system

Abstract

The system of the embodiment aims to provide women with information, resources, and tools in one place to foster empathy and growth. [Solution] A system according to an embodiment includes an information providing unit, a resource providing unit, a tool providing unit, and a participation accepting unit. The information providing unit provides information. The resource providing unit provides resources based on the information provided by the information providing unit. The tool providing unit provides tools based on the resources provided by the resource providing unit. The participation accepting unit accepts participation to use the tools provided by the tool providing 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] Previous technology has been challenged by a lack of a centralized system that provides information, resources, and tools to help women empathize and grow.

[0005] The system of the embodiment aims to provide women with information, resources, and tools in one place to foster empathy and growth. [Means for solving the problem]

[0006] A system according to an embodiment includes an information providing unit, a resource providing unit, a tool providing unit, and a participation accepting unit. The information providing unit provides information. The resource providing unit provides resources based on the information provided by the information providing unit. The tool providing unit provides tools based on the resources provided by the resource providing unit. The participation accepting unit accepts participation to use the tools provided by the tool providing unit. [Effects of the Invention]

[0007] The system according to the embodiment can provide women with information, resources, and tools in one place to foster empathy and growth. [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 community system according to an embodiment of the present invention provides information, resources, and tools to help women encourage and connect with each other and achieve self-improvement. This community system provides support for women to achieve self-improvement and live better lives. For example, the system may include articles and videos on mental health, workshops for self-development, forums for building relationships, and seminars on career development. The community system is provided through an online platform, allowing users to select and participate in content based on their interests and needs. For example, the system may include an information provider that provides information on mental health, a resource provider that provides resources related to self-improvement, a tool provider that provides tools for building relationships, and a participation reception unit that accepts participation in career development. This allows the community system to provide support for women to achieve self-improvement and live better lives.

[0029] A community system according to an embodiment includes an information providing unit, a resource providing unit, a tool providing unit, and a participation accepting unit. The information providing unit provides information on various topics of interest to women. Examples of such information include articles and videos on mental health, workshops for self-development, forums for building relationships, and seminars on career development. The resource providing unit provides resources for women to achieve self-development based on the information provided by the information providing unit. Examples of such resources include mental health guidebooks, materials for self-development, toolkits for building relationships, and online courses for career development. The tool providing unit provides tools for women to achieve self-development based on the resources provided by the resource providing unit. Examples of such tools include apps to support mental health, online platforms for self-development, communication tools for building relationships, and networking tools for career development. The participation accepting unit accepts participation to use the tools provided by the tool providing unit. Examples of such tools include participation in mental health workshops, registration for online self-development courses, participation in forums for building relationships, and participation in seminars for career development. This enables the community system according to an embodiment to provide support for women to achieve self-development and live better lives.

[0030] The information providing unit can provide information related to mental health. Information related to mental health includes, for example, stress management, psychotherapy, and mental health care guidelines. The information providing unit can provide, for example, articles and videos related to stress management. The information providing unit can also provide information related to psychotherapy. For example, it can provide information related to cognitive behavioral therapy and mindfulness. The information providing unit can also provide mental health care guidelines. For example, it can provide information on mental health care methods in daily life and information on how to receive support from experts. In this way, the information providing unit can support the mental health of the user by providing information related to mental health.

[0031] The resource providing unit can provide resources related to self-development. Resources related to self-development include, for example, self-help books, online courses, workshops, etc. The resource providing unit can, for example, provide self-help books. The resource providing unit can also provide online courses. For example, it can provide online courses related to self-development. The resource providing unit can also provide workshops. For example, it can provide workshops related to self-development. In this way, the resource providing unit can promote the self-development of the user by providing resources related to self-development.

[0032] The tool providing unit can provide tools that are useful for building human relationships. Tools that are useful for building human relationships include, for example, communication tools, team building tools, and counseling tools. The tool providing unit can provide, for example, communication tools. The tool providing unit can also provide team building tools. For example, it can provide tools that are useful for team building. The tool providing unit can also provide counseling tools. For example, it can provide tools that are useful for counseling. In this way, the tool providing unit can support the improvement of the user's human relationships by providing tools that are useful for building relationships.

[0033] The participation acceptance unit can accept participation related to career growth. Participation related to career growth includes, for example, career seminars, networking events, mentoring programs, etc. The participation acceptance unit can, for example, accept participation in a career seminar. The participation acceptance unit can also accept participation in a networking event. For example, it can accept participation in a networking event. The participation acceptance unit can also accept participation in a mentoring program. For example, it can accept participation in a mentoring program. In this way, the participation acceptance unit can support the career growth of the user by accepting participation related to career development.

[0034] The information providing unit can analyze the user's past browsing history and select appropriate information. The information providing unit can provide new related information based on, for example, the content of articles or videos the user has viewed in the past. The information providing unit can also provide the latest information and trends based on topics frequently viewed by the user. Furthermore, the information providing unit can suggest information that the user may be interested in by referring to content the user has saved in the past. In this way, the information providing unit can provide optimal information based on the user's past browsing history, thereby providing information that meets the user's interests and needs. Methods for collecting and analyzing past browsing history include, for example, web browser history and app usage history. In this way, the information providing unit can analyze the user's past browsing history and select appropriate information.

[0035] The information providing unit can filter information based on the user's current living situation or areas of interest when providing information. For example, when the user inputs their current living situation, the information providing unit can provide information appropriate to the situation. Furthermore, when the user selects an area of ​​interest, the information providing unit can prioritize information related to that area. Furthermore, when the user sets a specific goal, the information providing unit can provide information useful for achieving the goal. This allows the information providing unit to provide more appropriate support by providing information according to the user's living situation and areas of interest. Examples of methods for collecting and analyzing the current living situation include survey results, user profile information, etc. Examples of methods for collecting and analyzing areas of interest include the user's search history, social media activity, etc. This allows the information providing unit to filter information based on the user's current living situation and areas of interest when providing information.

[0036] When providing information, the information providing unit can prioritize providing highly relevant information based on the user's geographical location information. For example, the information providing unit can provide information about nearby events and workshops based on the user's current location. Furthermore, if the user is interested in a particular area, the information providing unit can prioritize providing information related to that area. Furthermore, if the user is traveling, the information providing unit can provide information about travel destinations and tourist spots. This allows the information providing unit to provide more appropriate support by providing highly relevant information based on the user's geographical location information. Examples of methods for collecting and using geographical location information include GPS data and IP addresses. This allows the information providing unit to prioritize providing highly relevant information based on the user's geographical location information when providing information.

[0037] The information providing unit can analyze the user's social media activity and provide related information when providing information. The information providing unit can provide related information based on, for example, content shared by the user on social media. The information providing unit can also provide information that is likely to be of interest to the user based on accounts and groups the user follows. Furthermore, the information providing unit can provide information related to events the user is participating in on social media. This allows the information providing unit to provide more appropriate support by providing related information based on the user's social media activity. Methods for collecting and analyzing social media activity include, for example, post content, the number of likes, the number of followers, etc. This allows the information providing unit to analyze the user's social media activity and provide related information when providing information.

[0038] The resource providing unit can select an appropriate resource by analyzing the user's past usage history when providing a resource. For example, the resource providing unit can provide new related resources based on resources the user has used in the past. The resource providing unit can also provide the latest resources and trends based on resources the user frequently uses. Furthermore, the resource providing unit can suggest resources that the user may be interested in by referring to resources the user has saved in the past. In this way, the resource providing unit can provide optimal resources based on the user's past usage history, thereby providing resources that meet the user's interests and needs. Methods for collecting and analyzing past usage history include, for example, app usage history and download history. In this way, the resource providing unit can select an appropriate resource by analyzing the user's past usage history when providing a resource.

[0039] The resource providing unit can perform filtering based on the user's current living situation or areas of interest when providing resources. For example, when the user inputs their current living situation, the resource providing unit can provide resources appropriate to that situation. Furthermore, when the user selects an area of ​​interest, the resource providing unit can preferentially provide resources related to that area. Furthermore, when the user sets a specific goal, the resource providing unit can provide resources that are useful for achieving that goal. In this way, the resource providing unit can provide more appropriate support by providing resources according to the user's living situation or areas of interest. Methods for filtering resources include, for example, the user's living situation and areas of interest. In this way, the resource providing unit can perform filtering based on the user's current living situation and areas of interest when providing resources.

[0040] The resource providing unit can provide resources with priority based on the user's geographical location information when providing resources. For example, the resource providing unit can provide resources for nearby events or workshops based on the user's current location. Furthermore, if the user is interested in a particular area, the resource providing unit can also provide resources related to that area with priority. Furthermore, if the user is traveling, the resource providing unit can provide resources for the user's travel destination or tourist attractions. This allows the resource providing unit to provide more appropriate support by providing resources with high relevance based on the user's geographical location information. Examples of methods for collecting and using geographical location information include GPS data and IP addresses. This allows the resource providing unit to provide resources with high relevance based on the user's geographical location information when providing resources with priority.

[0041] The resource providing unit can analyze the user's social media activity and provide related resources when providing resources. The resource providing unit can provide related resources based on, for example, content shared by the user on social media. The resource providing unit can also provide resources that the user is likely to be interested in based on accounts and groups the user follows. Furthermore, the resource providing unit can provide resources related to events the user is participating in on social media. This allows the resource providing unit to provide more appropriate support by providing related resources based on the user's social media activity. Methods for collecting and analyzing social media activity include, for example, post content, the number of likes, and the number of followers. This allows the resource providing unit to analyze the user's social media activity and provide related resources when providing resources.

[0042] When providing a tool, the tool providing unit can analyze the user's past usage history and select an appropriate tool. For example, the tool providing unit can provide new related tools based on tools the user has used in the past. The tool providing unit can also provide the latest tools and trends based on tools the user frequently uses. Furthermore, the tool providing unit can suggest tools that the user may be interested in by referring to tools the user has saved in the past. In this way, the tool providing unit can provide the optimal tool based on the user's past usage history, thereby providing tools that meet the user's interests and needs. Methods for collecting and analyzing past usage history include, for example, app usage history and download history. In this way, the tool providing unit can analyze the user's past usage history and select an appropriate tool when providing a tool.

[0043] The tool providing unit can filter tools based on the user's current living situation or areas of interest when providing the tools. For example, when the user inputs their current living situation, the tool providing unit provides tools appropriate to the situation. Furthermore, when the user selects an area of ​​interest, the tool providing unit can preferentially provide tools related to that area. Furthermore, when the user sets a specific goal, the tool providing unit can provide tools that are useful for achieving the goal. In this way, the tool providing unit can provide more appropriate support by providing tools according to the user's living situation or areas of interest. Methods for filtering tools include, for example, the user's living situation and areas of interest. In this way, the tool providing unit can filter tools based on the user's current living situation and areas of interest when providing the tools.

[0044] When providing tools, the tool providing unit can prioritize providing highly relevant tools based on the user's geographical location information. For example, the tool providing unit can provide tools for nearby events or workshops based on the user's current location. Furthermore, if the user is interested in a particular region, the tool providing unit can prioritize providing tools related to that region. Furthermore, if the user is traveling, the tool providing unit can provide tools for travel destinations or tourist spots. This allows the tool providing unit to provide more appropriate support by providing highly relevant tools based on the user's geographical location information. Examples of methods for collecting and using geographical location information include GPS data and IP addresses. This allows the tool providing unit to prioritize providing highly relevant tools based on the user's geographical location information when providing tools.

[0045] The tool providing unit can analyze the user's social media activities and provide related tools when providing the tools. For example, the tool providing unit can provide related tools based on content shared by the user on social media. The tool providing unit can also provide tools that the user may be interested in based on accounts and groups the user follows. Furthermore, the tool providing unit can provide tools related to events the user is participating in on social media. This allows the tool providing unit to provide more appropriate support by providing related tools based on the user's social media activities. Methods for collecting and analyzing social media activities include, for example, post content, the number of likes, and the number of followers. This allows the tool providing unit to analyze the user's social media activities and provide related tools when providing the tools.

[0046] The participation acceptance unit can analyze the user's past participation history and select an appropriate participation method when accepting participation. The participation acceptance unit, for example, suggests a related new event based on the history of events the user has previously participated in. The participation acceptance unit can also suggest an optimal participation method based on the type of events the user frequently participates in. Furthermore, the participation acceptance unit can suggest events that the user may be interested in by referring to events that the user has saved in the past. In this way, the participation acceptance unit can provide an optimal participation method based on the user's past participation history, thereby providing a participation method that meets the user's interests and needs. Methods for collecting and analyzing past participation history include, for example, event participation history and seminar participation history. In this way, the participation acceptance unit can analyze the user's past participation history and select an appropriate participation method when accepting participation.

[0047] The participation acceptance unit can perform filtering based on the user's current living situation or areas of interest when accepting participation. For example, when the user inputs their current living situation, the participation acceptance unit can suggest events that are appropriate for that situation. Furthermore, when the user selects an area of ​​interest, the participation acceptance unit can also preferentially suggest events related to that area. Furthermore, when the user sets a specific goal, the participation acceptance unit can also suggest events that will help achieve that goal. In this way, the participation acceptance unit can provide more appropriate support by offering participation methods that correspond to the user's living situation and areas of interest. Methods for filtering participation include, for example, the user's living situation and areas of interest. In this way, the participation acceptance unit can perform filtering based on the user's current living situation and areas of interest when accepting participation.

[0048] The participation acceptance unit can prioritize accepting participation based on the user's geographical location information when accepting participation. For example, the participation acceptance unit can prioritize accepting participation for nearby events or workshops based on the user's current location. Furthermore, if the user is interested in a particular region, the participation acceptance unit can prioritize accepting participation for events related to that region. Furthermore, if the user is traveling, the participation acceptance unit can prioritize accepting participation for events or tourist spots at the user's travel destination. This allows the participation acceptance unit to provide more appropriate support by providing participation methods that are highly relevant based on the user's geographical location information. Examples of methods for collecting and using geographical location information include GPS data and IP addresses. This allows the participation acceptance unit to prioritize accepting participation based on the user's geographical location information when accepting participation.

[0049] The participation acceptance unit can analyze the user's social media activity and accept related participations when accepting participations. The participation acceptance unit can, for example, accept participations for related events based on content shared by the user on social media. The participation acceptance unit can also accept participations for events that the user is likely to be interested in based on accounts and groups the user follows. Furthermore, the participation acceptance unit can accept participations related to events the user is participating in on social media. This allows the participation acceptance unit to provide more appropriate support by providing related participation methods based on the user's social media activity. Methods for collecting and analyzing social media activity include, for example, post content, the number of likes, the number of followers, etc. This allows the participation acceptance unit to analyze the user's social media activity and accept related participations when accepting participations.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The community system may further include a health monitoring unit that monitors the user's health status. The health monitoring unit obtains data from the user's fitness tracker or smartwatch and monitors the user's health status in real time. For example, it may monitor the user's heart rate, sleep patterns, exercise volume, etc., and send an alert if an abnormality is detected. The health monitoring unit may also provide appropriate health advice and resources based on the user's health data. This allows users to not only improve themselves but also manage their health at the same time.

[0052] The resource provider can customize resources based on a user's learning style. For example, it can provide videos and infographics for visual learners, podcasts and audiobooks for auditory learners, and interactive workshops and hands-on materials for hands-on learners. Furthermore, the resource provider can continuously improve the content of resources based on user feedback. This allows the resource provider to provide resources tailored to a user's learning style, thereby more effectively supporting self-development.

[0053] The participation acceptance unit can analyze the user's past participation history and send appropriate reminders. For example, it can send reminders for events the user has previously participated in, encouraging the user to participate again. It can also send reminders for new events based on the types of events the user frequently participates in. It can also send reminders for events that the user may be interested in, referring to events that the user has saved in the past. In this way, the participation acceptance unit can provide optimal reminders based on the user's past participation history, thereby offering a participation method that suits the user's interests and needs.

[0054] The resource providing unit can provide local resources based on the user's geographical location information. For example, resources for nearby libraries or community centers can be provided based on the user's current location. Also, if the user is interested in a particular area, resources related to that area can be provided. Furthermore, if the user is traveling, resources for travel destinations and tourist attractions can be provided. This allows the resource providing unit to provide more appropriate support by providing highly relevant resources based on the user's geographical location information.

[0055] The participation acceptance unit can analyze the user's social media activity and suggest related events to participate in. For example, it can suggest related events to participate in based on content the user has shared on social media. It can also suggest events that the user may be interested in based on accounts and groups the user follows. It can also suggest participation related to events the user is participating in on social media. This allows the participation acceptance unit to provide more appropriate support by offering relevant participation methods based on the user's social media activity.

[0056] The processing flow of the first embodiment will be briefly explained below.

[0057] Step 1: The resource department provides information on a variety of topics of interest to women, including articles and videos on mental health, self-improvement workshops, relationship-building forums, and career advancement seminars. Step 2: The Resource Unit uses the information provided by the Information Unit to provide resources to help women achieve personal growth, such as mental health guidebooks, self-development materials, relationship-building toolkits, and online courses for career advancement. Step 3: The tool provider provides women with tools to achieve personal growth based on the resources provided by the resource provider, such as apps to support mental health, online platforms for self-development, communication tools for relationship building, and networking tools for career advancement. Step 4: The Participation Acceptance Unit accepts participants to use the tools provided by the Tool Provider Unit, such as attending a mental health workshop, enrolling in an online course for personal development, participating in a forum for relationship building, or attending a seminar for career development.

[0058] (Example 2) A community system according to an embodiment of the present invention provides information, resources, and tools to help women encourage and connect with each other and achieve self-improvement. This community system provides support for women to achieve self-improvement and live better lives. For example, the system may include articles and videos on mental health, workshops for self-development, forums for building relationships, and seminars on career development. The community system is provided through an online platform, allowing users to select and participate in content based on their interests and needs. For example, the system may include an information provider that provides information on mental health, a resource provider that provides resources related to self-improvement, a tool provider that provides tools for building relationships, and a participation reception unit that accepts participation in career development. This allows the community system to provide support for women to achieve self-improvement and live better lives.

[0059] A community system according to an embodiment includes an information providing unit, a resource providing unit, a tool providing unit, and a participation accepting unit. The information providing unit provides information on various topics of interest to women. Examples of such information include articles and videos on mental health, workshops for self-development, forums for building relationships, and seminars on career development. The resource providing unit provides resources for women to achieve self-development based on the information provided by the information providing unit. Examples of such resources include mental health guidebooks, materials for self-development, toolkits for building relationships, and online courses for career development. The tool providing unit provides tools for women to achieve self-development based on the resources provided by the resource providing unit. Examples of such tools include apps to support mental health, online platforms for self-development, communication tools for building relationships, and networking tools for career development. The participation accepting unit accepts participation to use the tools provided by the tool providing unit. Examples of such tools include participation in mental health workshops, registration for online self-development courses, participation in forums for building relationships, and participation in seminars for career development. This enables the community system according to an embodiment to provide support for women to achieve self-development and live better lives.

[0060] The information providing unit can provide information related to mental health. Information related to mental health includes, for example, stress management, psychotherapy, and mental health care guidelines. The information providing unit can provide, for example, articles and videos related to stress management. The information providing unit can also provide information related to psychotherapy. For example, it can provide information related to cognitive behavioral therapy and mindfulness. The information providing unit can also provide mental health care guidelines. For example, it can provide information on mental health care methods in daily life and information on how to receive support from experts. In this way, the information providing unit can support the mental health of the user by providing information related to mental health.

[0061] The resource providing unit can provide resources related to self-development. Resources related to self-development include, for example, self-help books, online courses, workshops, etc. The resource providing unit can, for example, provide self-help books. The resource providing unit can also provide online courses. For example, it can provide online courses related to self-development. The resource providing unit can also provide workshops. For example, it can provide workshops related to self-development. In this way, the resource providing unit can promote the self-development of the user by providing resources related to self-development.

[0062] The tool providing unit can provide tools that are useful for building human relationships. Tools that are useful for building human relationships include, for example, communication tools, team building tools, and counseling tools. The tool providing unit can provide, for example, communication tools. The tool providing unit can also provide team building tools. For example, it can provide tools that are useful for team building. The tool providing unit can also provide counseling tools. For example, it can provide tools that are useful for counseling. In this way, the tool providing unit can support the improvement of the user's human relationships by providing tools that are useful for building relationships.

[0063] The participation acceptance unit can accept participation related to career growth. Participation related to career growth includes, for example, career seminars, networking events, mentoring programs, etc. The participation acceptance unit can, for example, accept participation in a career seminar. The participation acceptance unit can also accept participation in a networking event. For example, it can accept participation in a networking event. The participation acceptance unit can also accept participation in a mentoring program. For example, it can accept participation in a mentoring program. In this way, the participation acceptance unit can support the career growth of the user by accepting participation related to career development.

[0064] The information providing unit can estimate the user's emotions and adjust the content of information to be provided based on the estimated emotions. For example, if the user is feeling stressed, the information providing unit can prioritize providing information on relaxation methods and stress relief. Furthermore, if the user is feeling happy, the information providing unit can provide positive experiences and success stories. Furthermore, if the user is feeling anxious, the information providing unit can provide encouraging messages and support information that give a sense of security. In this way, the information providing unit can provide more appropriate support by providing information according to the user's emotions. Emotions are estimated using methods such as facial expression recognition, voice analysis, and questionnaire results. In this way, the information providing unit can estimate the user's emotions and adjust the content of information to be provided based on the estimated emotions.

[0065] The information providing unit can analyze the user's past browsing history and select appropriate information. The information providing unit can provide new related information based on, for example, the content of articles or videos the user has viewed in the past. The information providing unit can also provide the latest information and trends based on topics frequently viewed by the user. Furthermore, the information providing unit can suggest information that the user may be interested in by referring to content the user has saved in the past. In this way, the information providing unit can provide optimal information based on the user's past browsing history, thereby providing information that meets the user's interests and needs. Methods for collecting and analyzing past browsing history include, for example, web browser history and app usage history. In this way, the information providing unit can analyze the user's past browsing history and select appropriate information.

[0066] The information providing unit can filter information based on the user's current living situation or areas of interest when providing information. For example, when the user inputs their current living situation, the information providing unit can provide information appropriate to the situation. Furthermore, when the user selects an area of ​​interest, the information providing unit can prioritize information related to that area. Furthermore, when the user sets a specific goal, the information providing unit can provide information useful for achieving the goal. This allows the information providing unit to provide more appropriate support by providing information according to the user's living situation and areas of interest. Examples of methods for collecting and analyzing the current living situation include survey results, user profile information, etc. Examples of methods for collecting and analyzing areas of interest include the user's search history, social media activity, etc. This allows the information providing unit to filter information based on the user's current living situation and areas of interest when providing information.

[0067] The information providing unit can estimate the user's emotions and determine the priority of information based on the estimated emotions. For example, if the user is sad, the information providing unit can prioritize providing encouraging and comforting information. Furthermore, if the user is excited, the information providing unit can prioritize providing interesting new information. Furthermore, if the user is tired, the information providing unit can prioritize providing information related to relaxation and rest. In this way, the information providing unit can determine the priority of information according to the user's emotions and provide more appropriate information. Emotion estimation is performed using methods such as facial expression recognition, voice analysis, and questionnaire results. Methods for determining the priority of information include, for example, the user's emotion score and the importance of information. In this way, the information providing unit can estimate the user's emotions and determine the priority of information based on the estimated emotions.

[0068] When providing information, the information providing unit can prioritize providing highly relevant information based on the user's geographical location information. For example, the information providing unit can provide information about nearby events and workshops based on the user's current location. Furthermore, if the user is interested in a particular area, the information providing unit can prioritize providing information related to that area. Furthermore, if the user is traveling, the information providing unit can provide information about travel destinations and tourist spots. This allows the information providing unit to provide more appropriate support by providing highly relevant information based on the user's geographical location information. Examples of methods for collecting and using geographical location information include GPS data and IP addresses. This allows the information providing unit to prioritize providing highly relevant information based on the user's geographical location information when providing information.

[0069] The information providing unit can analyze the user's social media activity and provide related information when providing information. The information providing unit can provide related information based on, for example, content shared by the user on social media. The information providing unit can also provide information that is likely to be of interest to the user based on accounts and groups the user follows. Furthermore, the information providing unit can provide information related to events the user is participating in on social media. This allows the information providing unit to provide more appropriate support by providing related information based on the user's social media activity. Methods for collecting and analyzing social media activity include, for example, post content, the number of likes, the number of followers, etc. This allows the information providing unit to analyze the user's social media activity and provide related information when providing information.

[0070] The resource providing unit can estimate the user's emotions and adjust the content of the resources to be provided based on the estimated emotions. For example, when the user is feeling stressed, the resource providing unit can provide resources related to relaxation methods and stress relief. Furthermore, when the user is feeling happy, the resource providing unit can provide positive experiences and success stories. Furthermore, when the user is feeling anxious, the resource providing unit can provide encouraging messages and support resources that give a sense of security. In this way, the resource providing unit can provide more appropriate support by providing resources according to the user's emotions. Emotions are estimated using methods such as facial expression recognition, voice analysis, and questionnaire results. In this way, the resource providing unit can estimate the user's emotions and adjust the content of the resources to be provided based on the estimated emotions.

[0071] The resource providing unit can select an appropriate resource by analyzing the user's past usage history when providing a resource. For example, the resource providing unit can provide new related resources based on resources the user has used in the past. The resource providing unit can also provide the latest resources and trends based on resources the user frequently uses. Furthermore, the resource providing unit can suggest resources that the user may be interested in by referring to resources the user has saved in the past. In this way, the resource providing unit can provide optimal resources based on the user's past usage history, thereby providing resources that meet the user's interests and needs. Methods for collecting and analyzing past usage history include, for example, app usage history and download history. In this way, the resource providing unit can select an appropriate resource by analyzing the user's past usage history when providing a resource.

[0072] The resource providing unit can perform filtering based on the user's current living situation or areas of interest when providing resources. For example, when the user inputs their current living situation, the resource providing unit can provide resources appropriate to that situation. Furthermore, when the user selects an area of ​​interest, the resource providing unit can preferentially provide resources related to that area. Furthermore, when the user sets a specific goal, the resource providing unit can provide resources that are useful for achieving that goal. In this way, the resource providing unit can provide more appropriate support by providing resources according to the user's living situation or areas of interest. Methods for filtering resources include, for example, the user's living situation and areas of interest. In this way, the resource providing unit can perform filtering based on the user's current living situation and areas of interest when providing resources.

[0073] The resource providing unit can estimate the user's emotions and determine the priority of resources based on the estimated emotions. For example, if the user is sad, the resource providing unit can prioritize providing resources that encourage or comfort the user. Furthermore, if the user is excited, the resource providing unit can prioritize providing new resources that will attract the user's attention. Furthermore, if the user is tired, the resource providing unit can prioritize providing resources related to relaxation or rest. In this way, the resource providing unit can determine the priority of resources according to the user's emotions and provide more appropriate resources. Emotions can be estimated using methods such as facial expression recognition, voice analysis, and questionnaire results. Methods for determining the priority of resources include, for example, the user's emotion score and the importance of resources. In this way, the resource providing unit can estimate the user's emotions and determine the priority of resources based on the estimated emotions.

[0074] The resource providing unit can provide resources with priority based on the user's geographical location information when providing resources. For example, the resource providing unit can provide resources for nearby events or workshops based on the user's current location. Furthermore, if the user is interested in a particular area, the resource providing unit can also provide resources related to that area with priority. Furthermore, if the user is traveling, the resource providing unit can provide resources for the user's travel destination or tourist attractions. This allows the resource providing unit to provide more appropriate support by providing resources with high relevance based on the user's geographical location information. Examples of methods for collecting and using geographical location information include GPS data and IP addresses. This allows the resource providing unit to provide resources with high relevance based on the user's geographical location information when providing resources with priority.

[0075] The resource providing unit can analyze the user's social media activity and provide related resources when providing resources. The resource providing unit can provide related resources based on, for example, content shared by the user on social media. The resource providing unit can also provide resources that the user is likely to be interested in based on accounts and groups the user follows. Furthermore, the resource providing unit can provide resources related to events the user is participating in on social media. This allows the resource providing unit to provide more appropriate support by providing related resources based on the user's social media activity. Methods for collecting and analyzing social media activity include, for example, post content, the number of likes, and the number of followers. This allows the resource providing unit to analyze the user's social media activity and provide related resources when providing resources.

[0076] The tool providing unit can estimate the user's emotions and adjust the content of the tools to be provided based on the estimated emotions. For example, if the user is feeling stressed, the tool providing unit can provide tools related to relaxation methods and stress relief. Furthermore, if the user is feeling happy, the tool providing unit can provide positive experiences and success stories. Furthermore, if the user is feeling anxious, the tool providing unit can provide encouraging messages and support tools that give a sense of security. In this way, the tool providing unit can provide more appropriate support by providing tools according to the user's emotions. Emotions are estimated using methods such as facial expression recognition, voice analysis, and questionnaire results. In this way, the tool providing unit can estimate the user's emotions and adjust the content of the tools to be provided based on the estimated emotions.

[0077] When providing a tool, the tool providing unit can analyze the user's past usage history and select an appropriate tool. For example, the tool providing unit can provide new related tools based on tools the user has used in the past. The tool providing unit can also provide the latest tools and trends based on tools the user frequently uses. Furthermore, the tool providing unit can suggest tools that the user may be interested in by referring to tools the user has saved in the past. In this way, the tool providing unit can provide the optimal tool based on the user's past usage history, thereby providing tools that meet the user's interests and needs. Methods for collecting and analyzing past usage history include, for example, app usage history and download history. In this way, the tool providing unit can analyze the user's past usage history and select an appropriate tool when providing a tool.

[0078] The tool providing unit can filter tools based on the user's current living situation or areas of interest when providing the tools. For example, when the user inputs their current living situation, the tool providing unit provides tools appropriate to the situation. Furthermore, when the user selects an area of ​​interest, the tool providing unit can preferentially provide tools related to that area. Furthermore, when the user sets a specific goal, the tool providing unit can provide tools that are useful for achieving the goal. In this way, the tool providing unit can provide more appropriate support by providing tools according to the user's living situation or areas of interest. Methods for filtering tools include, for example, the user's living situation and areas of interest. In this way, the tool providing unit can filter tools based on the user's current living situation and areas of interest when providing the tools.

[0079] The tool providing unit can estimate the user's emotions and determine the priority of tools based on the estimated emotions. For example, if the user is sad, the tool providing unit can prioritize providing tools that encourage or comfort the user. Furthermore, if the user is excited, the tool providing unit can prioritize providing new tools that will attract the user's attention. Furthermore, if the user is tired, the tool providing unit can prioritize providing tools related to relaxation or rest. In this way, the tool providing unit can determine the priority of tools according to the user's emotions and provide more appropriate tools. Emotion estimation is performed using methods such as facial expression recognition, voice analysis, and survey results. Methods for determining the priority of tools include, for example, the user's emotion score and the importance of tools. In this way, the tool providing unit can estimate the user's emotions and determine the priority of tools based on the estimated emotions.

[0080] When providing tools, the tool providing unit can prioritize providing highly relevant tools based on the user's geographical location information. For example, the tool providing unit can provide tools for nearby events or workshops based on the user's current location. Furthermore, if the user is interested in a particular region, the tool providing unit can prioritize providing tools related to that region. Furthermore, if the user is traveling, the tool providing unit can provide tools for travel destinations or tourist spots. This allows the tool providing unit to provide more appropriate support by providing highly relevant tools based on the user's geographical location information. Examples of methods for collecting and using geographical location information include GPS data and IP addresses. This allows the tool providing unit to prioritize providing highly relevant tools based on the user's geographical location information when providing tools.

[0081] The tool providing unit can analyze the user's social media activities and provide related tools when providing the tools. For example, the tool providing unit can provide related tools based on content shared by the user on social media. The tool providing unit can also provide tools that the user may be interested in based on accounts and groups the user follows. Furthermore, the tool providing unit can provide tools related to events the user is participating in on social media. This allows the tool providing unit to provide more appropriate support by providing related tools based on the user's social media activities. Methods for collecting and analyzing social media activities include, for example, post content, the number of likes, and the number of followers. This allows the tool providing unit to analyze the user's social media activities and provide related tools when providing the tools.

[0082] The participation acceptance unit can estimate the user's emotions and adjust the participation acceptance method based on the estimated emotions. For example, if the user is nervous, the participation acceptance unit can provide a simple and intuitive acceptance method. Furthermore, if the user is relaxed, the participation acceptance unit can provide detailed options and suggest a customizable acceptance method. Furthermore, if the user is in a hurry, the participation acceptance unit can prioritize voice input and quickly accept participation. This allows the participation acceptance unit to provide more appropriate support by providing a participation acceptance method that corresponds to the user's emotions. Emotions can be estimated using methods such as facial expression recognition, voice analysis, and questionnaire results. This allows the participation acceptance unit to estimate the user's emotions and adjust the participation acceptance method based on the estimated emotions.

[0083] The participation acceptance unit can analyze the user's past participation history and select an appropriate participation method when accepting participation. The participation acceptance unit, for example, suggests a related new event based on the history of events the user has previously participated in. The participation acceptance unit can also suggest an optimal participation method based on the type of events the user frequently participates in. Furthermore, the participation acceptance unit can suggest events that the user may be interested in by referring to events that the user has saved in the past. In this way, the participation acceptance unit can provide an optimal participation method based on the user's past participation history, thereby providing a participation method that meets the user's interests and needs. Methods for collecting and analyzing past participation history include, for example, event participation history and seminar participation history. In this way, the participation acceptance unit can analyze the user's past participation history and select an appropriate participation method when accepting participation.

[0084] The participation acceptance unit can perform filtering based on the user's current living situation or areas of interest when accepting participation. For example, when the user inputs their current living situation, the participation acceptance unit can suggest events that are appropriate for that situation. Furthermore, when the user selects an area of ​​interest, the participation acceptance unit can also preferentially suggest events related to that area. Furthermore, when the user sets a specific goal, the participation acceptance unit can also suggest events that will help achieve that goal. In this way, the participation acceptance unit can provide more appropriate support by offering participation methods that correspond to the user's living situation and areas of interest. Methods for filtering participation include, for example, the user's living situation and areas of interest. In this way, the participation acceptance unit can perform filtering based on the user's current living situation and areas of interest when accepting participation.

[0085] The participation acceptance unit can estimate the user's emotions and determine the priority of participation based on the estimated emotions. For example, if the user is sad, the participation acceptance unit can prioritize encouraging and comforting events. Furthermore, if the user is excited, the participation acceptance unit can prioritize interesting new events. Furthermore, if the user is tired, the participation acceptance unit can prioritize relaxing and resting events. In this way, the participation acceptance unit can provide more appropriate support by determining the priority of participation based on the user's emotions. Emotions can be estimated using methods such as facial expression recognition, voice analysis, and questionnaire results. Methods for determining the priority of participation include, for example, the user's emotion score and the importance of participation. In this way, the participation acceptance unit can estimate the user's emotions and determine the priority of participation based on the estimated emotions.

[0086] The participation acceptance unit can prioritize accepting participation based on the user's geographical location information when accepting participation. For example, the participation acceptance unit can prioritize accepting participation for nearby events or workshops based on the user's current location. Furthermore, if the user is interested in a particular region, the participation acceptance unit can prioritize accepting participation for events related to that region. Furthermore, if the user is traveling, the participation acceptance unit can prioritize accepting participation for events or tourist spots at the user's travel destination. This allows the participation acceptance unit to provide more appropriate support by providing participation methods that are highly relevant based on the user's geographical location information. Examples of methods for collecting and using geographical location information include GPS data and IP addresses. This allows the participation acceptance unit to prioritize accepting participation based on the user's geographical location information when accepting participation.

[0087] The participation acceptance unit can analyze the user's social media activity and accept related participations when accepting participations. The participation acceptance unit can, for example, accept participations for related events based on content shared by the user on social media. The participation acceptance unit can also accept participations for events that the user is likely to be interested in based on accounts and groups the user follows. Furthermore, the participation acceptance unit can accept participations related to events the user is participating in on social media. This allows the participation acceptance unit to provide more appropriate support by providing related participation methods based on the user's social media activity. Methods for collecting and analyzing social media activity include, for example, post content, the number of likes, the number of followers, etc. This allows the participation acceptance unit to analyze the user's social media activity and accept related participations when accepting participations. === Hard Collateral 1-1 === Each of the multiple elements, including the information providing unit, resource providing unit, tool providing unit, and participation accepting unit, described above, is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the information providing unit is realized by the output device 40 of the smart device 14 or the specific processing unit 290 of the data processing device 12 and provides articles and videos related to mental health. The resource providing unit is realized by the specific processing unit 290 of the data processing device 12 and provides educational materials and guidebooks for self-development. The tool providing unit is realized by the control unit 46A of the smart device 14 or the specific processing unit 290 of the data processing device 12 and provides communication tools for relationship building. The participation accepting unit is realized by the reception device 38 of the smart device 14 or the specific processing unit 290 of the data processing device 12 and accepts participation in a seminar for career development. === Hard Collateral 1-2 === Each of the multiple elements, including the information provider, resource provider, tool provider, and participation acceptance unit, described above, is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the information provider is realized by the speaker 240 of the smart glasses 214 or the specific processing unit 290 of the data processing device 12 and provides articles and videos related to mental health. The resource provider is realized by the specific processing unit 290 of the data processing device 12 and provides educational materials and guidebooks for self-development. The tool provider is realized by the control unit 46A of the smart glasses 214 or the specific processing unit 290 of the data processing device 12 and provides communication tools for relationship building. The participation acceptance unit is realized by the microphone 238 of the smart glasses 214 or the specific processing unit 290 of the data processing device 12 and accepts participation in a seminar for career development. === Hard Collateral 1-3 === Each of the multiple elements including the information provider, resource provider, tool provider, and participation acceptance unit described above is realized, for example, by at least one of the headset terminal 314 and the data processing device 12. For example, the information provider is realized by the display 343 of the headset terminal 314 or the specific processing unit 290 of the data processing device 12 and provides articles and videos related to mental health. The resource provider is realized by the specific processing unit 290 of the data processing device 12 and provides educational materials and guidebooks for self-development. The tool provider is realized by the control unit 46A of the headset terminal 314 or the specific processing unit 290 of the data processing device 12 and provides communication tools for relationship building. The participation acceptance unit is realized by the microphone 238 of the headset terminal 314 or the specific processing unit 290 of the data processing device 12 and accepts participation in a seminar for career development. === Hard Collateral 1-4 === Each of the multiple elements including the information providing unit, resource providing unit, tool providing unit, and participation accepting unit described above is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the information providing unit is realized by the speaker 240 of the robot 414 or the specific processing unit 290 of the data processing device 12 and provides articles and videos related to mental health. The resource providing unit is realized by the specific processing unit 290 of the data processing device 12 and provides educational materials and guidebooks for self-development. The tool providing unit is realized by the control unit 46A of the robot 414 or the specific processing unit 290 of the data processing device 12 and provides communication tools for relationship building. The participation accepting unit is realized by the microphone 238 of the robot 414 or the specific processing unit 290 of the data processing device 12 and accepts participation in a seminar for career development.

[0088] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0089] The community system may further include a health monitoring unit that monitors the user's health status. The health monitoring unit obtains data from the user's fitness tracker or smartwatch and monitors the user's health status in real time. For example, it may monitor the user's heart rate, sleep patterns, exercise volume, etc., and send an alert if an abnormality is detected. The health monitoring unit may also provide appropriate health advice and resources based on the user's health data. This allows users to not only improve themselves but also manage their health at the same time.

[0090] The information providing unit can estimate the user's emotions and adjust the format of the information to be provided based on the estimated emotions. For example, if the user is feeling stressed, relaxing music or a meditation guide can be provided. If the user is feeling happy, positive video messages or success stories can be provided. Furthermore, if the user is feeling anxious, reassuring text messages or support information can be provided. In this way, the information providing unit can provide more appropriate support by providing the format of information according to the user's emotions.

[0091] The resource provider can customize resources based on a user's learning style. For example, it can provide videos and infographics for visual learners, podcasts and audiobooks for auditory learners, and interactive workshops and hands-on materials for hands-on learners. Furthermore, the resource provider can continuously improve the content of resources based on user feedback. This allows the resource provider to provide resources tailored to a user's learning style, thereby more effectively supporting self-development.

[0092] The tool providing unit can estimate the user's emotions and adjust the interface of the tool to be provided based on the estimated emotions. For example, if the user is feeling stressed, a simple and intuitive interface can be provided. If the user is feeling happy, a colorful and interactive interface can be provided. Furthermore, if the user is feeling anxious, a calming interface that gives a sense of security can be provided. In this way, the tool providing unit can provide more appropriate support by providing an interface that corresponds to the user's emotions.

[0093] The participation acceptance unit can analyze the user's past participation history and send appropriate reminders. For example, it can send reminders for events the user has previously participated in, encouraging the user to participate again. It can also send reminders for new events based on the types of events the user frequently participates in. It can also send reminders for events that the user may be interested in, referring to events that the user has saved in the past. In this way, the participation acceptance unit can provide optimal reminders based on the user's past participation history, thereby offering a participation method that suits the user's interests and needs.

[0094] The information providing unit can estimate the user's emotions and adjust the timing of information delivery based on the estimated emotions. For example, if the user is feeling stressed, relaxing information can be delivered at night. If the user is feeling happy, positive information can be delivered in the morning. Furthermore, if the user is feeling anxious, information that gives a sense of security can be delivered during the day. In this way, the information providing unit can provide more appropriate support by providing information delivery timing that corresponds to the user's emotions.

[0095] The resource providing unit can provide local resources based on the user's geographical location information. For example, resources for nearby libraries or community centers can be provided based on the user's current location. Also, if the user is interested in a particular area, resources related to that area can be provided. Furthermore, if the user is traveling, resources for travel destinations and tourist attractions can be provided. This allows the resource providing unit to provide more appropriate support by providing highly relevant resources based on the user's geographical location information.

[0096] The tool providing unit can estimate the user's emotions and provide guidance on how to use the tool based on the estimated emotions. For example, if the user is feeling stressed, the tool providing unit can provide guidance on relaxation methods and stress relief. If the user is feeling happy, the tool providing unit can provide positive experiences and success stories. Furthermore, if the user is feeling anxious, the tool providing unit can provide encouraging messages and support tools that give a sense of security. In this way, the tool providing unit can provide more appropriate support by providing guidance on how to use the tool according to the user's emotions.

[0097] The participation acceptance unit can analyze the user's social media activity and suggest related events to participate in. For example, it can suggest related events to participate in based on content the user has shared on social media. It can also suggest events that the user may be interested in based on accounts and groups the user follows. It can also suggest participation related to events the user is participating in on social media. This allows the participation acceptance unit to provide more appropriate support by offering relevant participation methods based on the user's social media activity.

[0098] The information providing unit can estimate the user's emotions and collect information feedback based on the estimated emotions. For example, if the user is feeling stressed, feedback on relaxation methods can be collected. If the user is feeling happy, feedback on positive experiences and success stories can be collected. Furthermore, if the user is feeling anxious, feedback on information that gives a sense of security can be collected. In this way, the information providing unit can provide more appropriate information by collecting feedback according to the user's emotions.

[0099] The processing flow of the second embodiment will be briefly explained below.

[0100] Step 1: The resource department provides information on a variety of topics of interest to women, including articles and videos on mental health, self-improvement workshops, relationship-building forums, and career advancement seminars. Step 2: The Resource Unit uses the information provided by the Information Unit to provide resources to help women achieve personal growth, such as mental health guidebooks, self-development materials, relationship-building toolkits, and online courses for career advancement. Step 3: The tool provider provides women with tools to achieve personal growth based on the resources provided by the resource provider, such as apps to support mental health, online platforms for self-development, communication tools for relationship building, and networking tools for career advancement. Step 4: The Participation Acceptance Unit accepts participants to use the tools provided by the Tool Provider Unit, such as attending a mental health workshop, enrolling in an online course for personal development, participating in a forum for relationship building, or attending a seminar for career development.

[0101] 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.

[0102] 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 the generative AI include a neural network (NN) and a neural network (NN). 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 (e.g., still image data or video data). 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 one or more data formats of voice data, text data, image data, etc. 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 may perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-mentioned parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. The processing performed by an AI including the generative AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI including the generative AI.

[0103] 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.

[0104] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0105] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0106] 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.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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).

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0119] 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.

[0120] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0121] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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).

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0135] 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.

[0136] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0137] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0138] 7, a 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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).

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0152] 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.

[0153] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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).

[0158] 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.

[0159] 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."

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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, in order to avoid confusion and to 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.

[0171] 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.

[0172] [Explanation of symbols]

[0173] 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. an information providing unit that provides information; a resource providing unit that provides resources based on the information provided by the information providing unit; a tool providing unit that provides a tool based on the resource provided by the resource providing unit; a participation acceptance unit that accepts participation to use the tool provided by the tool providing unit; Equipped with A system characterized by:

2. The information providing unit Providing information about mental health 2. The system of claim 1.

3. The resource providing unit Providing resources for personal growth 2. The system of claim 1.

4. The tool providing unit Providing tools to help build relationships 2. The system of claim 1.

5. The participation acceptance unit Accepting participation in career growth 2. The system of claim 1.

6. The information providing unit Estimate the user's emotions and adjust the content of the information provided based on the estimated emotions.

2. The system of claim 1.

7. The information providing unit Analyze users' past browsing history and select appropriate information 2. The system of claim 1.

8. The information providing unit Filter information based on the user's current life situation or interests 2. The system of claim 1.

9. The information providing unit Estimate the user's emotions and prioritize information based on the estimated emotions 2. The system of claim 1.

10. The information providing unit When providing information, it prioritizes providing relevant information based on the user's geographic location.

2. The system of claim 1.

Images