system

Abstract

The system according to the embodiment aims to efficiently manage procedures and information gathering associated with moving. [Solution] The system according to the embodiment comprises a reception unit, an analysis unit, a selection unit, a listing unit, a management unit, a subsidy display unit, and an estimate unit. The reception unit accepts information from the user regarding moving companies, government notifications, and family composition. The analysis unit analyzes the information received by the reception unit. The selection unit selects candidate medical institutions or educational institutions based on the information analyzed by the analysis unit. The listing unit displays the candidates selected by the selection unit to the user, who then selects appropriate information to create a list. The management unit manages expenses and tasks based on the information listed by the listing unit. The subsidy display unit displays a list of subsidy programs related to relocation based on the information managed by the management unit. The estimate unit acts as a bulk quote site based on the information displayed by the subsidy display unit.

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technologies have had the problem that the many procedures and information gathering required for moving are cumbersome and difficult to manage efficiently.

[0005] The system according to the embodiment aims to efficiently manage procedures and information gathering associated with moving. [Means for solving the problem]

[0006] The system according to the embodiment includes a reception unit, an analysis unit, a selection unit, a listing unit, a management unit, a subsidy display unit, and an estimate unit. The reception unit accepts information from the user regarding moving companies, government notifications, and family composition. The analysis unit analyzes the information accepted by the reception unit. The selection unit selects candidate medical institutions or educational institutions based on the information analyzed by the analysis unit. The listing unit displays the candidates selected by the selection unit to the user, who selects appropriate information and creates a list. The management unit manages expenses and tasks based on the information listed by the listing unit. The subsidy display unit displays a list of subsidy programs related to relocation based on the information managed by the management unit. The estimate unit acts as a bulk quote site based on the information displayed by the subsidy display unit. [Effects of the Invention]

[0007] The system according to the embodiment can efficiently manage procedures and information gathering associated with moving. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) A moving information management system according to an embodiment of the present invention accepts and analyzes information on moving companies, government notifications, and family structure from a user, selects candidate medical institutions, and displays the information to the user. Based on the information entered by the user, the moving information management system creates a list of necessary information, manages expenses and tasks, and displays a list of relocation subsidy programs. The moving information management system also functions as a bulk quote site, receiving fees from each selected company. For example, the moving information management system allows a user to input information such as the moving company, government notifications, and family structure. The user inputs information such as the departure and destination points, the number and ages of family members, and the details of the notification to the government. This information is entered into the system's input section. The moving information management system then analyzes the input information and selects candidate medical institutions and educational institutions in the area. For example, it displays information on nearby hospitals and schools. The user can select the necessary information from the displayed candidates and create a list. Furthermore, the moving information management system also manages expenses and tasks. For example, it displays a list of moving expenses and necessary procedures. This allows users to grasp the costs and tasks involved in moving at a glance. The moving information management system also displays a list of subsidy programs related to moving. For example, it displays information on subsidies and grants related to moving. Users can select applicable subsidies from the displayed list and apply for them. Finally, the moving information management system also functions as a bulk quote site. The system's operating costs are covered by receiving fees from each company selected by the user. For example, fees can be received from moving companies and government processing agents. This allows users to centrally manage moving information and efficiently proceed with the moving process. The moving information management system allows users to centrally manage moving information and efficiently proceed with the moving process. For example, this single tool can manage all moving-related information, including selecting a moving company, submitting notifications to government offices, selecting candidate medical and educational institutions, managing costs and tasks, and displaying a list of subsidy programs.

[0029] A moving information management system according to an embodiment includes a reception unit, an analysis unit, a selection unit, a listing unit, a management unit, a subsidy display unit, and an estimate unit. The reception unit receives information from a user about a moving company, notifications to government offices, and family composition. For example, the reception unit receives information from the user, such as the departure and destination points, the number and ages of family members, and the details of notifications to government offices. The analysis unit analyzes the information received by the reception unit. For example, the analysis unit analyzes information input by the user using a data analysis method or algorithm. The selection unit selects candidate medical institutions or educational institutions based on the information analyzed by the analysis unit. For example, the selection unit displays information about nearby hospitals and schools. The listing unit displays the candidates selected by the selection unit to the user, allowing the user to select and list the information they need. For example, the listing unit selects and lists the information they need from the displayed candidates. The management unit manages expenses and tasks based on the information listed by the listing unit. For example, the management unit displays a list of moving expenses and necessary procedure tasks. The subsidy display unit displays a list of subsidy programs related to relocation based on the information managed by the management unit. For example, the subsidy display unit displays information on subsidies and grants associated with moving. The estimate unit acts as a bulk estimate site based on the information displayed by the subsidy display unit. For example, the estimate unit receives a fee from each contractor selected by the user. As a result, the moving information management system according to the embodiment allows users to centrally manage information related to moving and efficiently proceed with the moving process.

[0030] The reception unit can accept information from the user, such as the departure point and destination, the number and ages of family members, and details of notifications submitted to government offices. The reception unit, for example, accepts information on the departure point and destination from the user. For example, the reception unit accepts information such as the address, region, and country entered by the user. The reception unit can also accept information on the number and ages of family members. For example, the reception unit accepts information on the ages and specific needs of each family member. Furthermore, the reception unit can also accept information on details of notifications submitted to government offices. For example, the reception unit accepts information such as a change of address notification, a change of resident registration, and tax-related notifications. By accepting detailed information from the user, more accurate analysis and selection becomes possible.

[0031] The analysis unit can analyze the information received by the reception unit and select candidate medical institutions and educational institutions in the area. The analysis unit analyzes the information received by the reception unit, for example, using data analysis methods and algorithms. For example, the analysis unit selects candidate medical institutions and educational institutions suitable for the area based on information input by the user. The analysis unit can also select candidate medical institutions and educational institutions based on evaluation criteria and a selection process. For example, the analysis unit displays information on nearby hospitals and schools. This makes it possible to select candidate medical institutions and educational institutions suitable for the area.

[0032] The selection unit can display information about hospitals or schools. The selection unit displays, for example, information about nearby hospitals and schools. For example, the selection unit displays information such as the location of the hospital, the services it offers, and reviews. The selection unit can also display information such as the location of the school, the educational programs it offers, and reviews. This makes it possible to provide information about medical institutions and educational institutions that are convenient for the user.

[0033] The listing unit allows the user to select necessary information from the displayed candidates and create a list. The listing unit, for example, allows the user to select necessary information from the displayed candidates and create a list. For example, the listing unit lists the information selected by the user based on the list format and the method of organizing the information. The listing unit can also provide tools and functions for efficiently listing the information selected by the user. This allows the user to efficiently list the information they need.

[0034] The management unit can display a list of costs or procedural tasks required for moving. For example, the management unit displays a list of costs or procedural tasks required for moving. For example, the management unit displays costs and tasks required for moving based on a breakdown of costs and procedural steps. The management unit can also display the costs and tasks required for moving in a visually easy-to-understand format so that the user can grasp the costs and tasks required for moving at a glance. This allows the user to grasp the costs and tasks required for moving at a glance.

[0035] The subsidy display unit can display information about subsidies and grants associated with moving. The subsidy display unit displays, for example, information about subsidies and grants associated with moving. For example, the subsidy display unit displays information about subsidies and grants based on the type of subsidy eligible and application conditions. The subsidy display unit can also display information about available subsidies and grants in a visually easy-to-understand format so that the user can easily check the information about available subsidies and grants. This allows the user to easily check the information about available subsidies and grants.

[0036] The estimating unit can receive fees from each provider selected by the user. For example, the estimating unit receives fees from each provider selected by the user. For example, the estimating unit receives fees from each provider based on a breakdown of fees and payment method. The estimating unit can also receive fees from each selected provider to cover the operating costs of the system. This makes it possible to cover the operating costs of the system.

[0037] The reception unit can reference the user's past moving history and automatically complete input items. The reception unit, for example, references the user's past moving history and automatically completes input items. For example, the reception unit automatically completes notification details previously entered by the user to a moving company or government office. The reception unit can also automatically complete family composition and ages from the user's past moving history. The reception unit can also automatically complete address information previously entered by the user. This makes it possible to streamline input work by automatically completing input items based on the user's past moving history.

[0038] The reception unit can suggest related additional information in real time based on the user's input. The reception unit suggests related additional information in real time based on the user's input, for example. For example, when the user inputs a moving company, the reception unit suggests related government notification information. Furthermore, when the user inputs family composition, the reception unit can also suggest information on related medical institutions and educational institutions. Furthermore, when the user inputs a destination, the reception unit can suggest related local subsidy programs. In this way, by suggesting related information in real time based on the user's input, convenience for the user can be improved.

[0039] The reception unit can provide the optimum input means according to the user's input method. For example, the reception unit provides the optimum input means according to the user's input method (voice, text, image, etc.). For example, if the user selects voice input, the reception unit inputs information using voice recognition technology. Also, if the user selects text input, the reception unit can input information using a keyboard or touch panel. Also, if the user selects image input, the reception unit can input information using image recognition technology. In this way, by providing the optimum input means according to the user's input method, it is possible to make input work more efficient.

[0040] The reception unit can add region-specific input items taking into account the user's geographical location information. The reception unit can add region-specific input items taking into account the user's geographical location information, for example. For example, when a user moves to a specific region, the reception unit can add notification information from local government offices that is specific to that region. Furthermore, when a user moves to a specific region, the reception unit can also add information about medical institutions and educational institutions that are specific to that region. Furthermore, when a user moves to a specific region, the reception unit can also add information about subsidy programs that are specific to that region. This can make input work more efficient by providing region-specific input items that take into account the user's geographical location information.

[0041] The reception unit can analyze the user's social media activity and suggest related input items. The reception unit, for example, analyzes the user's social media activity and suggests related input items. For example, the reception unit can suggest related input items based on the location where the user checked in on social media. The reception unit can also analyze the content of the user's social media posts and suggest related input items. The reception unit can also suggest related input items by taking into account the activities of the user's friends on social media. This makes it possible to make input work more efficient by suggesting related input items based on the user's social media activity.

[0042] The reception unit can customize the input interface by reflecting the user's past feedback. The reception unit customizes the input interface by reflecting the user's past feedback, for example. For example, the reception unit improves the input interface based on feedback provided by the user in the past. The reception unit can also suggest an easy-to-use input interface based on the user's past feedback. The reception unit can also adjust the design of the input interface by reflecting the user's past feedback. In this way, the input interface can be customized based on the user's past feedback, thereby improving user convenience.

[0043] The analysis unit can improve the accuracy of the analysis by referring to the user's past moving data during analysis. The analysis unit can improve the accuracy of the analysis by, for example, referring to the user's past moving data during analysis. For example, the analysis unit selects optimal candidates for medical institutions or educational institutions based on the user's past moving data. The analysis unit can also analyze the contents of government notifications from the user's past moving data. The analysis unit can also improve the accuracy of the analysis results by referring to the user's past moving data. This makes it possible to provide more accurate analysis results by improving the analysis accuracy based on the user's past moving data.

[0044] The analysis unit can customize the analysis results based on the user's family structure and age during analysis. The analysis unit customizes the analysis results based on the user's family structure and age during analysis, for example. For example, the analysis unit selects optimal candidates for medical institutions and educational institutions based on the user's family structure. The analysis unit can also provide information on appropriate medical institutions and educational institutions based on the user's age. The analysis unit can also customize the analysis results taking the user's family structure and age into consideration. This makes it possible to provide more appropriate information by providing analysis results that take the user's family structure and age into consideration.

[0045] The analysis unit can evaluate the reliability of the user's input content during analysis and reflect this in the analysis results. The analysis unit, for example, evaluates the reliability of the user's input content during analysis and reflects this in the analysis results. For example, the analysis unit evaluates whether the user's input content is accurate and provides a highly reliable analysis result. Furthermore, if there is an error in the user's input content, the analysis unit can suggest a correction and reflect this in the analysis results. Furthermore, the analysis unit can evaluate the reliability of the user's input content and improve the accuracy of the analysis results. In this way, by evaluating the reliability of the user's input content, it is possible to provide a more accurate analysis result.

[0046] The analysis unit can provide analysis results taking into account the user's geographical location information during analysis. For example, when analyzing, the analysis unit can provide analysis results taking into account the user's geographical location information. For example, if a user moves to a specific area, the analysis unit can provide information about medical institutions and educational institutions in that area. The analysis unit can also provide optimal government notification information based on the user's geographical location information. The analysis unit can also customize the analysis results taking into account the user's geographical location information. This makes it possible to provide more appropriate information by providing analysis results that take into account the user's geographical location information.

[0047] The analysis unit can analyze the user's social media activities during the analysis and provide related analysis results. For example, the analysis unit can provide information on related medical institutions or educational institutions based on the location where the user checked in on social media. The analysis unit can also analyze the content of the user's social media posts and provide related analysis results. The analysis unit can also provide related analysis results by referring to the activities of the user's friends on social media. This makes it possible to provide more appropriate information by providing related analysis results based on the user's social media activities.

[0048] The analysis unit can customize the analysis algorithm by reflecting the user's past feedback during analysis. The analysis unit, for example, customizes the analysis algorithm by reflecting the user's past feedback during analysis. For example, the analysis unit improves the analysis algorithm based on feedback provided by the user in the past. The analysis unit can also propose a highly accurate analysis algorithm based on the user's past feedback. The analysis unit can also customize the analysis algorithm by reflecting the user's past feedback. In this way, the analysis accuracy can be improved by customizing the analysis algorithm based on the user's past feedback.

[0049] The selection unit can improve the accuracy of selection when selecting candidates by referring to the user's past selection history. For example, the selection unit improves the accuracy of selection when selecting candidates by referring to the user's past selection history. For example, the selection unit selects the most suitable medical institution or educational institution candidate based on the user's past selection history. The selection unit can also select the details of notifications from government offices based on the user's past selection history. The selection unit can also improve the accuracy of selection by referring to the user's past selection history. In this way, by improving the accuracy of selection based on the user's past selection history, more appropriate candidates can be selected.

[0050] The selection unit can customize the candidates based on the user's family structure and age when selecting candidates. For example, the selection unit customizes the candidates based on the user's family structure and age when selecting candidates. For example, the selection unit selects optimal medical institution or educational institution candidates based on the user's family structure. The selection unit can also provide information on appropriate medical institutions or educational institutions based on the user's age. The selection unit can also customize the candidates taking the user's family structure and age into consideration. This makes it possible to provide more appropriate information by providing candidates that take the user's family structure and age into consideration.

[0051] The selection unit can evaluate the reliability of the user's input content when selecting candidates and reflect this in the selection result. For example, the selection unit evaluates the reliability of the user's input content when selecting candidates and reflects this in the selection result. For example, the selection unit evaluates whether the user's input content is accurate and provides a highly reliable selection result. Furthermore, if there is an error in the user's input content, the selection unit can suggest a correction and reflect this in the selection result. Furthermore, the selection unit can evaluate the reliability of the user's input content and improve the accuracy of the selection result. In this way, by evaluating the reliability of the user's input content, it is possible to provide a more accurate selection result.

[0052] The selection unit can provide candidates by taking into consideration the user's geographical location information when selecting candidates. For example, when selecting candidates, the selection unit provides candidates by taking into consideration the user's geographical location information. For example, if the user moves to a specific area, the selection unit provides candidates for medical institutions and educational institutions in that area. The selection unit can also provide optimal government notification information based on the user's geographical location information. The selection unit can also customize the candidates by taking into consideration the user's geographical location information. In this way, by providing candidates that take into consideration the user's geographical location information, more appropriate information can be provided.

[0053] The selection unit may analyze the user's social media activity when selecting candidates and provide relevant candidates. For example, the selection unit may analyze the user's social media activity when selecting candidates and provide relevant candidates. For example, the selection unit may provide relevant medical or educational institution candidates based on the location where the user checked in on social media. The selection unit may also analyze the content of the user's social media posts and provide relevant candidates. The selection unit may also provide relevant candidates based on the activity of the user's friends on social media. In this way, more appropriate information can be provided by providing relevant candidates based on the user's social media activity.

[0054] The selection unit can customize the selection algorithm by reflecting the user's past feedback when selecting candidates. For example, the selection unit customizes the selection algorithm by reflecting the user's past feedback when selecting candidates. For example, the selection unit improves the selection algorithm based on feedback provided by the user in the past. The selection unit can also propose a highly accurate selection algorithm based on the user's past feedback. The selection unit can also customize the selection algorithm by reflecting the user's past feedback. In this way, the selection accuracy can be improved by customizing the selection algorithm based on the user's past feedback.

[0055] The listing unit can improve the accuracy of the listing by referring to the user's past listing history when creating a list. The listing unit, for example, improves the accuracy of the listing by referring to the user's past listing history when creating a list. For example, the listing unit suggests an optimal listing method based on the user's past listing history. The listing unit can also automatically list related information from the user's past listing history. The listing unit can also improve the accuracy of the listing by referring to the user's past listing history. In this way, a more accurate list can be provided by improving the accuracy of the listing based on the user's past listing history.

[0056] The listing unit can customize the list based on the user's family structure and age when creating the list. The listing unit customizes the list based on the user's family structure and age when creating the list. For example, the listing unit suggests an optimal listing method based on the user's family structure. The listing unit can also provide an appropriate listing method based on the user's age. The listing unit can also customize the list taking the user's family structure and age into consideration. This makes it possible to provide more appropriate information by providing a list that takes the user's family structure and age into consideration.

[0057] The listing unit can evaluate the reliability of the user's input content when listing and reflect this in the listing result. The listing unit, for example, evaluates the reliability of the user's input content when listing and reflects this in the listing result. For example, the listing unit evaluates whether the user's input content is accurate and provides a highly reliable listing result. Furthermore, if there is an error in the user's input content, the listing unit can also suggest a correction and reflect this in the listing result. Furthermore, the listing unit can evaluate the reliability of the user's input content and improve the accuracy of the listing result. In this way, by evaluating the reliability of the user's input content, a more accurate listing result can be provided.

[0058] The listing unit can provide a list taking into consideration the user's geographical location information when creating a list. For example, when creating a list, the listing unit provides a list taking into consideration the user's geographical location information. For example, if a user moves to a specific area, the listing unit provides a list of medical institutions and educational institutions in that area. The listing unit can also provide optimal government notification information based on the user's geographical location information. The listing unit can also customize the list taking into consideration the user's geographical location information. In this way, by providing a list taking into consideration the user's geographical location information, more appropriate information can be provided.

[0059] The list creation unit can analyze the user's social media activity when creating a list and provide a related list. For example, the list creation unit can analyze the user's social media activity when creating a list and provide a related list. For example, the list creation unit can provide a list of related medical institutions or educational institutions based on the location where the user checked in on social media. The list creation unit can also analyze the content of the user's social media posts and provide a related list. The list creation unit can also provide a related list by referring to the activity of the user's friends on social media. In this way, by providing a related list based on the user's social media activity, more appropriate information can be provided.

[0060] The listing unit can customize the listing algorithm by reflecting the user's past feedback when creating a list. The listing unit, for example, customizes the listing algorithm by reflecting the user's past feedback when creating a list. For example, the listing unit improves the listing algorithm based on feedback provided by the user in the past. The listing unit can also propose a highly accurate listing algorithm based on the user's past feedback. The listing unit can also customize the listing algorithm by reflecting the user's past feedback. In this way, the listing accuracy can be improved by customizing the listing algorithm based on the user's past feedback.

[0061] The management unit can improve management accuracy by referring to the user's past management history during management. The management unit, for example, improves management accuracy by referring to the user's past management history during management. For example, the management unit proposes an optimal management method based on the user's past management history. The management unit can also automatically manage related information from the user's past management history. The management unit can also improve management accuracy by referring to the user's past management history. In this way, more accurate management can be provided by improving management accuracy based on the user's past management history.

[0062] The management unit can customize the management content based on the user's family structure and age during management. The management unit, for example, customizes the management content based on the user's family structure and age during management. For example, the management unit suggests an optimal management method based on the user's family structure. The management unit can also provide an appropriate management method based on the user's age. The management unit can also customize the management content taking the user's family structure and age into consideration. This makes it possible to provide more appropriate information by providing management content that takes the user's family structure and age into consideration.

[0063] The management unit can evaluate the reliability of the user's input content during management and reflect this in the management results. For example, the management unit evaluates the reliability of the user's input content during management and reflects this in the management results. For example, the management unit evaluates whether the user's input content is accurate and provides highly reliable management results. Furthermore, if there is an error in the user's input content, the management unit can suggest a correction and reflect this in the management results. Furthermore, the management unit can evaluate the reliability of the user's input content and improve the accuracy of the management results. In this way, by evaluating the reliability of the user's input content, more accurate management results can be provided.

[0064] The management unit can provide management content taking into account the user's geographical location information during management. For example, the management unit provides management content taking into account the user's geographical location information during management. For example, if a user moves to a specific area, the management unit provides management content for medical institutions and educational institutions in that area. The management unit can also provide optimal government notification information based on the user's geographical location information. The management unit can also customize management content taking into account the user's geographical location information. In this way, by providing management content taking into account the user's geographical location information, more appropriate information can be provided.

[0065] The management unit can analyze the user's social media activities during management and provide related management content. For example, the management unit can analyze the user's social media activities during management and provide related management content. For example, the management unit can provide management content of related medical institutions or educational institutions based on the location where the user checked in on social media. The management unit can also analyze the content posted by the user on social media and provide related management content. The management unit can also provide related management content by referring to the activities of the user's friends on social media. In this way, by providing related management content based on the user's social media activity, more appropriate information can be provided.

[0066] The management unit can customize the management algorithm by reflecting the user's past feedback during management. The management unit, for example, customizes the management algorithm by reflecting the user's past feedback during management. For example, the management unit improves the management algorithm based on feedback provided by the user in the past. The management unit can also propose a highly accurate management algorithm based on the user's past feedback. The management unit can also customize the management algorithm by reflecting the user's past feedback. In this way, customizing the management algorithm based on the user's past feedback can improve management accuracy.

[0067] The subsidy display unit can improve display accuracy by referring to the user's past subsidy application history when displaying subsidies. The subsidy display unit can improve display accuracy by referring to the user's past subsidy application history when displaying subsidies. For example, the subsidy display unit displays optimal subsidy information based on the user's past subsidy application history. The subsidy display unit can also automatically display related subsidy information from the user's past subsidy application history. The subsidy display unit can also improve display accuracy by referring to the user's past subsidy application history. This makes it possible to provide more accurate subsidy information by improving display accuracy based on the user's past subsidy application history.

[0068] The subsidy display unit can customize the subsidy information based on the user's family structure and age when displaying the subsidy. The subsidy display unit customizes the subsidy information based on the user's family structure and age when displaying the subsidy. For example, the subsidy display unit displays optimal subsidy information based on the user's family structure. The subsidy display unit can also provide appropriate subsidy information based on the user's age. The subsidy display unit can also customize the subsidy information taking into account the user's family structure and age. This makes it possible to provide more appropriate information by providing subsidy information that takes into account the user's family structure and age.

[0069] The subsidy display unit can evaluate the reliability of the user's input content when displaying the subsidy and reflect it in the display result. The subsidy display unit, for example, evaluates the reliability of the user's input content when displaying the subsidy and reflects it in the display result. For example, the subsidy display unit evaluates whether the user's input content is accurate and displays highly reliable subsidy information. Furthermore, if there is an error in the user's input content, the subsidy display unit can also suggest a correction and reflect it in the display result. Furthermore, the subsidy display unit can evaluate the reliability of the user's input content and improve the accuracy of the display result. In this way, by evaluating the reliability of the user's input content, more accurate subsidy information can be provided.

[0070] The subsidy display unit can provide subsidy information taking into account the user's geographical location information when displaying subsidies. For example, the subsidy display unit provides subsidy information taking into account the user's geographical location information when displaying subsidies. For example, if the user moves to a specific area, the subsidy display unit provides subsidy information for that area. The subsidy display unit can also provide optimal subsidy information based on the user's geographical location information. The subsidy display unit can also customize the subsidy information taking into account the user's geographical location information. This makes it possible to provide more appropriate information by providing subsidy information taking into account the user's geographical location information.

[0071] The subsidy display unit may analyze the user's social media activity and provide related subsidy information when displaying subsidies. For example, the subsidy display unit may analyze the user's social media activity and provide related subsidy information when displaying subsidies. For example, the subsidy display unit may provide related subsidy information based on the location where the user checked in on social media. The subsidy display unit may also analyze the content of the user's social media posts and provide related subsidy information. The subsidy display unit may also provide related subsidy information with reference to the activities of the user's friends on social media. This allows for more appropriate information to be provided by providing related subsidy information based on the user's social media activity.

[0072] The subsidy display unit can customize the display algorithm by reflecting the user's past feedback when displaying the subsidy. For example, the subsidy display unit customizes the display algorithm by reflecting the user's past feedback when displaying the subsidy. For example, the subsidy display unit improves the display algorithm based on feedback provided by the user in the past. The subsidy display unit can also suggest a highly accurate display algorithm based on the user's past feedback. The subsidy display unit can also customize the display algorithm by reflecting the user's past feedback. In this way, display accuracy can be improved by customizing the display algorithm based on the user's past feedback.

[0073] The estimating unit can improve the accuracy of the estimate by referring to the user's past estimate history when making an estimate. The estimating unit, for example, improves the accuracy of the estimate by referring to the user's past estimate history when making an estimate. For example, the estimating unit suggests an optimal estimation method based on the user's past estimate history. The estimating unit can also automatically estimate related information from the user's past estimate history. The estimating unit can also improve the accuracy of the estimate by referring to the user's past estimate history. In this way, by improving the accuracy of the estimate based on the user's past estimate history, it is possible to provide a more accurate estimate.

[0074] The estimation unit can customize the estimate content based on the user's family structure and age at the time of estimation. The estimation unit customizes the estimate content based on the user's family structure and age, for example, at the time of estimation. For example, the estimation unit suggests an optimal estimation method based on the user's family structure. The estimation unit can also provide an appropriate estimation method based on the user's age. The estimation unit can also customize the estimate content taking the user's family structure and age into consideration. This makes it possible to provide more appropriate information by providing estimate content that takes the user's family structure and age into consideration.

[0075] The estimation unit can evaluate the reliability of the user's input content at the time of estimation and reflect it in the estimation result. The estimation unit, for example, evaluates the reliability of the user's input content at the time of estimation and reflects it in the estimation result. For example, the estimation unit evaluates whether the user's input content is accurate and provides a highly reliable estimation result. Furthermore, if there is an error in the user's input content, the estimation unit can suggest a correction and reflect it in the estimation result. Furthermore, the estimation unit can evaluate the reliability of the user's input content and improve the accuracy of the estimation result. In this way, by evaluating the reliability of the user's input content, a more accurate estimation result can be provided.

[0076] The estimation unit can provide estimate contents taking into account the user's geographical location information when providing an estimate. For example, the estimation unit provides estimate contents taking into account the user's geographical location information when providing an estimate. For example, if the user is moving to a specific area, the estimation unit provides estimate contents for that area. The estimation unit can also provide optimal estimate contents based on the user's geographical location information. The estimation unit can also customize the estimate contents taking into account the user's geographical location information. In this way, by providing estimate contents taking into account the user's geographical location information, more appropriate information can be provided.

[0077] The estimation unit can analyze the user's social media activity at the time of estimation and provide related estimate content. The estimation unit, for example, analyzes the user's social media activity at the time of estimation and provides related estimate content. For example, the estimation unit can provide related estimate content based on the location where the user checked in on social media. The estimation unit can also analyze the content of the user's social media posts and provide related estimate content. The estimation unit can also provide related estimate content by referring to the activity of the user's friends on social media. In this way, by providing related estimate content based on the user's social media activity, more appropriate information can be provided.

[0078] The estimation unit can customize the estimation algorithm by reflecting the user's past feedback when making an estimate. The estimation unit, for example, customizes the estimation algorithm by reflecting the user's past feedback when making an estimate. For example, the estimation unit improves the estimation algorithm based on feedback provided by the user in the past. The estimation unit can also propose a highly accurate estimation algorithm based on the user's past feedback. The estimation unit can also customize the estimation algorithm by reflecting the user's past feedback. In this way, the estimation accuracy can be improved by customizing the estimation algorithm based on the user's past feedback.

[0079] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0080] The moving information management system may further include a health management unit that monitors the user's health condition. For example, the health management unit may collect the user's health data and evaluate the impact of the stress of moving on the user's health. The health management unit may also adjust the moving schedule based on the user's health condition. Furthermore, the health management unit may provide the user with advice on maintaining their health. This may make it easier for the user to maintain their health during the move.

[0081] The moving information management system may further include a pet management unit that manages information about the user's pet. For example, the pet management unit may record the type and health status of the user's pet and suggest pet-friendly facilities at the new location. The pet management unit may also list the procedures and documents required for moving a pet. Furthermore, the pet management unit may provide advice on reducing stress for pets. This allows the user to move their pet smoothly.

[0082] The moving information management system can further include a leisure suggestion unit that suggests leisure facilities in the new destination based on the user's hobbies and interests. For example, the leisure suggestion unit analyzes the user's hobbies and interests and creates a list of recommended leisure facilities in the new destination. The leisure suggestion unit can also plan leisure activities according to the user's schedule. Furthermore, the leisure suggestion unit can provide the user with discount information on leisure facilities. This allows the user to enjoy life in the new destination.

[0083] The moving information management system can further include an aftercare section that supports the user's life after moving. For example, the aftercare section provides information about the local community after moving. The aftercare section can also guide the user to procedures and services necessary for life after moving. Furthermore, the aftercare section can also provide advice regarding life after moving. This allows the user to smoothly start life after moving.

[0084] The moving information management system may further include an environmental assessment unit that evaluates the environmental impact of a user's move and proposes an environmentally friendly moving plan. For example, the environmental assessment unit may calculate the carbon dioxide emissions associated with the move and propose an environmentally friendly moving method. The environmental assessment unit may also recommend the use of recyclable packaging materials. Furthermore, the environmental assessment unit may also provide guidance on how to dispose of waste associated with the move. This allows the user to move in an environmentally friendly manner.

[0085] The processing flow of the first embodiment will be briefly explained below.

[0086] Step 1: The reception unit receives information from the user about the moving company, notifications to the government office, and family composition. For example, the reception unit receives information from the user such as the departure and destination points, the number and ages of family members, and the details of notifications to the government office. Step 2: The analysis unit analyzes the information received by the reception unit. For example, the analysis unit analyzes the information input by the user using a data analysis method or algorithm. Step 3: The selection unit selects candidates for medical institutions and educational institutions based on the information analyzed by the analysis unit. For example, the selection unit displays information on nearby hospitals and schools. Step 4: The listing unit displays the candidates selected by the selection unit to the user, and the user selects and lists the information they need. For example, the listing unit allows the user to select and list the information they need from the displayed candidates. Step 5: The management section manages expenses and tasks based on the information listed by the listing section. For example, the management section displays a list of expenses and tasks for necessary procedures for moving. Step 6: The subsidy display unit displays a list of subsidy programs related to relocation based on the information managed by the management unit. For example, the subsidy display unit displays information on subsidies and grants related to relocation. Step 7: The quotation unit acts as a bulk quotation site based on the information displayed by the subsidy display unit. For example, the quotation unit receives a commission from each contractor selected by the user.

[0087] (Example 2) A moving information management system according to an embodiment of the present invention accepts and analyzes information on moving companies, government notifications, and family structure from a user, selects candidate medical institutions, and displays the information to the user. Based on the information entered by the user, the moving information management system creates a list of necessary information, manages expenses and tasks, and displays a list of relocation subsidy programs. The moving information management system also functions as a bulk quote site, receiving fees from each selected company. For example, the moving information management system allows a user to input information such as the moving company, government notifications, and family structure. The user inputs information such as the departure and destination points, the number and ages of family members, and the details of the notification to the government. This information is entered into the system's input section. The moving information management system then analyzes the input information and selects candidate medical institutions and educational institutions in the area. For example, it displays information on nearby hospitals and schools. The user can select the necessary information from the displayed candidates and create a list. Furthermore, the moving information management system also manages expenses and tasks. For example, it displays a list of moving expenses and necessary procedures. This allows users to grasp the costs and tasks involved in moving at a glance. The moving information management system also displays a list of subsidy programs related to moving. For example, it displays information on subsidies and grants related to moving. Users can select applicable subsidies from the displayed list and apply for them. Finally, the moving information management system also functions as a bulk quote site. The system's operating costs are covered by receiving fees from each company selected by the user. For example, fees can be received from moving companies and government processing agents. This allows users to centrally manage moving information and efficiently proceed with the moving process. The moving information management system allows users to centrally manage moving information and efficiently proceed with the moving process. For example, this single tool can manage all moving-related information, including selecting a moving company, submitting notifications to government offices, selecting candidate medical and educational institutions, managing costs and tasks, and displaying a list of subsidy programs.

[0088] A moving information management system according to an embodiment includes a reception unit, an analysis unit, a selection unit, a listing unit, a management unit, a subsidy display unit, and an estimate unit. The reception unit receives information from a user about a moving company, notifications to government offices, and family composition. For example, the reception unit receives information from the user, such as the departure and destination points, the number and ages of family members, and the details of notifications to government offices. The analysis unit analyzes the information received by the reception unit. For example, the analysis unit analyzes information input by the user using a data analysis method or algorithm. The selection unit selects candidate medical institutions or educational institutions based on the information analyzed by the analysis unit. For example, the selection unit displays information about nearby hospitals and schools. The listing unit displays the candidates selected by the selection unit to the user, allowing the user to select and list the information they need. For example, the listing unit selects and lists the information they need from the displayed candidates. The management unit manages expenses and tasks based on the information listed by the listing unit. For example, the management unit displays a list of moving expenses and necessary procedure tasks. The subsidy display unit displays a list of subsidy programs related to relocation based on the information managed by the management unit. For example, the subsidy display unit displays information on subsidies and grants associated with moving. The estimate unit acts as a bulk estimate site based on the information displayed by the subsidy display unit. For example, the estimate unit receives a fee from each contractor selected by the user. As a result, the moving information management system according to the embodiment allows users to centrally manage information related to moving and efficiently proceed with the moving process.

[0089] The reception unit can accept information from the user, such as the departure point and destination, the number and ages of family members, and details of notifications submitted to government offices. The reception unit, for example, accepts information on the departure point and destination from the user. For example, the reception unit accepts information such as the address, region, and country entered by the user. The reception unit can also accept information on the number and ages of family members. For example, the reception unit accepts information on the ages and specific needs of each family member. Furthermore, the reception unit can also accept information on details of notifications submitted to government offices. For example, the reception unit accepts information such as a change of address notification, a change of resident registration, and tax-related notifications. By accepting detailed information from the user, more accurate analysis and selection becomes possible.

[0090] The analysis unit can analyze the information received by the reception unit and select candidate medical institutions and educational institutions in the area. The analysis unit analyzes the information received by the reception unit, for example, using data analysis methods and algorithms. For example, the analysis unit selects candidate medical institutions and educational institutions suitable for the area based on information input by the user. The analysis unit can also select candidate medical institutions and educational institutions based on evaluation criteria and a selection process. For example, the analysis unit displays information on nearby hospitals and schools. This makes it possible to select candidate medical institutions and educational institutions suitable for the area.

[0091] The selection unit can display information about hospitals or schools. The selection unit displays, for example, information about nearby hospitals and schools. For example, the selection unit displays information such as the location of the hospital, the services it offers, and reviews. The selection unit can also display information such as the location of the school, the educational programs it offers, and reviews. This makes it possible to provide information about medical institutions and educational institutions that are convenient for the user.

[0092] The listing unit allows the user to select necessary information from the displayed candidates and create a list. The listing unit, for example, allows the user to select necessary information from the displayed candidates and create a list. For example, the listing unit lists the information selected by the user based on the list format and the method of organizing the information. The listing unit can also provide tools and functions for efficiently listing the information selected by the user. This allows the user to efficiently list the information they need.

[0093] The management unit can display a list of costs or procedural tasks required for moving. For example, the management unit displays a list of costs or procedural tasks required for moving. For example, the management unit displays costs and tasks required for moving based on a breakdown of costs and procedural steps. The management unit can also display the costs and tasks required for moving in a visually easy-to-understand format so that the user can grasp the costs and tasks required for moving at a glance. This allows the user to grasp the costs and tasks required for moving at a glance.

[0094] The subsidy display unit can display information about subsidies and grants associated with moving. The subsidy display unit displays, for example, information about subsidies and grants associated with moving. For example, the subsidy display unit displays information about subsidies and grants based on the type of subsidy eligible and application conditions. The subsidy display unit can also display information about available subsidies and grants in a visually easy-to-understand format so that the user can easily check the information about available subsidies and grants. This allows the user to easily check the information about available subsidies and grants.

[0095] The estimating unit can receive fees from each provider selected by the user. For example, the estimating unit receives fees from each provider selected by the user. For example, the estimating unit receives fees from each provider based on a breakdown of fees and payment method. The estimating unit can also receive fees from each selected provider to cover the operating costs of the system. This makes it possible to cover the operating costs of the system.

[0096] The reception unit can estimate the user's emotion and adjust the design of the input interface based on the estimated user's emotion. The reception unit, for example, estimates the user's emotion and adjusts the design of the input interface based on the estimated user's emotion. For example, if the user is feeling stressed, the reception unit can provide a simple interface and minimize input steps. Furthermore, if the user is relaxed, the reception unit can provide detailed input options and suggest a customizable input method. Furthermore, if the user is in a hurry, the reception unit can prioritize voice input to enable quick information input. In this way, an optimal input interface can be provided according to the user's emotion.

[0097] The reception unit can reference the user's past moving history and automatically complete input items. The reception unit, for example, references the user's past moving history and automatically completes input items. For example, the reception unit automatically completes notification details previously entered by the user to a moving company or government office. The reception unit can also automatically complete family composition and ages from the user's past moving history. The reception unit can also automatically complete address information previously entered by the user. This makes it possible to streamline input work by automatically completing input items based on the user's past moving history.

[0098] The reception unit can suggest related additional information in real time based on the user's input. The reception unit suggests related additional information in real time based on the user's input, for example. For example, when the user inputs a moving company, the reception unit suggests related government notification information. Furthermore, when the user inputs family composition, the reception unit can also suggest information on related medical institutions and educational institutions. Furthermore, when the user inputs a destination, the reception unit can suggest related local subsidy programs. In this way, by suggesting related information in real time based on the user's input, convenience for the user can be improved.

[0099] The reception unit can provide the optimum input means according to the user's input method. For example, the reception unit provides the optimum input means according to the user's input method (voice, text, image, etc.). For example, if the user selects voice input, the reception unit inputs information using voice recognition technology. Also, if the user selects text input, the reception unit can input information using a keyboard or touch panel. Also, if the user selects image input, the reception unit can input information using image recognition technology. In this way, by providing the optimum input means according to the user's input method, it is possible to make input work more efficient.

[0100] The reception unit can estimate the user's emotion and adjust the priority of input items based on the estimated user's emotion. The reception unit, for example, estimates the user's emotion and adjusts the priority of input items based on the estimated user's emotion. For example, when the user is feeling stressed, the reception unit can preferentially display important input items. Furthermore, when the user is relaxed, the reception unit can also display detailed input items. Furthermore, when the user is in a hurry, the reception unit can also display the minimum number of input items. This makes it possible to provide optimal priorities of input items according to the user's emotion.

[0101] The reception unit can add region-specific input items taking into account the user's geographical location information. The reception unit can add region-specific input items taking into account the user's geographical location information, for example. For example, when a user moves to a specific region, the reception unit can add notification information from local government offices that is specific to that region. Furthermore, when a user moves to a specific region, the reception unit can also add information about medical institutions and educational institutions that are specific to that region. Furthermore, when a user moves to a specific region, the reception unit can also add information about subsidy programs that are specific to that region. This can make input work more efficient by providing region-specific input items that take into account the user's geographical location information.

[0102] The reception unit can analyze the user's social media activity and suggest related input items. The reception unit, for example, analyzes the user's social media activity and suggests related input items. For example, the reception unit can suggest related input items based on the location where the user checked in on social media. The reception unit can also analyze the content of the user's social media posts and suggest related input items. The reception unit can also suggest related input items by taking into account the activities of the user's friends on social media. This makes it possible to make input work more efficient by suggesting related input items based on the user's social media activity.

[0103] The reception unit can customize the input interface by reflecting the user's past feedback. The reception unit customizes the input interface by reflecting the user's past feedback, for example. For example, the reception unit improves the input interface based on feedback provided by the user in the past. The reception unit can also suggest an easy-to-use input interface based on the user's past feedback. The reception unit can also adjust the design of the input interface by reflecting the user's past feedback. In this way, the input interface can be customized based on the user's past feedback, thereby improving user convenience.

[0104] The analysis unit can estimate the user's emotions and adjust the analysis algorithm based on the estimated user's emotions. The analysis unit, for example, estimates the user's emotions and adjusts the analysis algorithm based on the estimated user's emotions. For example, if the user is feeling stressed, the analysis unit can simplify the analysis algorithm and provide results quickly. Also, if the user is relaxed, the analysis unit can perform a detailed analysis and provide highly accurate results. Also, if the user is in a hurry, the analysis unit can speed up the analysis algorithm and provide results quickly. This makes it possible to provide an optimal analysis algorithm according to the user's emotions.

[0105] The analysis unit can improve the accuracy of the analysis by referring to the user's past moving data during analysis. The analysis unit can improve the accuracy of the analysis by, for example, referring to the user's past moving data during analysis. For example, the analysis unit selects optimal candidates for medical institutions or educational institutions based on the user's past moving data. The analysis unit can also analyze the contents of government notifications from the user's past moving data. The analysis unit can also improve the accuracy of the analysis results by referring to the user's past moving data. This makes it possible to provide more accurate analysis results by improving the analysis accuracy based on the user's past moving data.

[0106] The analysis unit can customize the analysis results based on the user's family structure and age during analysis. The analysis unit customizes the analysis results based on the user's family structure and age during analysis, for example. For example, the analysis unit selects optimal candidates for medical institutions and educational institutions based on the user's family structure. The analysis unit can also provide information on appropriate medical institutions and educational institutions based on the user's age. The analysis unit can also customize the analysis results taking the user's family structure and age into consideration. This makes it possible to provide more appropriate information by providing analysis results that take the user's family structure and age into consideration.

[0107] The analysis unit can evaluate the reliability of the user's input content during analysis and reflect this in the analysis results. The analysis unit, for example, evaluates the reliability of the user's input content during analysis and reflects this in the analysis results. For example, the analysis unit evaluates whether the user's input content is accurate and provides a highly reliable analysis result. Furthermore, if there is an error in the user's input content, the analysis unit can suggest a correction and reflect this in the analysis results. Furthermore, the analysis unit can evaluate the reliability of the user's input content and improve the accuracy of the analysis results. In this way, by evaluating the reliability of the user's input content, it is possible to provide a more accurate analysis result.

[0108] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the estimated user emotions. The analysis unit, for example, estimates the user's emotions and adjusts the display method of the analysis results based on the estimated user emotions. For example, if the user is feeling stressed, the analysis unit provides a simple, highly visible display method. Furthermore, if the user is relaxed, the analysis unit can provide a display method that includes detailed information. Furthermore, if the user is in a hurry, the analysis unit can provide a display method that focuses on the main points. In this way, by providing an optimal display method according to the user's emotions, it is possible to help the user understand the analysis results.

[0109] The analysis unit can provide analysis results taking into account the user's geographical location information during analysis. For example, when analyzing, the analysis unit can provide analysis results taking into account the user's geographical location information. For example, if a user moves to a specific area, the analysis unit can provide information about medical institutions and educational institutions in that area. The analysis unit can also provide optimal government notification information based on the user's geographical location information. The analysis unit can also customize the analysis results taking into account the user's geographical location information. This makes it possible to provide more appropriate information by providing analysis results that take into account the user's geographical location information.

[0110] The analysis unit can analyze the user's social media activities during the analysis and provide related analysis results. For example, the analysis unit can provide information on related medical institutions or educational institutions based on the location where the user checked in on social media. The analysis unit can also analyze the content of the user's social media posts and provide related analysis results. The analysis unit can also provide related analysis results by referring to the activities of the user's friends on social media. This makes it possible to provide more appropriate information by providing related analysis results based on the user's social media activities.

[0111] The analysis unit can customize the analysis algorithm by reflecting the user's past feedback during analysis. The analysis unit, for example, customizes the analysis algorithm by reflecting the user's past feedback during analysis. For example, the analysis unit improves the analysis algorithm based on feedback provided by the user in the past. The analysis unit can also propose a highly accurate analysis algorithm based on the user's past feedback. The analysis unit can also customize the analysis algorithm by reflecting the user's past feedback. In this way, the analysis accuracy can be improved by customizing the analysis algorithm based on the user's past feedback.

[0112] The selection unit can estimate the user's emotion and adjust the candidate selection criteria based on the estimated user's emotion. The selection unit, for example, estimates the user's emotion and adjusts the candidate selection criteria based on the estimated user's emotion. For example, the selection unit selects candidates using simple criteria when the user is stressed. The selection unit can also select candidates using detailed criteria when the user is relaxed. The selection unit can also apply criteria for quickly selecting candidates when the user is in a hurry. This allows more appropriate candidates to be selected by providing optimal candidate selection criteria according to the user's emotion.

[0113] The selection unit can improve the accuracy of selection when selecting candidates by referring to the user's past selection history. For example, the selection unit improves the accuracy of selection when selecting candidates by referring to the user's past selection history. For example, the selection unit selects the most suitable medical institution or educational institution candidate based on the user's past selection history. The selection unit can also select the details of notifications from government offices based on the user's past selection history. The selection unit can also improve the accuracy of selection by referring to the user's past selection history. In this way, by improving the accuracy of selection based on the user's past selection history, more appropriate candidates can be selected.

[0114] The selection unit can customize the candidates based on the user's family structure and age when selecting candidates. For example, the selection unit customizes the candidates based on the user's family structure and age when selecting candidates. For example, the selection unit selects optimal medical institution or educational institution candidates based on the user's family structure. The selection unit can also provide information on appropriate medical institutions or educational institutions based on the user's age. The selection unit can also customize the candidates taking the user's family structure and age into consideration. This makes it possible to provide more appropriate information by providing candidates that take the user's family structure and age into consideration.

[0115] The selection unit can evaluate the reliability of the user's input content when selecting candidates and reflect this in the selection result. For example, the selection unit evaluates the reliability of the user's input content when selecting candidates and reflects this in the selection result. For example, the selection unit evaluates whether the user's input content is accurate and provides a highly reliable selection result. Furthermore, if there is an error in the user's input content, the selection unit can suggest a correction and reflect this in the selection result. Furthermore, the selection unit can evaluate the reliability of the user's input content and improve the accuracy of the selection result. In this way, by evaluating the reliability of the user's input content, it is possible to provide a more accurate selection result.

[0116] The selection unit can estimate the user's emotion and adjust the display method of the candidates based on the estimated user's emotion. The selection unit, for example, estimates the user's emotion and adjusts the display method of the candidates based on the estimated user's emotion. For example, if the user is feeling stressed, the selection unit provides a simple, highly visible display method. Furthermore, if the user is relaxed, the selection unit can provide a display method including detailed information. Furthermore, if the user is in a hurry, the selection unit can provide a display method that focuses on the main points. In this way, by providing an optimal display method according to the user's emotion, it is possible to help the user understand the candidates.

[0117] The selection unit can provide candidates by taking into consideration the user's geographical location information when selecting candidates. For example, when selecting candidates, the selection unit provides candidates by taking into consideration the user's geographical location information. For example, if the user moves to a specific area, the selection unit provides candidates for medical institutions and educational institutions in that area. The selection unit can also provide optimal government notification information based on the user's geographical location information. The selection unit can also customize the candidates by taking into consideration the user's geographical location information. In this way, by providing candidates that take into consideration the user's geographical location information, more appropriate information can be provided.

[0118] The selection unit may analyze the user's social media activity when selecting candidates and provide relevant candidates. For example, the selection unit may analyze the user's social media activity when selecting candidates and provide relevant candidates. For example, the selection unit may provide relevant medical or educational institution candidates based on the location where the user checked in on social media. The selection unit may also analyze the content of the user's social media posts and provide relevant candidates. The selection unit may also provide relevant candidates based on the activity of the user's friends on social media. In this way, more appropriate information can be provided by providing relevant candidates based on the user's social media activity.

[0119] The selection unit can customize the selection algorithm by reflecting the user's past feedback when selecting candidates. For example, the selection unit customizes the selection algorithm by reflecting the user's past feedback when selecting candidates. For example, the selection unit improves the selection algorithm based on feedback provided by the user in the past. The selection unit can also propose a highly accurate selection algorithm based on the user's past feedback. The selection unit can also customize the selection algorithm by reflecting the user's past feedback. In this way, the selection accuracy can be improved by customizing the selection algorithm based on the user's past feedback.

[0120] The listing unit can estimate the user's emotions and adjust the listing method based on the estimated user's emotions. The listing unit, for example, estimates the user's emotions and adjusts the listing method based on the estimated user's emotions. For example, the listing unit provides a simple listing method when the user is feeling stressed. Furthermore, the listing unit can also provide a detailed listing method when the user is relaxed. Furthermore, the listing unit can also provide a method that allows for quick listing when the user is in a hurry. In this way, the listing work can be made more efficient by providing an optimal listing method according to the user's emotions.

[0121] The listing unit can improve the accuracy of the listing by referring to the user's past listing history when creating a list. The listing unit, for example, improves the accuracy of the listing by referring to the user's past listing history when creating a list. For example, the listing unit suggests an optimal listing method based on the user's past listing history. The listing unit can also automatically list related information from the user's past listing history. The listing unit can also improve the accuracy of the listing by referring to the user's past listing history. In this way, a more accurate list can be provided by improving the accuracy of the listing based on the user's past listing history.

[0122] The listing unit can customize the list based on the user's family structure and age when creating the list. The listing unit customizes the list based on the user's family structure and age when creating the list. For example, the listing unit suggests an optimal listing method based on the user's family structure. The listing unit can also provide an appropriate listing method based on the user's age. The listing unit can also customize the list taking the user's family structure and age into consideration. This makes it possible to provide more appropriate information by providing a list that takes the user's family structure and age into consideration.

[0123] The listing unit can evaluate the reliability of the user's input content when listing and reflect this in the listing result. The listing unit, for example, evaluates the reliability of the user's input content when listing and reflects this in the listing result. For example, the listing unit evaluates whether the user's input content is accurate and provides a highly reliable listing result. Furthermore, if there is an error in the user's input content, the listing unit can also suggest a correction and reflect this in the listing result. Furthermore, the listing unit can evaluate the reliability of the user's input content and improve the accuracy of the listing result. In this way, by evaluating the reliability of the user's input content, a more accurate listing result can be provided.

[0124] The list creation unit can estimate the user's emotions and adjust the display method of the list based on the estimated user's emotions. The list creation unit, for example, estimates the user's emotions and adjusts the display method of the list based on the estimated user's emotions. For example, when the user is feeling stressed, the list creation unit provides a simple, highly visible display method. Furthermore, when the user is relaxed, the list creation unit can also provide a display method including detailed information. Furthermore, when the user is in a hurry, the list creation unit can also provide a display method that focuses on the main points. In this way, by providing an optimal display method according to the user's emotions, it is possible to help the user understand the list.

[0125] The listing unit can provide a list taking into consideration the user's geographical location information when creating a list. For example, when creating a list, the listing unit provides a list taking into consideration the user's geographical location information. For example, if a user moves to a specific area, the listing unit provides a list of medical institutions and educational institutions in that area. The listing unit can also provide optimal government notification information based on the user's geographical location information. The listing unit can also customize the list taking into consideration the user's geographical location information. In this way, by providing a list taking into consideration the user's geographical location information, more appropriate information can be provided.

[0126] The list creation unit can analyze the user's social media activity when creating a list and provide a related list. For example, the list creation unit can analyze the user's social media activity when creating a list and provide a related list. For example, the list creation unit can provide a list of related medical institutions or educational institutions based on the location where the user checked in on social media. The list creation unit can also analyze the content of the user's social media posts and provide a related list. The list creation unit can also provide a related list by referring to the activity of the user's friends on social media. In this way, by providing a related list based on the user's social media activity, more appropriate information can be provided.

[0127] The listing unit can customize the listing algorithm by reflecting the user's past feedback when creating a list. The listing unit, for example, customizes the listing algorithm by reflecting the user's past feedback when creating a list. For example, the listing unit improves the listing algorithm based on feedback provided by the user in the past. The listing unit can also propose a highly accurate listing algorithm based on the user's past feedback. The listing unit can also customize the listing algorithm by reflecting the user's past feedback. In this way, the listing accuracy can be improved by customizing the listing algorithm based on the user's past feedback.

[0128] The management unit can estimate the user's emotions and adjust the expense and task management methods based on the estimated user emotions. The management unit, for example, estimates the user's emotions and adjusts the expense and task management methods based on the estimated user emotions. For example, the management unit can provide a simple management method when the user is feeling stressed. The management unit can also provide a detailed management method when the user is relaxed. The management unit can also provide a method that allows for quick management when the user is in a hurry. In this way, the management work can be made more efficient by providing the optimal management method according to the user's emotions.

[0129] The management unit can improve management accuracy by referring to the user's past management history during management. The management unit, for example, improves management accuracy by referring to the user's past management history during management. For example, the management unit proposes an optimal management method based on the user's past management history. The management unit can also automatically manage related information from the user's past management history. The management unit can also improve management accuracy by referring to the user's past management history. In this way, more accurate management can be provided by improving management accuracy based on the user's past management history.

[0130] The management unit can customize the management content based on the user's family structure and age during management. The management unit, for example, customizes the management content based on the user's family structure and age during management. For example, the management unit suggests an optimal management method based on the user's family structure. The management unit can also provide an appropriate management method based on the user's age. The management unit can also customize the management content taking the user's family structure and age into consideration. This makes it possible to provide more appropriate information by providing management content that takes the user's family structure and age into consideration.

[0131] The management unit can evaluate the reliability of the user's input content during management and reflect this in the management results. For example, the management unit evaluates the reliability of the user's input content during management and reflects this in the management results. For example, the management unit evaluates whether the user's input content is accurate and provides highly reliable management results. Furthermore, if there is an error in the user's input content, the management unit can suggest a correction and reflect this in the management results. Furthermore, the management unit can evaluate the reliability of the user's input content and improve the accuracy of the management results. In this way, by evaluating the reliability of the user's input content, more accurate management results can be provided.

[0132] The management unit can estimate the user's emotions and adjust the display method of the management results based on the estimated user emotions. The management unit, for example, estimates the user's emotions and adjusts the display method of the management results based on the estimated user emotions. For example, if the user is feeling stressed, the management unit provides a simple, highly visible display method. Furthermore, if the user is relaxed, the management unit can provide a display method that includes detailed information. Furthermore, if the user is in a hurry, the management unit can provide a display method that focuses on the main points. In this way, by providing the optimal display method according to the user's emotions, it is possible to help the user understand the management results.

[0133] The management unit can provide management content taking into account the user's geographical location information during management. For example, the management unit provides management content taking into account the user's geographical location information during management. For example, if a user moves to a specific area, the management unit provides management content for medical institutions and educational institutions in that area. The management unit can also provide optimal government notification information based on the user's geographical location information. The management unit can also customize management content taking into account the user's geographical location information. In this way, by providing management content taking into account the user's geographical location information, more appropriate information can be provided.

[0134] The management unit can analyze the user's social media activities during management and provide related management content. For example, the management unit can analyze the user's social media activities during management and provide related management content. For example, the management unit can provide management content of related medical institutions or educational institutions based on the location where the user checked in on social media. The management unit can also analyze the content posted by the user on social media and provide related management content. The management unit can also provide related management content by referring to the activities of the user's friends on social media. In this way, by providing related management content based on the user's social media activity, more appropriate information can be provided.

[0135] The management unit can customize the management algorithm by reflecting the user's past feedback during management. The management unit, for example, customizes the management algorithm by reflecting the user's past feedback during management. For example, the management unit improves the management algorithm based on feedback provided by the user in the past. The management unit can also propose a highly accurate management algorithm based on the user's past feedback. The management unit can also customize the management algorithm by reflecting the user's past feedback. In this way, customizing the management algorithm based on the user's past feedback can improve management accuracy.

[0136] The subsidy display unit can estimate the user's emotions and adjust the display method of the subsidy information based on the estimated user's emotions. The subsidy display unit, for example, estimates the user's emotions and adjusts the display method of the subsidy information based on the estimated user's emotions. For example, when the user is feeling stressed, the subsidy display unit provides a simple, highly visible display method. Furthermore, when the user is relaxed, the subsidy display unit can also provide a display method including detailed information. Furthermore, when the user is in a hurry, the subsidy display unit can also provide a display method that focuses on the main points. In this way, by providing an optimal display method according to the user's emotions, it is possible to help the user understand the subsidy information.

[0137] The subsidy display unit can improve display accuracy by referring to the user's past subsidy application history when displaying subsidies. The subsidy display unit can improve display accuracy by referring to the user's past subsidy application history when displaying subsidies. For example, the subsidy display unit displays optimal subsidy information based on the user's past subsidy application history. The subsidy display unit can also automatically display related subsidy information from the user's past subsidy application history. The subsidy display unit can also improve display accuracy by referring to the user's past subsidy application history. This makes it possible to provide more accurate subsidy information by improving display accuracy based on the user's past subsidy application history.

[0138] The subsidy display unit can customize the subsidy information based on the user's family structure and age when displaying the subsidy. The subsidy display unit customizes the subsidy information based on the user's family structure and age when displaying the subsidy. For example, the subsidy display unit displays optimal subsidy information based on the user's family structure. The subsidy display unit can also provide appropriate subsidy information based on the user's age. The subsidy display unit can also customize the subsidy information taking into account the user's family structure and age. This makes it possible to provide more appropriate information by providing subsidy information that takes into account the user's family structure and age.

[0139] The subsidy display unit can evaluate the reliability of the user's input content when displaying the subsidy and reflect it in the display result. The subsidy display unit, for example, evaluates the reliability of the user's input content when displaying the subsidy and reflects it in the display result. For example, the subsidy display unit evaluates whether the user's input content is accurate and displays highly reliable subsidy information. Furthermore, if there is an error in the user's input content, the subsidy display unit can also suggest a correction and reflect it in the display result. Furthermore, the subsidy display unit can evaluate the reliability of the user's input content and improve the accuracy of the display result. In this way, by evaluating the reliability of the user's input content, more accurate subsidy information can be provided.

[0140] The subsidy display unit can estimate the user's emotions and adjust the priority of subsidy information based on the estimated user's emotions. The subsidy display unit can, for example, estimate the user's emotions and adjust the priority of subsidy information based on the estimated user's emotions. For example, the subsidy display unit can prioritize displaying important subsidy information when the user is feeling stressed. The subsidy display unit can also display detailed subsidy information when the user is relaxed. The subsidy display unit can also display minimal subsidy information when the user is in a hurry. This can help the user understand the subsidy information by providing optimal priorities according to the user's emotions.

[0141] The subsidy display unit can provide subsidy information taking into account the user's geographical location information when displaying subsidies. For example, the subsidy display unit provides subsidy information taking into account the user's geographical location information when displaying subsidies. For example, if the user moves to a specific area, the subsidy display unit provides subsidy information for that area. The subsidy display unit can also provide optimal subsidy information based on the user's geographical location information. The subsidy display unit can also customize the subsidy information taking into account the user's geographical location information. This makes it possible to provide more appropriate information by providing subsidy information taking into account the user's geographical location information.

[0142] The subsidy display unit may analyze the user's social media activity and provide related subsidy information when displaying subsidies. For example, the subsidy display unit may analyze the user's social media activity and provide related subsidy information when displaying subsidies. For example, the subsidy display unit may provide related subsidy information based on the location where the user checked in on social media. The subsidy display unit may also analyze the content of the user's social media posts and provide related subsidy information. The subsidy display unit may also provide related subsidy information with reference to the activities of the user's friends on social media. This allows for more appropriate information to be provided by providing related subsidy information based on the user's social media activity.

[0143] The subsidy display unit can customize the display algorithm by reflecting the user's past feedback when displaying the subsidy. For example, the subsidy display unit customizes the display algorithm by reflecting the user's past feedback when displaying the subsidy. For example, the subsidy display unit improves the display algorithm based on feedback provided by the user in the past. The subsidy display unit can also suggest a highly accurate display algorithm based on the user's past feedback. The subsidy display unit can also customize the display algorithm by reflecting the user's past feedback. In this way, display accuracy can be improved by customizing the display algorithm based on the user's past feedback.

[0144] The estimation unit can estimate the user's emotions and adjust the display method of the estimate based on the estimated user's emotions. The estimation unit, for example, estimates the user's emotions and adjusts the display method of the estimate based on the estimated user's emotions. For example, if the user is feeling stressed, the estimation unit provides a simple, highly visible display method. Furthermore, if the user is relaxed, the estimation unit can also provide a display method including detailed information. Furthermore, if the user is in a hurry, the estimation unit can also provide a display method that focuses on the main points. In this way, by providing an optimal display method according to the user's emotions, it is possible to help the user understand the estimate.

[0145] The estimating unit can improve the accuracy of the estimate by referring to the user's past estimate history when making an estimate. The estimating unit, for example, improves the accuracy of the estimate by referring to the user's past estimate history when making an estimate. For example, the estimating unit suggests an optimal estimation method based on the user's past estimate history. The estimating unit can also automatically estimate related information from the user's past estimate history. The estimating unit can also improve the accuracy of the estimate by referring to the user's past estimate history. In this way, by improving the accuracy of the estimate based on the user's past estimate history, it is possible to provide a more accurate estimate.

[0146] The estimation unit can customize the estimate content based on the user's family structure and age at the time of estimation. The estimation unit customizes the estimate content based on the user's family structure and age, for example, at the time of estimation. For example, the estimation unit suggests an optimal estimation method based on the user's family structure. The estimation unit can also provide an appropriate estimation method based on the user's age. The estimation unit can also customize the estimate content taking the user's family structure and age into consideration. This makes it possible to provide more appropriate information by providing estimate content that takes the user's family structure and age into consideration.

[0147] The estimation unit can evaluate the reliability of the user's input content at the time of estimation and reflect it in the estimation result. The estimation unit, for example, evaluates the reliability of the user's input content at the time of estimation and reflects it in the estimation result. For example, the estimation unit evaluates whether the user's input content is accurate and provides a highly reliable estimation result. Furthermore, if there is an error in the user's input content, the estimation unit can suggest a correction and reflect it in the estimation result. Furthermore, the estimation unit can evaluate the reliability of the user's input content and improve the accuracy of the estimation result. In this way, by evaluating the reliability of the user's input content, a more accurate estimation result can be provided.

[0148] The estimation unit can estimate the user's emotions and adjust the priority of the estimation results based on the estimated user's emotions. The estimation unit, for example, estimates the user's emotions and adjusts the priority of the estimation results based on the estimated user's emotions. For example, when the user is feeling stressed, the estimation unit can prioritize and display important estimation results. Furthermore, when the user is relaxed, the estimation unit can display detailed estimation results. Furthermore, when the user is in a hurry, the estimation unit can display minimal estimation results. This can help the user understand the estimation results by providing optimal priorities according to the user's emotions.

[0149] The estimation unit can provide estimate contents taking into account the user's geographical location information when providing an estimate. For example, the estimation unit provides estimate contents taking into account the user's geographical location information when providing an estimate. For example, if the user is moving to a specific area, the estimation unit provides estimate contents for that area. The estimation unit can also provide optimal estimate contents based on the user's geographical location information. The estimation unit can also customize the estimate contents taking into account the user's geographical location information. In this way, by providing estimate contents taking into account the user's geographical location information, more appropriate information can be provided.

[0150] The estimation unit can analyze the user's social media activity at the time of estimation and provide related estimate content. The estimation unit, for example, analyzes the user's social media activity at the time of estimation and provides related estimate content. For example, the estimation unit can provide related estimate content based on the location where the user checked in on social media. The estimation unit can also analyze the content of the user's social media posts and provide related estimate content. The estimation unit can also provide related estimate content by referring to the activity of the user's friends on social media. In this way, by providing related estimate content based on the user's social media activity, more appropriate information can be provided.

[0151] The estimation unit can customize the estimation algorithm by reflecting the user's past feedback when making an estimate. The estimation unit, for example, customizes the estimation algorithm by reflecting the user's past feedback when making an estimate. For example, the estimation unit improves the estimation algorithm based on feedback provided by the user in the past. The estimation unit can also propose a highly accurate estimation algorithm based on the user's past feedback. The estimation unit can also customize the estimation algorithm by reflecting the user's past feedback. In this way, the estimation accuracy can be improved by customizing the estimation algorithm based on the user's past feedback. === Hard Collateral 1-1 === Each of the multiple elements, including the reception unit, analysis unit, selection unit, listing unit, management unit, subsidy display unit, and estimate unit, is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the reception unit is realized by the reception device 38 of the smart device 14 and receives information from a user. The analysis unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes the received information. The selection unit is realized by the specific processing unit 290 of the data processing device 12 and selects candidate medical institutions or educational institutions based on the analyzed information. The listing unit is realized by the control unit 46A of the smart device 14 and displays the selected candidates to the user in a list. The management unit is realized by the specific processing unit 290 of the data processing device 12 and manages expenses and tasks. The subsidy display unit is realized by the specific processing unit 290 of the data processing device 12 and displays a list of subsidy programs. The estimate unit is realized by, for example, the control unit 46A of the smart device 14, and serves as a bulk estimate site. === Hard Collateral 1-2 === Each of the multiple elements, including the reception unit, analysis unit, selection unit, listing unit, management unit, subsidy display unit, and estimation unit, is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the reception unit is realized by the microphone 238 of the smart glasses 214 and receives information from the user. The analysis unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and analyzes the received information. The selection unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and selects candidate medical institutions or educational institutions based on the analyzed information. The listing unit is realized, for example, by the control unit 46A of the smart glasses 214 and displays the selected candidates to the user in a list. The management unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and manages expenses and tasks. The subsidy display unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and displays a list of subsidy programs. The estimate unit is realized by, for example, the control unit 46A of the smart glasses 214, and serves as a bulk estimate site. === Hard Collateral 1-3 === Each of the multiple elements, including the reception unit, analysis unit, selection unit, listing unit, management unit, subsidy display unit, and estimate unit, is implemented, for example, by at least one of the headset terminal 314 and the data processing device 12. For example, the reception unit is implemented by the microphone 238 of the headset terminal 314 and receives information from the user. The analysis unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and analyzes the received information. The selection unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and selects candidate medical institutions or educational institutions based on the analyzed information. The listing unit is implemented, for example, by the control unit 46A of the headset terminal 314 and displays the selected candidates to the user in a list. The management unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and manages expenses and tasks. The subsidy display unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and displays a list of subsidy programs. The estimate unit is realized by, for example, the control unit 46A of the headset type terminal 314, and serves as a bulk estimate site. === Hard Collateral 1-4 === Each of the multiple elements, including the reception unit, analysis unit, selection unit, listing unit, management unit, subsidy display unit, and estimate unit, is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the reception unit is realized by the microphone 238 of the robot 414 and receives information from the user. The analysis unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and analyzes the received information. The selection unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and selects candidate medical institutions or educational institutions based on the analyzed information. The listing unit is realized, for example, by the control unit 46A of the robot 414 and displays the selected candidates to the user in a list. The management unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and manages expenses and tasks. The subsidy display unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and displays a list of subsidy programs. The estimate unit is realized by, for example, the control unit 46A of the robot 414, and serves as a bulk estimate site.

[0152] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0153] The moving information management system may further include a health management unit that monitors the user's health condition. For example, the health management unit may collect the user's health data and evaluate the impact of the stress of moving on the user's health. The health management unit may also adjust the moving schedule based on the user's health condition. Furthermore, the health management unit may provide the user with advice on maintaining their health. This may make it easier for the user to maintain their health during the move.

[0154] The moving information management system may further include a pet management unit that manages information about the user's pet. For example, the pet management unit may record the type and health status of the user's pet and suggest pet-friendly facilities at the new location. The pet management unit may also list the procedures and documents required for moving a pet. Furthermore, the pet management unit may provide advice on reducing stress for pets. This allows the user to move their pet smoothly.

[0155] The moving information management system can further include a leisure suggestion unit that suggests leisure facilities in the new destination based on the user's hobbies and interests. For example, the leisure suggestion unit analyzes the user's hobbies and interests and creates a list of recommended leisure facilities in the new destination. The leisure suggestion unit can also plan leisure activities according to the user's schedule. Furthermore, the leisure suggestion unit can provide the user with discount information on leisure facilities. This allows the user to enjoy life in the new destination.

[0156] The moving information management system may further include a progress adjustment unit that estimates the user's emotions and adjusts the progress of the move based on the estimated user emotions. For example, the progress adjustment unit may slow down the moving schedule if the user is feeling stressed. The progress adjustment unit may also efficiently advance the moving schedule if the user is relaxed. Furthermore, the progress adjustment unit may provide support for quickly completing the move if the user is in a hurry. This makes it possible to provide an optimal moving schedule that corresponds to the user's emotions.

[0157] The moving information management system may further include an advice unit that estimates the user's emotions and provides advice about the move based on the estimated user emotions. For example, if the advice unit is feeling stressed, it may suggest ways to relax. If the user is relaxed, the advice unit may also provide advice on how to efficiently proceed with the move. Furthermore, if the user is in a hurry, the advice unit may also provide advice on how to quickly complete the move. This makes it possible to provide optimal advice according to the user's emotions.

[0158] The moving information management system may further include a support unit that estimates the user's emotions and provides support related to the move based on the estimated user emotions. For example, if the support unit is feeling stressed, it may provide a service to handle moving procedures on the user's behalf. If the user is feeling relaxed, the support unit may also provide support for the user to complete the moving procedures themselves. Furthermore, if the user is in a hurry, the support unit may also provide support for the user to complete the move quickly. This makes it possible to provide optimal support according to the user's emotions.

[0159] The moving information management system can further include an information providing unit that estimates the user's emotions and provides information about the move based on the estimated user emotions. For example, if the user is feeling stressed, the information providing unit can provide simple, highly visible information. If the user is relaxed, the information providing unit can also provide detailed information. Furthermore, if the user is in a hurry, the information providing unit can also provide information that focuses on the main points. This makes it possible to provide optimal information according to the user's emotions.

[0160] The moving information management system may further include a notification unit that estimates the user's emotions and adjusts notifications related to the move based on the estimated user emotions. For example, the notification unit may reduce the frequency of notifications when the user is feeling stressed. The notification unit may also provide detailed notifications when the user is relaxed. Furthermore, the notification unit may prioritize important notifications when the user is in a hurry. This allows the system to provide optimal notifications according to the user's emotions.

[0161] The moving information management system can further include an aftercare section that supports the user's life after moving. For example, the aftercare section provides information about the local community after moving. The aftercare section can also guide the user to procedures and services necessary for life after moving. Furthermore, the aftercare section can also provide advice regarding life after moving. This allows the user to smoothly start life after moving.

[0162] The moving information management system may further include an environmental assessment unit that evaluates the environmental impact of a user's move and proposes an environmentally friendly moving plan. For example, the environmental assessment unit may calculate the carbon dioxide emissions associated with the move and propose an environmentally friendly moving method. The environmental assessment unit may also recommend the use of recyclable packaging materials. Furthermore, the environmental assessment unit may also provide guidance on how to dispose of waste associated with the move. This allows the user to move in an environmentally friendly manner.

[0163] The processing flow of the second embodiment will be briefly explained below.

[0164] Step 1: The reception unit receives information from the user about the moving company, notifications to the government office, and family composition. For example, the reception unit receives information from the user such as the departure and destination points, the number and ages of family members, and the details of notifications to the government office. Step 2: The analysis unit analyzes the information received by the reception unit. For example, the analysis unit analyzes the information input by the user using a data analysis method or algorithm. Step 3: The selection unit selects candidates for medical institutions and educational institutions based on the information analyzed by the analysis unit. For example, the selection unit displays information on nearby hospitals and schools. Step 4: The listing unit displays the candidates selected by the selection unit to the user, and the user selects and lists the information they need. For example, the listing unit allows the user to select and list the information they need from the displayed candidates. Step 5: The management section manages expenses and tasks based on the information listed by the listing section. For example, the management section displays a list of expenses and tasks for necessary procedures for moving. Step 6: The subsidy display unit displays a list of subsidy programs related to relocation based on the information managed by the management unit. For example, the subsidy display unit displays information on subsidies and grants related to relocation. Step 7: The quotation unit acts as a bulk quotation site based on the information displayed by the subsidy display unit. For example, the quotation unit receives a commission from each contractor selected by the user.

[0165] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0166] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0167] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0168] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0169] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0170] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0171] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0172] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0173] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0174] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0175] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0176] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0177] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0178] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0179] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0180] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0181] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0182] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0183] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0184] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0185] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0186] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0187] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0188] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0189] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0190] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0191] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0192] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0193] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0194] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0195] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0196] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0197] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0198] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0199] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0200] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0201] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0202] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0203] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0204] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0205] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0206] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0207] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0208] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0209] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0210] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0211] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0212] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0213] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0214] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0215] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0216] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0217] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0218] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0219] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0220] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0221] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0222] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0223] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0224] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0225] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0226] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0227] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0228] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0229] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0230] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0231] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0232] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0233] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0234] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0235] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0236] [Explanation of symbols]

[0237] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a reception unit that receives information from users about moving companies, notifications to government offices, and family composition; an analysis unit that analyzes the information received by the reception unit; a selection unit that selects candidates for medical institutions or educational institutions based on the information analyzed by the analysis unit; a listing unit that displays the candidates selected by the selection unit to a user, and allows the user to select appropriate information and list it; a management unit that manages expenses and tasks based on the information listed by the listing unit; a subsidy display unit that displays a list of subsidy programs related to relocation based on the information managed by the management unit; an estimate unit that serves as a bulk estimate site based on the information displayed by the subsidy display unit; A system characterized by:

2. The reception unit Accepts information from users about their departure and destination, number of family members and their ages, and details of notifications to government offices 2. The system of claim 1.

3. The analysis unit The information received by the reception unit is analyzed, and candidates for medical institutions and educational institutions in the area are selected.

2. The system of claim 1.

4. The selection unit View hospital or school information 2. The system of claim 1.

5. The listing unit The user selects the necessary information from the displayed candidates and creates a list 2. The system of claim 1.

6. The management unit Display a list of moving expenses or procedure tasks 2. The system of claim 1.

7. The subsidy display unit View information on subsidies and grants for moving 2. The system of claim 1.

8. The estimation unit We receive fees from each provider selected by the user.

2. The system of claim 1.

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