereinafter referred to as "natural sentences"). In this example, the natural sentence representing location information is generated as text such as "Current location is the office." The NLG algorithm includes methods based on rule-based or machine learning models. This allows the learning support means 30 to acquire learning data based on the selection of more natural sentence structures and word combinations. 【0062】 The information processing device 10 works in conjunction with the learning support means 30 to request the LLM 90 to assign priorities more effectively based on the user's behavioral information. For example, when setting priorities for various appointments, if a parent-teacher meeting the user attended in the past was an important appointment, or if the user consistently took their child to and from extracurricular activities in the past, these appointments would likely be given a high priority. In addition, priorities are assigned based on other factors such as family relevance, travel time, location information, and defined indicators related to past behavioral trends. Any method may be used for this. 【0063】 As described above, in steps S103 to S104, based on the prompt P1 from the information processing device 10 and the input of additional learning data from the learning support means 30, the LLM 90 can assign priority to the specified scheduled data. The additional learning data input to the LLM 90 by the learning support means 30 may be in JSON format. 【0064】 In step S105, the information processing device 10 obtains the schedule data assigned a priority from the LLM 90. Referring again to Figure 5, the information processing device 10 extracts information regarding the priority assigned to each schedule from the response result of the LLM 90 and links it with a predetermined database. In this example, the response result of the LLM 90 can take various forms. Therefore, the information processing device 10 is required to process data according to various data formats. For example, if the output result contains a JSON string such as "{"status": "success","priority": "high","reason": "****."}", the information processing device 10 extracts the priority of the corresponding schedule from the priority field. In this example, status represents the processing result (e.g., success or error), priority represents the level of the determined priority, such as high, medium, or low, and reason represents the reason for setting that priority. 【0065】 Based on these implementations, the information processing device 10 and the LLM 90 can exchange data more efficiently. The information processing device 10 records priority-based schedule data in the database. Alternatively, the information processing device 10 may record the priority corresponding to a schedule already recorded in the database. Here, we will describe the database for managing user schedules. 【0066】 Figure 6 is an example diagram of the user schedule database 1000. The user schedule database 1000 contains multiple records related to a user. Each record corresponds to information specific to each user (or account). Each record includes a user ID, subscriber information, schedule data, task information, activity history, and location information. The user ID is unique identification information corresponding to an account issued by a user using this application. Subscriber information is basic user information obtained according to the contract status of communication services, etc., and includes, for example, name, telephone number, gender, age, and family structure. Schedule data is information for managing the user's schedule, which is recorded (or has been recorded) in the past, present, and future, and includes, for example, date, time, schedule content, and priority. In this example, the date and time are date and time information that shows a timeline in chronological order, and include, for example, a schedule corresponding to a calendar function. The schedule content is data that shows the content of the user's schedule, and includes schedules extracted by the information processing system 1. Priority is an index related to the priority of each schedule assigned by LLM90. Task information is a record that shows the tasks for each scheduled event, generated by the "task decomposition" described later. Activity history and location information are records that show the history of the user's activities and location, recorded continuously or periodically for each date (or time). 【0067】 In the information processing system 1, information regarding the user's schedule is stored in the user schedule database 1000, and the information processing device 10 or the learning support means 30 can access the database at will. For example, when the learning support means 30 performs the processing related to assigning priorities as described above, it can obtain data from the database to input to the LLM 90. 【0068】 The information processing device 10 records priority-assigned schedule data obtained from the LLM 90 and can also present the user with the correspondence between the schedule data and its priority via the user terminal 20. In this example, the information processing device 10 receives editing instructions from the user for schedules that have been assigned a priority. The editing instructions are instructions for editing the schedule. The user performs modification processing related to the schedule data or priority via various UI (User Interface) displayed on the user terminal 20. The information processing device 10 updates the data in the user schedule database 1000 in response to the user's input, i.e., the editing instructions. This process may be executed at any time. 【0069】 Returning to Figure 4, in step S106, the information processing device 10 requests the LLM 90 to break down the schedule into multiple tasks (hereinafter referred to as the "breakdown request"). In this example, the breakdown request includes a prompt that the information processing device 10 automatically generates. Accordingly, the learning support means 30 can input additional learning data to the LLM 90 according to the user's behavior information or information about family structure. 【0070】 Furthermore, the processing in step S106 may be executed concurrently with the priority request in step S103. Alternatively, the information processing device 10 may request the LLM 90 to decompose schedules that meet predetermined conditions (for example, only schedules with medium to high priority) from among the schedules that have already been assigned a priority in the user schedule database 1000. In this case, the learning support means 30 can identify user behavior information, etc., corresponding to the target schedule and input it into the LLM 90 as additional data. 【0071】 In addition, the information processing device 10 may cooperate with the user terminal 20 and issue disassembly requests based on the user's real-time actions and information regarding family structure. The timing of the disassembly requests may be determined in any way in the information processing system 1. 【0072】 The following describes the prompts generated by the information processing device 10 in response to a decomposition request for a scheduled event called "Parents' Meeting" in the user schedule database 1000. 【0073】 Figure 7 illustrates a prompt for a decomposition request and the result generated by LLM90. Prompt P2 includes text such as, "Please decompose the following schedule of user U1 into 5 specific tasks and rearrange them in chronological order. Schedule: December 4, 2024, 10:00 AM, Parent-Teacher Meeting at my child's school..." In this example, prompt P2 includes the number of tasks to be decomposed (e.g., 5) and the order in which the multiple tasks should be output (e.g., chronological order). This information is predetermined in a rule-based system and determined by the information processing device 10 according to the schedule subject to the decomposition request. The information processing device 10 works in conjunction with the learning support means 30 to identify the data used for "task decomposition" for each schedule and inputs it into LLM90. In response to this prompt, LLM90 decomposes the specified schedule into tasks. Here, "decomposing a schedule into tasks" means generating one or more tasks from the schedule. This allows LLM90 to decompose schedules into tasks more effectively. Tasks may be generated based on any perspective; for example, the information processing device 10 may arbitrarily specify predetermined perspectives such as schedule, location, reservation, purchase, arrangement, reminder, or confirmation. 【0074】 The generated result R2 represents data on task decomposition generated by LLM90 in response to the decomposition request, and includes text such as, "The schedule has been decomposed into five specific tasks and sorted in chronological order of when they should be executed. (1) November 28, 2024: Confirmation of notice and contents of the parent-teacher meeting... Check notifications and emails from the school to confirm the detailed date, time, location, and agenda of the parent-teacher meeting. It is a good idea to make a note in advance of any questions you would like to ask other parents or any information you would like to share..." The generated result R2 represents, for example, the tasks that should be executed by the day the target schedule is to be executed, in chronological order. Therefore, the information processing device 10 or the learning support means 30 may make a decomposition request to LLM90 to take into account the schedule recorded in the user schedule database 1000. This allows LLM90 to effectively generate multiple tasks corresponding to the target schedule. 【0075】 Returning to Figure 4, in step S107, the information processing device 10 obtains information from the LLM 90 indicating multiple tasks for each schedule. In this example, the information processing device 10 records the multiple tasks in the task information of the user schedule database 1000. The task information is a record of the task and whether or not it is executed, and is used, for example, for task management for each schedule. The information processing device 10 also has a database for managing multiple tasks collectively. Here, we will describe the database for managing tasks. 【0076】 Figure 8 illustrates the task database 2000. The task database 2000 contains multiple records related to tasks. Each record corresponds to information specific to a task. Each record includes the task ID, execution date and time, execution details, and whether or not the task was executed. The task ID is unique identification information corresponding to each scheduled task. The task ID has a common identifier with tasks recorded in the user schedule database 1000. The execution date and time and execution details are the scheduled date and time and specific actions to be performed by the user for the task. This information is recorded in each record by the information processing device 10 extracting the generated data related to task decomposition output by the LLM 90. Whether or not the task was executed indicates whether or not the target task was performed by the user. In addition to the execution status, this record may also record the proposal status regarding the task to the user. This allows the information processing device 10 to identify the execution status of each task and manage schedules. 【0077】 In the information processing system 1, the task database 2000 records or updates each data item in conjunction with the user schedule database 1000. The information processing device 10 and the learning support means 30 can access the task database 2000 at will. For example, the information processing device 10 can use the task database 2000 when proposing tasks and registering completed tasks, as described later. Alternatively, the learning support means 30 can use the task database 2000 as learning data to input into the LLM 90 in the process of assigning priority to schedules or decomposing tasks as described above. 【0078】 The information processing device 10 outputs schedule data to the user terminal 20, which includes information indicating multiple tasks generated by the LLM 90 upon registration of a task in the database. The schedule data includes a schedule with priority and multiple tasks corresponding to that schedule. In this example, the user can perform editing or modification operations on the schedule data displayed on the user terminal 20. The information processing device 10 updates the schedule data in the database, particularly the records related to tasks, in response to user input. 【0079】 Based on the above, the information processing device 10, by utilizing the LLM90, can comprehensively consider factors such as the user's past behavior, family structure, time requirements, and priorities, and generate subtasks more flexibly. In other words, while conventional fixed task division based on rule-based systems made it difficult to reflect the individual circumstances of the user, the present invention can generate tasks that can be executed according to the user's environment or situation at the time. Next, a method for more effectively suggesting tasks as a function for managing the user's schedule in the information processing system 1 will be described. 【0080】 Returning to Figure 4, in event E2, the information processing device 10 detects an execution suggestion trigger. In this example, the execution suggestion trigger indicates the conditions that prompt the information processing device 10 to suggest a task to the user to perform. In event E2, the information processing device 10 starts the subsequent processing if the predetermined conditions (hereinafter referred to as "execution conditions") are met. In this example, the execution conditions include, for example, (A) conditions corresponding to the schedule or task, and (B) conditions corresponding to the user's context. 【0081】 First, (A) Regarding conditions corresponding to a schedule or task, the information processing device 10 can set execution conditions in advance based on various perspectives on the schedule or task. For example, if "arranging a cake" is scheduled as a task related to the preparation of a "child's birthday party," the information processing device 10 can set the execution condition for this task as "the cake order must not be completed one week before the birthday party." The information processing device 10 will determine whether the execution condition for the task has been met when one week before the birthday party arrives. 【0082】 In addition, execution suggestion triggers are determined according to the user's situation, such as when multiple appointments are scheduled in a day, or when the user is handling multiple tasks simultaneously. In this example, if the user is attending a parent-teacher meeting or taking their child to and from extracurricular activities while also attending work-related meetings, prioritizing each appointment or task becomes important. Therefore, the information processing device 10 may set conditions related to priority, or it may set them in combination with conditions that depend on the user's context, as described later. 【0083】 Next, with respect to (B) conditions corresponding to the user's context, the information processing device 10 determines whether the execution conditions corresponding to the context obtained from the user terminal 20 via an API (Application Programming Interface) or the like are met. In this example, the context is information for identifying the user's actions, and includes, for example, action information, location information, payment information, or operation information related to the terminal. For example, the information processing device 10 determines whether the actions estimated from the user's context are suitable for execution conditions that are set in advance for each task, such as visiting a specific place, whether or not a specific action is performed, or the arrival of a specific date. 【0084】 In this example, if the user has scheduled activities during the day, such as attending a parent-teacher meeting, taking the child to and from extracurricular activities, and attending a meeting, various conditions may be set for the situation inferred from the user's context (e.g., location, time, or task completion status). This allows LLM90 to comprehensively consider travel time or family structure and suggest the highest priority tasks in real time. 【0085】 Context regarding user actions via the user terminal 20 is acquired periodically, and the information processing device 10 can propose a task when the context satisfies certain conditions. The execution conditions can be anything, and execution conditions other than (A) and (B) may be defined for each schedule or task. Subsequent processing begins when the execution conditions are met. 【0086】 In step S108, the information processing device 10 requests the LLM 90 (hereinafter referred to as the "suggestion request") to suggest, for example, which task the user should perform from among several tasks, based on the given situation, for tasks whose execution conditions have been met. In this example, the suggestion request includes a prompt that the information processing device 10 automatically generates. Here, the prompt generated by the information processing device 10 in relation to the suggestion request will be described. 【0087】 Figure 9 illustrates a prompt for a request for suggestions and the result generated by LLM90. Prompt P3 includes text such as, for example, "Please suggest an action that user U1 should take on December 4th, along with the reason. [Prior information]...[Schedule]..." In this example, prompt P3 includes information about the schedule or task to which the suggestion should be made, as well as information about the user's state or situation (prior information in Figure 9). 【0088】 Here, for example, if multiple appointments and tasks are scheduled in a single day, the information processing device 10 is required to propose tasks more efficiently within the limited time, taking into account the user's travel time or family structure. Therefore, the data regarding the user's situation specified by the information processing device 10 is classified, for example, into Table 2 below. [Table 2] 【0089】 The information regarding the status of these users in Table 2 is determined by the information processing device 10 according to the schedule or task to which the request for proposal pertains, and is input when generating the prompt P3 indicating the request for proposal. The information processing device 10 may also specify the information in Table 2 according to the execution conditions. 【0090】 Furthermore, in a suggestion request, the information processing device 10 can input a specification to prompt P3 regarding the timing of notifying the user of the suggestion or the website related to the suggestion. In this example, if the task targeted by the suggestion request is "arranging a birthday cake," the information processing device 10 may request the LLM90 to provide a reminder for the reservation or a link to an e-commerce site that includes the cake ordering page. Alternatively, if the user has multiple tasks to complete in a day, the suggestion request may include information about the user's travel time or family structure to help the LLM90 efficiently suggest tasks. This allows the LLM90 to estimate tasks that the user might overlook and suggest them at the appropriate time. 【0091】 Returning to Figure 4, in step S109, the learning support means 30 outputs additional learning data to the LLM 90. At this point, the information processing device 10 instructs the learning support means 30 to input additional user U1 behavior information to the LLM 90. 【0092】 Alternatively, the process may be replaced by the information processing device 10 coordinating with the learning support means 30 to input user status data into prompt P3 and individually inputting it into the LLM 90. In this example, the learning support means 30 can identify additional learning data according to the schedule or task that is the subject of the proposal request. This includes, for example, a process in which the learning support means 30 selectively extracts additional learning data from the data recorded in the user schedule database 1000 or the task database 2000. Various analysis methods or extraction methods can be applied to this process, and any such method may be used. 【0093】 In step S110, the information processing device 10 acquires information indicating the proposal results generated by LLM90. Refer to Figure 9 again. The generated result R3 represents data related to the schedule or task proposal generated by LLM90 in response to the proposal request, and includes text such as, for example, "We would like to propose the actions to be taken on Wednesday, December 4th. 1. Choose to work from home. Reason: There is a parent-teacher meeting at 10am, ... Example schedule: ..." The generated result R3 schedules the tasks to be performed in chronological order according to the target schedule. In this example, the information processing device 10 records the tasks included in the schedule of the generated result R3 in the user schedule database 1000. 【0094】 Here, the information processing device 10 performs processing to execute suggestions to the user. The information processing device 10 can basically suggest tasks to the user or send notifications via the user terminal 20. This processing is defined in advance in a database or similar based on the functions implemented in this application. 【0095】 The information processing device 10 may propose scheduled events or tasks that meet the execution conditions to the user as specific functions corresponding to this application, or it may individually notify the user of tasks according to the user context acquired by the user terminal 20. When using the user context, the information processing device 10 notifies the user when the context related to location information, etc., meets the defined conditions. The notification trigger for each task may be set in any way; for example, the user terminal 20 may send a push notification when the user context related to location information, time information, or completion information of other tasks meets the predetermined conditions. 【0096】 More specifically, the system may suggest work tasks upon the user's arrival at the office, or suggest shopping tasks or picking up / dropping off children from extracurricular activities on the way home from daycare. Since the timing of notifications may vary depending on the user's situation, the information processing device 10 may also request the LLM 90 to specify the timing of the notification when making a suggestion request. In this way, the information processing system 1 can utilize the reasoning capabilities of the LLM 90 to propose tasks that take into account the user's family structure, past behavioral history, or location information (or travel time) from a comprehensive or multifaceted perspective. 【0097】 Returning to Figure 4, in step S111, the information processing device 10 registers the results of the user's execution of the proposed task (hereinafter referred to as "execution results") in the database. This process includes registering the results of the user's execution of multiple tasks. The task execution results are registered in various databases and used for processes related to prioritizing schedules, task decomposition, and task execution proposals. The information processing device 10 and the learning support means 30 can use the user's execution results to provide feedback, evaluation, or analysis on the user's actions, thereby improving the functionality for more effective task management. 【0098】 As described above, the information processing system 1 can provide a service for efficiently managing the user's schedule and tasks. In this example, the information processing device 10 can utilize the LLM90 to more effectively prioritize schedules, decompose tasks, and propose task execution. Thus, in the present invention, from the perspective of user convenience regarding task management functions, it is expected that tasks that were previously performed manually by the user will be automated, and flexible processing will be performed taking into account the individual user's state or circumstances. 【0099】 3. Variant The present invention is not limited to the embodiments described above, and various modifications are possible. Several modifications are described below. Two or more of the items described below may be combined and applied. 【0100】 (1) Information processing system 1 The hardware and network configurations in the information processing system 1 are not limited to those illustrated in the embodiments. The information processing system 1 may have any hardware and network configurations as long as they can realize the required functions. For example, multiple physical devices may cooperate to function as the information processing system 1. For example, at least some of the functions of the information processing device 10 may be implemented in the user terminal 20 or the learning support means 30. For example, the user terminal 20 or the learning support means 30 may have at least some of the functions of the information processing device 10 related to scheduling, task decomposition, and task execution suggestion. 【0101】 (2) Information processing device 10 Some of the functions of the information processing device 10 may be implemented on other servers. These servers may be, for example, physical servers or virtual servers (including so-called cloud servers). Furthermore, the correspondence between functional elements and hardware is not limited to those illustrated in the embodiments. For example, at least some of the functions described in the embodiments as being implemented on the information processing device 10 may be implemented on other devices or systems, and conversely, at least some of the functions described as being implemented on other devices or systems may be implemented on the information processing device 10. In this example, at least some of the functional elements implemented by the information processing device 10 may be implemented on other devices or systems, for example, AI, applications, or other software. 【0102】 (3) User terminal 20 The user terminal 20 is not limited to those illustrated in the embodiments. The user terminal 20 may perform the above-described processing using any display screen, input device, or UI. The functions of the application installed on the user terminal 20 may be modified in any way, and may be any functions that can be provided by the task management assistant defined in the information processing system 1. Furthermore, the functions related to the application may be implemented in any way depending on the UI (User Interface) provided by the user terminal 20. For example, the user terminal 20 may provide a calendar function, a schedule editing function, a task management function, a display switching function, a notification function, a data sharing function, or a function to link with other applications in the task management assistant. 【0103】 (4) Learning support means 30 The learning support means 30 is not limited to those exemplified in the embodiments. The learning support means 30 includes devices or systems having AI, applications, or software, and may be implemented in any form. The learning support means 30 may be implemented in the information processing device 10, or the information processing device 10 may execute the processing in the learning support means 30. The learning support means 30 may cooperate with existing services and acquire user behavior information from these services. For example, in addition to location information or payment information provided by the telecommunications carrier at the user terminal 20, the learning support means 30 may cooperate with scheduling services, map applications, or e-commerce sites operated by other businesses to acquire schedule information, time information, location information, travel information, and payment information as user behavior information. 【0104】 (5) How to use the Task Management Assistant The sequence chart shown in Figure 4 is merely an example of operation, and the operation of the information processing system 1 is not limited to this. Some of the illustrated operations may be changed or omitted, the order may be changed, or new operations may be added. For example, the user may input the schedule data in any way. In this example, the user terminal 20 can output schedule data in a format determined according to the type of user operation performed through this application to the information processing device 10. In step S101, the information processing device 10 may simultaneously make a request to extract schedule data, a priority request, and a decomposition request to the LLM 90. 【0105】 The following sections describe variations in the operation of the information processing system 1 regarding scheduling prioritization, task decomposition, and task execution proposals. 【0106】 (6) How to prioritize appointments Prioritization in event E1 may be based on any circumstances or triggers. In this example, the information processing device 10 may perform processing to set priorities in accordance with the context acquired in real time, in addition to the user's behavior information. In step S103, the information processing device 10 may input additional user-specific data to prompt P1 using at least some of the functions of the learning support means 30. The information processing device 10 may also request the LLM 90 to assign priorities to each task, in addition to assigning priorities to each schedule. In step S104, the data that the learning support means 30 learns from the LLM 90 can be anything; for example, data about the user's family or other users that are similar to the user's behavioral tendencies may be used. 【0107】 (7) Operation method related to task decomposition In step S106, the information processing device 10 may also make requests to combine, integrate, or delete tasks (hereinafter referred to as "integration requests") in addition to decomposition requests. In this example, the information processing device 10 selects and extracts tasks that are the target of the integration request from among multiple tasks registered in the database, based on the user's status or defined conditions. At this time, the information processing device 10 may use any method to select the tasks, for example, by determining them according to priority. Furthermore, although the embodiment describes an example in which the decomposition request is executed in parallel with the setting of priority, the information processing device 10 may make a decomposition request at any timing. The information processing device 10 generates a prompt that includes the selected tasks and makes an integration request to the LLM 90. The information processing device 10 obtains the result of the integration request from the LLM 90 and updates the information in the database. 【0108】 (8) Operation method for proposing task execution In event E2, the execution conditions may be defined in any way. For example, the information processing device 10 may determine whether the execution conditions have been met based on the user's context, such as location information, biometric information, or voice information. The request for a proposal to the LLM 90 in steps S108 to S109 may be made in any way. The information processing device 10 may also request the LLM 90 to determine conditions for proposing individual tasks, separate from the execution conditions. In step S111, when the information processing device 10 registers a task performed by the user, it may register it in the database in association with various data such as location information, behavioral information, or payment information. 【0109】 (9) Database (data) The database (or the data itself) of the information processing system 1 shown in Figures 6 and 8 is not limited to those illustrated in the embodiments. Any data can be registered in the database in this example. The user schedule database 1000 and the task database 2000 may record any information. For example, tags, keywords, or labels related to appointments or tasks may be attached to the database. The record structure in the user schedule database 1000 and the task database 2000 can be anything, and searches, filtering, sorting, adding, or updating may be performed on these databases in accordance with the operation of the information processing system 1. 【0110】 (10) Others The various programs executed by processor 101 may be provided by downloading them over a network such as the Internet, or they may be provided recorded on a computer-readable non-temporary recording medium such as a DVD-ROM. Each processor may be, for example, a CPU, an MPU (Micro Processing Unit), or a GPU (Graphics Processing Unit). 【0111】 The block diagrams used in the description of the above embodiments show functional units. These functional blocks (components) are realized by any combination of at least one of hardware and software. Furthermore, the method of realizing each functional block is not particularly limited. That is, each functional block may be realized using one device that is physically or logically coupled, or it may be realized using two or more physically or logically separated devices that are directly or indirectly connected (for example, using wired or wireless connections). A functional block may also be realized by combining the above one device or the above multiple devices with software. 【0112】 Functions include, but are not limited to, judgment, decision, determination, calculation, calculation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, assumption, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating (mapping), and assigning. For example, a functional block (configuration part) that enables transmission is called a transmitting unit or transmitter. As mentioned above, the method of implementation is not particularly limited. 【0113】 For example, the information processing device 10 in one embodiment of the present disclosure may function as a computer that performs the processing of the present disclosure. 【0114】 Each aspect or embodiment described in this disclosure may be applied to at least one of the following systems: LTE (Long Term Evolution), LTE-A (LTE-Advanced), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), 5G (5th generation mobile communication system), FRA (Future Radio Access), NR (new Radio), 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 802.20, UWB (Ultra-WideBand), Bluetooth (registered trademark), and other appropriate systems, as well as next-generation systems extended based thereon. Furthermore, multiple systems may be applied in combination (for example, a combination of at least one of LTE and LTE-A with 5G). 【0115】 The processing procedures, sequences, flowcharts, etc., of each aspect or embodiment described in this disclosure may be reordered, provided they do not contradict each other. For example, the methods described in this disclosure present various step elements in an exemplary order and are not limited to the specific order presented. 【0116】 Input and output information may be stored in a specific location (e.g., memory) or managed using a management table. Input and output information may be overwritten, updated, or appended to. Output information may be deleted. Input information may be sent to other devices. 【0117】 The determination may be made by a value represented by 1 bit (0 or 1), by a boolean value (true or false), or by a numerical comparison (for example, a comparison with a predetermined value). 【0118】 Although the present disclosure has been described in detail above, it will be 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 intent and scope of the present disclosure as defined by the claims. Therefore, the descriptions in the present disclosure are illustrative and not intended to be restrictive in any way. 【0119】 Software should be broadly interpreted to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, execution threads, procedures, functions, etc., whether they are called software, firmware, middleware, microcode, hardware description languages, or by any other name. Furthermore, software, instructions, information, etc., may be transmitted and received via a transmission medium. For example, if software is transmitted from a website, server, or other remote source using at least one of wired technologies (such as coaxial cable, fiber optic cable, twisted pair, or digital subscriber line (DSL)) and wireless technologies (such as infrared or microwave), at least one of these wired and wireless technologies is included in the definition of a transmission medium. 【0120】 The information, signals, etc., described herein may be represented using any of the following different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc., which may be referred to throughout the above description, may be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof. Terms used herein and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meaning. 【0121】 Furthermore, the information, parameters, etc., described in this disclosure may be expressed using absolute values, relative values ​​from a predetermined value, or corresponding other information. 【0122】 In this disclosure, the phrase "based on" does not mean "based solely on" unless otherwise specified. In other words, the phrase "based on" means both "based solely on" and "based at least on." 【0123】 Any reference to elements using designations such as “First,” “Second,” etc., as used in this disclosure does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient way to distinguish between two or more elements. Accordingly, references to the First and Second elements do not imply that only two elements may be employed, or that the First element must precede the Second element in any way. 【0124】 In the above-described configuration of each device, the term "part" may be replaced with "means," "circuit," "device," etc. 【0125】 Where the terms “include,” “including,” and variations thereof are used in this disclosure, these terms are intended to be inclusive, as is the term “comprising.” Furthermore, the term “or” as used in this disclosure is not intended to mean exclusive OR. 【0126】 In this disclosure, if articles are added by translation, such as a, an, and the in English, this disclosure may include the fact that the noun following these articles is plural. 【0127】 In this 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 "combine" may be interpreted similarly to "different." [Explanation of symbols] 【0128】 1... Information processing system, 10... Information processing device, 20... User terminal, 30... Learning support means, 90... LLM, 9... Network, 11... Reception unit, 12... Acquisition unit, 13... Priority request unit, 14... Decomposition request unit, 15... Proposal request unit, 181... Output unit, 182... Proposal unit, 183... Registration unit, 184... Notification unit, 191... Storage unit, 192... Control unit, 101... Processor, 102... Memory, 103... Storage, 104... Communication device, 1000... User schedule database, 2000... Task database, E... Event, P... Prompt, R... Generation result, T... Task

Claims

[Claim 1] A reception desk that accepts input for multiple appointments related to the user, An acquisition unit that acquires behavioral information relating to the user's past actions, including a history of location information of places the user has visited in the past, and contextual information indicating the user's current status. A priority request unit requests a large-scale language model to assign a priority to each of the multiple schedules using the aforementioned behavioral information and contextual information. An output unit that outputs schedule data for the plurality of appointments that have been given priority by the large-scale language model in response to the above request. An information processing device having [Claim 2] A reception desk that accepts input for multiple appointments related to the user, An acquisition unit that acquires behavioral information regarding the user's past actions and contextual information indicating the user's current status, A priority request unit requests a large-scale language model to assign a priority to each of the multiple schedules using the aforementioned behavioral information and contextual information. An output unit that outputs schedule data for the plurality of appointments that have been given priority by the large-scale language model in response to the above request, A proposal unit that proposes tasks for the user to perform based on the aforementioned scheduled data. It has, The aforementioned behavioral information includes information that identifies the tasks among the proposed tasks that the user has completed. Information processing device. [Claim 3] A reception desk that accepts input for multiple appointments related to the user, An acquisition unit that acquires behavioral information regarding the user's past actions and contextual information indicating the user's current status, A priority request unit requests a large-scale language model to assign a priority to each of the multiple appointments, using the aforementioned behavioral information and contextual information, and based on information regarding the user's family structure. An output unit that outputs schedule data for the plurality of appointments that have been given priority by the large-scale language model in response to the above request. An information processing device having [Claim 4] A reception desk that accepts input for multiple appointments related to the user, An acquisition unit that acquires behavioral information regarding the user's past actions and contextual information indicating the user's current status, A priority request unit that requests a large-scale language model to assign a priority to each of the multiple appointments using the aforementioned behavioral information and the aforementioned contextual information, the priority request unit that requests the model to assign a priority considering the travel time between each appointment, based on information that identifies the time and location for each of the multiple appointments, An output unit outputs schedule data including information specifying the time and location for each of the multiple schedules that have been prioritized by the large-scale language model in response to the aforementioned request. An information processing device having [Claim 5] A reception desk that receives input for multiple appointments related to a user and editing instructions for appointments with assigned priorities, An acquisition unit that acquires behavioral information regarding the user's past actions and contextual information indicating the user's current status, A priority request unit requests a large-scale language model to assign a priority to each of the multiple schedules using the aforementioned behavioral information and contextual information. A schedule data relating to the plurality of schedules to which priority has been assigned by the large-scale language model in response to the above request, and an output unit that outputs the schedule data for receiving editing instructions from the user for the schedule to which priority has been assigned in the receiving unit. An information processing device having [Claim 6] A reception desk that accepts input for multiple appointments related to the user, An acquisition unit that acquires behavioral information regarding the user's past actions and contextual information indicating the user's current status, A priority request unit requests a large-scale language model to assign a priority to each of the multiple schedules using the aforementioned behavioral information and contextual information. An output unit that outputs schedule data for the plurality of appointments that have been given priority by the large-scale language model in response to the above request, A decomposition request unit requests the large-scale language model to decompose the schedules among the aforementioned multiple schedules that meet the given priority conditions into multiple tasks. An information processing device having [Claim 7] A proposal unit that suggests to the user which of the aforementioned multiple tasks should be performed. The information processing apparatus according to claim 6, having the following features. [Claim 8] Registration unit that registers the results of the user performing each of the multiple tasks in the database. The information processing apparatus according to claim 6, having the following features. [Claim 9] Computers A step to accept input for multiple appointments related to the user, The steps include obtaining behavioral information relating to the user's past actions, which includes a history of location information of places the user has visited in the past, and contextual information indicating the user's current status. The steps include requesting a large-scale language model to assign a priority to each of the multiple appointments using the aforementioned behavioral information and contextual information, The steps include outputting schedule data for the plurality of appointments that have been prioritized by the large-scale language model in response to the aforementioned request, and An information processing method having [Claim 10] Computers A step to accept input for multiple appointments related to the user, The steps include obtaining behavioral information regarding the user's past actions and contextual information indicating the user's current status, The steps include requesting a large-scale language model to assign a priority to each of the multiple appointments using the aforementioned behavioral information and contextual information, The steps include outputting schedule data for the multiple schedules that have been prioritized by the large-scale language model in response to the aforementioned request, The steps include proposing tasks that the user should perform based on the aforementioned scheduled data, and It has, The aforementioned behavioral information includes information that identifies the tasks among the proposed tasks that the user has completed. Information processing methods. [Claim 11] Computers A step to accept input for multiple appointments related to the user, The steps include obtaining behavioral information regarding the user's past actions and contextual information indicating the user's current status, The steps include: requesting a large-scale language model to assign a priority to each of the multiple appointments using the aforementioned behavioral information and contextual information, and based on information regarding the user's family structure; The steps include outputting schedule data for the plurality of appointments that have been prioritized by the large-scale language model in response to the aforementioned request, and An information processing method having [Claim 12] Computers A step to accept input for multiple appointments related to the user, The steps include obtaining behavioral information regarding the user's past actions and contextual information indicating the user's current status, A step of requesting a large-scale language model to assign a priority to each of the multiple appointments using the aforementioned behavioral information and the aforementioned contextual information, the step of requesting the model to assign a priority considering the travel time between each appointment based on information that identifies the time and place for each of the multiple appointments, The steps include outputting schedule data, including information specifying the time and location, for each of the multiple schedules that have been prioritized by the large-scale language model in response to the aforementioned request, and An information processing method having [Claim 13] Computers A step that accepts input of multiple appointments for the user and editing instructions for appointments to which priorities have been assigned, The steps include obtaining behavioral information regarding the user's past actions and contextual information indicating the user's current status, The steps include requesting a large-scale language model to assign a priority to each of the multiple appointments using the aforementioned behavioral information and contextual information, A schedule data relating to the plurality of appointments to which priority has been assigned by the large-scale language model in response to the aforementioned request, wherein the receiving step involves outputting the schedule data for receiving editing instructions from the user for the appointments to which priority has been assigned. An information processing method having [Claim 14] Computers A step to accept input for multiple appointments related to the user, The steps include obtaining behavioral information regarding the user's past actions and contextual information indicating the user's current status, The steps include requesting a large-scale language model to assign a priority to each of the multiple appointments using the aforementioned behavioral information and contextual information, The steps include outputting schedule data for the multiple schedules that have been prioritized by the large-scale language model in response to the aforementioned request, The steps include: requesting the large-scale language model to decompose the schedules among the aforementioned multiple schedules into multiple tasks, for those schedules whose assigned priority meets the conditions; An information processing method having

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