system

Abstract

The system according to the embodiment aims to efficiently design a plan based on the content of an experience. [Solution] A system according to an embodiment includes a reception unit, an analysis unit, and a design unit. The reception unit inputs specific experience content. The analysis unit analyzes the information received by the reception unit. The design unit designs a plan based on the results of the analysis by the analysis 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] With conventional technology, the process of designing the optimal plan based on the experience content was time-consuming and inefficient.

[0005] The system according to the embodiment aims to efficiently design a plan based on the content of an experience. [Means for solving the problem]

[0006] The system according to the embodiment includes a reception unit, an analysis unit, and a design unit. The reception unit inputs specific experience content. The analysis unit analyzes the information received by the reception unit. The design unit designs a plan based on the results of the analysis by the analysis unit. [Effects of the Invention]

[0007] The system according to the embodiment can efficiently design a plan based on the content of the experience. [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 travel plan design system according to an embodiment of the present invention is a system that designs all the destinations, number of days, route, cost, etc., when a user inputs the experiences they want to have. This travel plan design system allows a generation AI to analyze the experiences and design the optimal destinations, number of days, route, and cost. The resulting design is provided to the user. For example, a user inputs the experiences they want to have, such as "I want to enjoy nature" or "I want to visit historical sites." This information is input into the generation AI, which then analyzes the input information. Based on the user's preferences, the generation AI designs the optimal destinations, number of days, route, and cost. For example, in response to a request to "enjoy nature," the generation AI suggests natural locations such as mountains and lakes and designs the number of days to stay, route, and budget. The designed destinations, number of days, route, and cost are provided to the user. The user can plan their trip based on the proposed plan. For example, they can plan a trip according to the destinations and routes suggested by the generation AI and enjoy it within their budget. This system allows users to easily have the optimal travel plan designed to suit their preferences. The generation AI designs all the destinations, number of days, route, and cost, allowing users to enjoy their trip without any hassle. This allows the travel plan design system to provide the optimal travel plan based on the user's wishes.

[0029] The travel plan design system according to the embodiment includes a reception unit, an analysis unit, and a design unit. The reception unit is a component for inputting specific experiences the user wants to have. Examples of experiences the user wants to have include, but are not limited to, trips, events, and activities. The reception unit supports, for example, both text input and selection from options. Text input includes free description and standard phrases. Selection from options includes drop-down menus and radio buttons. The analysis unit analyzes the information received by the reception unit. The analysis unit analyzes the information using methods such as data analysis, text analysis, and sentiment analysis. The analysis unit generates basic data for designing optimal destinations, number of days, route, and cost based on the user's preferences. The design unit designs a plan based on the results of the analysis by the analysis unit. The design unit designs, for example, a travel plan, an event plan, an activity plan, etc. The design unit specifically designs destinations, number of days, route, and cost. Criteria for selecting a destination include tourist attractions, restaurants, accommodations, etc. The criteria for setting the number of days include the duration of the trip and the number of days of stay. The criteria for designing the route include the means of transportation and stopovers. The cost calculation method includes the budget and cost items. This allows the travel plan design system to provide the optimal travel plan based on the user's wishes.

[0030] The design unit can design specific destinations, number of days, routes, and costs. For example, to select a destination, the design unit collects information on tourist attractions, restaurants, accommodations, etc., and suggests the optimal destination. Furthermore, to set the number of days, the design unit can consider the travel period and number of days of stay and suggest the optimal number of days. Furthermore, to design a route, the design unit can consider the means of transportation and stopovers and suggest the optimal route. To calculate costs, the design unit can consider budget and cost items and suggest the optimal cost. For example, the design unit collects information on tourist attractions and suggests the optimal destination based on the user's preferences. Furthermore, the design unit can consider the travel period and number of days of stay and suggest the optimal number of days. Furthermore, the design unit can consider the means of transportation and stopovers and suggest the optimal route. To calculate costs, the design unit can consider the budget and cost items and suggest the optimal cost. In this way, the design unit can provide a travel plan based on the user's preferences.

[0031] The travel plan design system includes a providing unit that provides the user with a specific plan designed by the design unit. The providing unit is a component that provides the user with the plan designed by the design unit. The providing unit can provide the plan in the form of, for example, email, PDF file, or web page. The providing unit has a function that allows the user to easily check the designed plan. For example, the providing unit can provide the designed plan in PDF format. The method of providing the PDF format includes criteria such as file size and layout. The providing unit can also send the designed plan by email. The method of providing the email includes criteria such as email address registration and timing of sending. The providing unit can also display the designed plan on a web page. The method of providing the web page includes criteria such as page layout and navigation design. This allows the providing unit to easily check the designed plan and plan a trip.

[0032] The travel plan design system includes a modification unit that allows a user to modify a plan provided by the provision unit. The modification unit is a component that allows a user to modify a plan provided by the provision unit. The modification unit, for example, has a function of accepting user feedback and modifying a plan. The modification unit allows a user to modify the provided plan to suit their own preferences. For example, the modification unit provides an interface that allows a user to modify the plan's destination, number of days, route, cost, etc. The modification unit sets criteria for modifying the plan based on user feedback. For example, if a user wants to change the destination, the modification unit can suggest a new destination based on the user's preferences. Also, if a user wants to change the number of days, the modification unit can suggest a new number of days based on the user's preferences. Furthermore, if a user wants to change the route, the modification unit can suggest a new route based on the user's preferences. When modifying the cost, the modification unit can consider budgets and cost items and suggest an optimal cost. This allows the modification unit to modify the provided plan to suit the user's preferences and create a travel plan that better suits them.

[0033] The reception unit can support both specific text input and a format for selecting from options. The reception unit is a component for inputting the content of an experience the user wants to have. The reception unit supports, for example, both text input and a format for selecting from options. Text input includes free description and standard phrases. Formats for selecting from options include drop-down menus and radio buttons. For example, the reception unit provides a text input field in which the user can freely describe the content of the experience. The reception unit can also provide an interface in which the user can select the content of the experience from options. This allows the reception unit to input the content of the experience according to the user's preferences. Furthermore, the reception unit can estimate the user's emotions and adjust the input method for the content of the experience based on the estimated user emotions. For example, if the user is feeling stressed, the reception unit can provide a simple interface and minimize the input steps. On the other hand, if the user is relaxed, the reception unit can provide detailed input options and suggest a customizable input method. Furthermore, if the user is in a hurry, the reception unit can prioritize voice input to allow the user to quickly input the content of the experience. This allows the reception unit to provide the optimal input method according to the user's emotions.

[0034] The providing unit can provide the design results in PDF format. The providing unit is a component that provides the plan designed by the design unit to the user. The providing unit can, for example, provide the design results in PDF format. The method of providing the PDF format includes criteria such as file size and layout. For example, the providing unit can generate the design results as a PDF file and provide it to the user. The providing unit can also adjust the layout of the PDF file to allow the user to easily check the plan. Furthermore, the providing unit can optimize the file size of the PDF file to make it easier for the user to download the file. In this way, the providing unit can provide the design results in PDF format to allow the user to easily check the plan.

[0035] The reception unit can analyze the user's past input history and suggest the optimal input format. The reception unit is a component for the user to input the content they want to experience. The reception unit can, for example, analyze the user's past input history and suggest the optimal input format. Analysis of the input history includes past input data and frequency of use. For example, the reception unit can automatically display experience content that the user has frequently input in the past as candidates. The reception unit can also preferentially suggest input methods (voice, text, etc.) that the user has used in the past. Furthermore, the reception unit can predict and suggest the experience content that will be used in a specific time period based on the user's past input history. This allows the reception unit to provide the optimal input format based on the user's past input history.

[0036] The reception unit can present input candidates based on the user's current interests and concerns when inputting experience content. The reception unit is a component for inputting the content the user wants to experience. For example, the reception unit can present input candidates based on the user's current interests and concerns when inputting experience content. Identification of interests and concerns includes survey results, past behavioral history, and the like. For example, the reception unit presents related experience content as candidates based on keywords recently searched by the user. The reception unit can also analyze posts that the user has "liked" on social media and suggest related experience content. Furthermore, the reception unit can present related experience content as candidates based on events that the user recently participated in. This allows the reception unit to suggest more appropriate experience content based on the user's interests and concerns.

[0037] The reception unit can present highly relevant input candidates in consideration of the user's geographical location information when the user inputs experience content. The reception unit is a component for inputting the content the user wants to experience. For example, the reception unit can present highly relevant input candidates in consideration of the user's geographical location information when the user inputs experience content. Examples of acquired geographical location information include GPS data and location information services. For example, the reception unit can preferentially display experience content in locations close to the user's current location. Furthermore, if the user is traveling, the reception unit can preferentially display experience content at the user's travel destination. Furthermore, if the user is interested in a specific region, the reception unit can also preferentially display experience content related to that region. In this way, the reception unit can provide more relevant experience content in consideration of the user's geographical location information.

[0038] The reception unit can analyze the user's social media activity when inputting experience content and present related input candidates. The reception unit is a component for inputting the experience content the user wants to have. For example, the reception unit can analyze the user's social media activity when inputting experience content and present related input candidates. Analysis of social media activity includes the content of posts, the number of likes, the number of followers, etc. For example, the reception unit presents related experience content as candidates based on posts that the user has "liked" on social media. The reception unit can also analyze posts from accounts the user follows on social media and suggest related experience content. Furthermore, the reception unit can present related experience content as candidates based on posts the user has shared on social media. This allows the reception unit to provide more relevant experience content based on the user's social media activity.

[0039] The analysis unit can improve the accuracy of the analysis by referring to the user's past travel history during analysis. The analysis unit is a component for analyzing information received by the reception unit. The analysis unit can improve the accuracy of the analysis by, for example, referring to the user's past travel history during analysis. Reference to the travel history includes past travel data and records of places visited. For example, the analysis unit can suggest related destinations based on places the user has visited in the past. The analysis unit can also analyze the user's preferred travel style from the user's past travel history and suggest an optimal plan. Furthermore, the analysis unit can also suggest an optimal route based on the means of transportation used by the user in the past. This allows the analysis unit to provide more accurate analysis results based on the user's past travel history.

[0040] The analysis unit can customize the analysis results based on the user's current living situation and areas of interest during analysis. The analysis unit is a component for analyzing the information received by the reception unit. The analysis unit can customize the analysis results based on the user's current living situation and areas of interest during analysis, for example. Identifying living situations includes occupation, family composition, income, etc. Identifying areas of interest includes hobbies and topics of interest, etc. For example, the analysis unit can suggest an appropriate travel plan based on the user's current living situation. The analysis unit can also suggest related destinations based on the user's areas of interest (nature, history, art, etc.). Furthermore, the analysis unit can suggest a reasonable travel plan taking into account the user's current health condition. This allows the analysis unit to provide more appropriate analysis results based on the user's living situation and areas of interest.

[0041] The analysis unit can customize the analysis results by taking into account the user's geographical location information during analysis. The analysis unit is a component for analyzing the information received by the reception unit. For example, the analysis unit can customize the analysis results by taking into account the user's geographical location information during analysis. Acquisition of geographical location information includes GPS data, location information services, and the like. For example, the analysis unit can prioritize displaying experience content in locations close to the user's current location. Furthermore, if the user is traveling, the analysis unit can prioritize displaying experience content at the user's travel destination. Furthermore, if the user is interested in a specific region, the analysis unit can also prioritize displaying experience content related to that region. In this way, the analysis unit can provide more relevant analysis results by taking into account the user's geographical location information.

[0042] The analysis unit can analyze the user's social media activity during the analysis and provide related analysis results. The analysis unit is a component for analyzing the information received by the reception unit. For example, the analysis unit can analyze the user's social media activity during the analysis and provide related analysis results. Analysis of social media activity includes the content of posts, the number of likes, the number of followers, etc. For example, the analysis unit can provide related experience content as analysis results based on posts that the user has "liked" on social media. The analysis unit can also analyze posts from accounts that the user follows on social media and suggest related experience content. Furthermore, the analysis unit can also provide related experience content as analysis results based on posts that the user has shared on social media. This allows the analysis unit to provide more relevant analysis results based on the user's social media activity.

[0043] The design unit can design an optimal plan by referring to the user's past travel history during design. The design unit is a component for designing a plan based on the results of analysis by the analysis unit. For example, the design unit can design an optimal plan by referring to the user's past travel history during design. Reference to travel history includes past travel data and records of places visited. For example, the design unit can suggest related destinations based on places the user has visited in the past. The design unit can also analyze the user's preferred travel style from the user's past travel history and suggest an optimal plan. Furthermore, the design unit can suggest an optimal route based on the means of transportation the user has used in the past. This allows the design unit to provide a more appropriate plan based on the user's past travel history.

[0044] The design unit can customize the plan based on the user's current living situation and areas of interest during design. The design unit is a component for designing a plan based on the results of analysis by the analysis unit. For example, the design unit can customize the plan based on the user's current living situation and areas of interest during design. Identifying living situations includes occupation, family composition, income, etc. Identifying areas of interest includes hobbies and topics of interest, etc. For example, the design unit proposes an appropriate travel plan based on the user's current living situation. The design unit can also propose related destinations based on the user's areas of interest (nature, history, art, etc.). Furthermore, the design unit can propose a reasonable travel plan taking into account the user's current health condition. This allows the design unit to provide a more appropriate plan based on the user's living situation and areas of interest.

[0045] The design unit can design an optimal plan taking into account the user's geographical location information during design. The design unit is a component for designing a plan based on the results of analysis by the analysis unit. For example, the design unit can design an optimal plan taking into account the user's geographical location information during design. Examples of acquired geographical location information include GPS data and location information services. For example, the design unit prioritizes designing experience content in locations close to the user's current location. Also, if the user is traveling, the design unit can prioritize designing experience content at the user's travel destination. Furthermore, if the user is interested in a specific region, the design unit can also prioritize designing experience content related to that region. This allows the design unit to provide a more relevant plan taking into account the user's geographical location information.

[0046] The design unit can analyze the user's social media activity during design and design a related plan. The design unit is a component for designing a plan based on the results of analysis by the analysis unit. For example, the design unit can analyze the user's social media activity during design and design a related plan. Analysis of social media activity includes the content of posts, the number of likes, the number of followers, etc. For example, the design unit can incorporate related experience content into the plan based on posts that the user has "liked" on social media. The design unit can also analyze posts from accounts that the user follows on social media and suggest related experience content. Furthermore, the design unit can incorporate related experience content into the plan based on posts that the user has shared on social media. This allows the design unit to provide a more relevant plan based on the user's social media activity.

[0047] The providing unit can select the optimal delivery method by referring to the user's past feedback when providing the plan. The providing unit is a component for providing the plan designed by the design unit to the user. For example, the providing unit can select the optimal delivery method by referring to the user's past feedback when providing the plan. Reference to feedback includes survey results, user comments, and the like. For example, the providing unit preferentially selects a delivery method (email, in-app notification, etc.) that the user has previously preferred. Furthermore, the providing unit can select a detailed delivery method if the user's past feedback indicates that detailed explanations are preferred. Furthermore, the providing unit can select a visually attractive delivery method based on the user's past feedback. This allows the providing unit to select a more appropriate delivery method based on the user's past feedback.

[0048] The provision unit can select the optimal provision method by taking into account the user's device information when providing the plan. The provision unit is a component for providing the plan designed by the design unit to the user. For example, the provision unit can select the optimal provision method by taking into account the user's device information when providing the plan. Acquired device information includes the device type and OS version. For example, if the user is using a smartphone, the provision unit selects a provision method that matches the screen size. Furthermore, if the user is using a tablet, the provision unit can select a provision method that is optimized for a large screen. Furthermore, if the user is using a smartwatch, the provision unit can select a provision method that is concise and highly visible. This allows the provision unit to select a more appropriate provision method by taking into account the user's device information.

[0049] The correction unit can suggest the optimal correction method by referring to the user's past correction history when making a correction. The correction unit is a component that allows the user to correct the plan provided by the provision unit. For example, the correction unit can suggest the optimal correction method by referring to the user's past correction history when making a correction. The reference to the correction history includes the content of past corrections and the frequency of corrections. For example, the correction unit can suggest related correction options based on the content of corrections made by the user in the past. The correction unit can also analyze the user's preferred correction style from the user's past correction history and suggest the optimal option. Furthermore, the correction unit can preferentially suggest correction methods (such as voice or text) that the user has used in the past. This allows the correction unit to provide a more appropriate correction method based on the user's past correction history.

[0050] The correction unit can propose an optimal correction method by taking into account the user's device information when making corrections. The correction unit is a component that allows the user to correct the plan provided by the provision unit. For example, the correction unit can propose an optimal correction method by taking into account the user's device information when making corrections. Acquired device information includes the device type and OS version. For example, if the user is using a smartphone, the correction unit can propose a correction method that matches the screen size. Furthermore, if the user is using a tablet, the correction unit can propose a correction method that is optimized for a large screen. Furthermore, if the user is using a smartwatch, the correction unit can propose a simple and highly visible correction method. This allows the correction unit to provide a more appropriate correction method by taking into account the user's device information.

[0051] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0052] The travel plan design system can further include a health management unit that takes into account the user's health condition. The health management unit can acquire the user's health data (e.g., heart rate, number of steps, sleep time, etc.) and reflect it in the design of the travel plan. For example, if the user gets tired easily, the health management unit can suggest a plan that includes plenty of rest time. Also, if the user has an active lifestyle, the health management unit can suggest a plan that includes activities such as hiking or cycling. Furthermore, if the user has specific health restrictions (e.g., dietary restrictions or allergies), the health management unit can also select restaurants and accommodations that accommodate those restrictions. This allows the travel plan design system to provide an optimal travel plan that suits the user's health condition.

[0053] The travel plan design system can further include a history reference unit that references the user's past travel history. The history reference unit records the places the user has visited and the activities the user has experienced in the past, and can refer to these when designing the next travel plan. For example, the system can suggest related new destinations based on the places the user has visited in the past. It can also suggest similar activities based on the activities the user has preferred in the past. It can also suggest optimal options based on the ratings of transportation methods and accommodations the user has used in the past. This allows the travel plan design system to provide a more personalized travel plan based on the user's past travel history.

[0054] The travel plan design system can further include a social media analysis unit that analyzes the user's social media activity. The social media analysis unit can analyze posts that the user has "liked" and content that the user has shared on social media and reflect the results in the design of the travel plan. For example, the social media analysis unit can suggest related tourist spots and activities based on posts that the user has "liked." It can also design travel plans related to themes of interest based on content that the user has shared. It can also analyze posts from accounts that the user follows and suggest related experiences. This allows the travel plan design system to provide more relevant travel plans based on the user's social media activity.

[0055] The travel plan design system can further include a lifestyle situation analysis unit that takes into account the user's current lifestyle situation. The lifestyle situation analysis unit can acquire information such as the user's occupation, family composition, and income, and reflect this in the design of the travel plan. For example, if the user has a busy job, the system can suggest a plan that allows them to refresh themselves in a short period of time. Also, if the user is traveling with their family, the system can suggest a plan that includes activities that the whole family can enjoy. Furthermore, the system can design a travel plan that can be enjoyed within the user's budget based on the user's income. This allows the travel plan design system to provide the optimal travel plan that suits the user's lifestyle situation.

[0056] The travel plan design system can further include a location information analysis unit that takes into account the user's geographical location information. The location information analysis unit can acquire location information of the user's current location and travel destination and reflect it in the design of the travel plan. For example, if the user wishes to travel to a location close to their current location, the location information analysis unit can suggest nearby tourist attractions and activities. Also, if the user is interested in a specific area, the system can design a travel plan related to that area. Furthermore, if the user is traveling, the system can prioritize suggestions for experiences at the travel destination. This allows the travel plan design system to provide more relevant travel plans based on the user's geographical location information.

[0057] The processing flow of the first embodiment will be briefly explained below.

[0058] Step 1: The reception unit is a section for inputting the specific content of the experience the user wants to have. The content of the experience the user wants to have includes, but is not limited to, travel, events, activities, etc. The reception unit supports, for example, both text input and a format for selecting from options. Text input includes free description and standard phrases. Formats for selecting from options include drop-down menus and radio buttons. Step 2: The analysis unit analyzes the information received by the reception unit. The analysis unit analyzes the information using methods such as data analysis, text analysis, and sentiment analysis. The analysis unit generates basic data for designing the optimal destination, number of days, route, and cost based on the user's preferences. Step 3: The design section designs a plan based on the results of the analysis performed by the analysis section. The design section designs, for example, travel plans, event plans, activity plans, etc. The design section specifically designs destinations, number of days, route, and cost. Criteria for selecting destinations include tourist spots, restaurants, accommodations, etc. Criteria for setting number of days include travel period and number of days of stay, etc. Criteria for designing routes include means of transportation, stopovers, etc. Cost calculation methods include budgets, cost items, etc.

[0059] (Example 2) A travel plan design system according to an embodiment of the present invention is a system that designs all the destinations, number of days, route, cost, etc., when a user inputs the experiences they want to have. This travel plan design system allows a generation AI to analyze the experiences and design the optimal destinations, number of days, route, and cost. The resulting design is provided to the user. For example, a user inputs the experiences they want to have, such as "I want to enjoy nature" or "I want to visit historical sites." This information is input into the generation AI, which then analyzes the input information. Based on the user's preferences, the generation AI designs the optimal destinations, number of days, route, and cost. For example, in response to a request to "enjoy nature," the generation AI suggests natural locations such as mountains and lakes and designs the number of days to stay, route, and budget. The designed destinations, number of days, route, and cost are provided to the user. The user can plan their trip based on the proposed plan. For example, they can plan a trip according to the destinations and routes suggested by the generation AI and enjoy it within their budget. This system allows users to easily have the optimal travel plan designed to suit their preferences. The generation AI designs all the destinations, number of days, route, and cost, allowing users to enjoy their trip without any hassle. This allows the travel plan design system to provide the optimal travel plan based on the user's wishes.

[0060] The travel plan design system according to the embodiment includes a reception unit, an analysis unit, and a design unit. The reception unit is a component for inputting specific experiences the user wants to have. Examples of experiences the user wants to have include, but are not limited to, trips, events, and activities. The reception unit supports, for example, both text input and selection from options. Text input includes free description and standard phrases. Selection from options includes drop-down menus and radio buttons. The analysis unit analyzes the information received by the reception unit. The analysis unit analyzes the information using methods such as data analysis, text analysis, and sentiment analysis. The analysis unit generates basic data for designing optimal destinations, number of days, route, and cost based on the user's preferences. The design unit designs a plan based on the results of the analysis by the analysis unit. The design unit designs, for example, a travel plan, an event plan, an activity plan, etc. The design unit specifically designs destinations, number of days, route, and cost. Criteria for selecting a destination include tourist attractions, restaurants, accommodations, etc. The criteria for setting the number of days include the duration of the trip and the number of days of stay. The criteria for designing the route include the means of transportation and stopovers. The cost calculation method includes the budget and cost items. This allows the travel plan design system to provide the optimal travel plan based on the user's wishes.

[0061] The design unit can design specific destinations, number of days, routes, and costs. For example, to select a destination, the design unit collects information on tourist attractions, restaurants, accommodations, etc., and suggests the optimal destination. Furthermore, to set the number of days, the design unit can consider the travel period and number of days of stay and suggest the optimal number of days. Furthermore, to design a route, the design unit can consider the means of transportation and stopovers and suggest the optimal route. To calculate costs, the design unit can consider budget and cost items and suggest the optimal cost. For example, the design unit collects information on tourist attractions and suggests the optimal destination based on the user's preferences. Furthermore, the design unit can consider the travel period and number of days of stay and suggest the optimal number of days. Furthermore, the design unit can consider the means of transportation and stopovers and suggest the optimal route. To calculate costs, the design unit can consider the budget and cost items and suggest the optimal cost. In this way, the design unit can provide a travel plan based on the user's preferences.

[0062] The travel plan design system includes a providing unit that provides the user with a specific plan designed by the design unit. The providing unit is a component that provides the user with the plan designed by the design unit. The providing unit can provide the plan in the form of, for example, email, PDF file, or web page. The providing unit has a function that allows the user to easily check the designed plan. For example, the providing unit can provide the designed plan in PDF format. The method of providing the PDF format includes criteria such as file size and layout. The providing unit can also send the designed plan by email. The method of providing the email includes criteria such as email address registration and timing of sending. The providing unit can also display the designed plan on a web page. The method of providing the web page includes criteria such as page layout and navigation design. This allows the providing unit to easily check the designed plan and plan a trip.

[0063] The travel plan design system includes a modification unit that allows a user to modify a plan provided by the provision unit. The modification unit is a component that allows a user to modify a plan provided by the provision unit. The modification unit, for example, has a function of accepting user feedback and modifying a plan. The modification unit allows a user to modify the provided plan to suit their own preferences. For example, the modification unit provides an interface that allows a user to modify the plan's destination, number of days, route, cost, etc. The modification unit sets criteria for modifying the plan based on user feedback. For example, if a user wants to change the destination, the modification unit can suggest a new destination based on the user's preferences. Also, if a user wants to change the number of days, the modification unit can suggest a new number of days based on the user's preferences. Furthermore, if a user wants to change the route, the modification unit can suggest a new route based on the user's preferences. When modifying the cost, the modification unit can consider budgets and cost items and suggest an optimal cost. This allows the modification unit to modify the provided plan to suit the user's preferences and create a travel plan that better suits them.

[0064] The reception unit can support both specific text input and a format for selecting from options. The reception unit is a component for inputting the content of an experience the user wants to have. The reception unit supports, for example, both text input and a format for selecting from options. Text input includes free description and standard phrases. Formats for selecting from options include drop-down menus and radio buttons. For example, the reception unit provides a text input field in which the user can freely describe the content of the experience. The reception unit can also provide an interface in which the user can select the content of the experience from options. This allows the reception unit to input the content of the experience according to the user's preferences. Furthermore, the reception unit can estimate the user's emotions and adjust the input method for the content of the experience based on the estimated user emotions. For example, if the user is feeling stressed, the reception unit can provide a simple interface and minimize the input steps. On the other hand, if the user is relaxed, the reception unit can provide detailed input options and suggest a customizable input method. Furthermore, if the user is in a hurry, the reception unit can prioritize voice input to allow the user to quickly input the content of the experience. This allows the reception unit to provide the optimal input method according to the user's emotions.

[0065] The providing unit can provide the design results in PDF format. The providing unit is a component that provides the plan designed by the design unit to the user. The providing unit can, for example, provide the design results in PDF format. The method of providing the PDF format includes criteria such as file size and layout. For example, the providing unit can generate the design results as a PDF file and provide it to the user. The providing unit can also adjust the layout of the PDF file to allow the user to easily check the plan. Furthermore, the providing unit can optimize the file size of the PDF file to make it easier for the user to download the file. In this way, the providing unit can provide the design results in PDF format to allow the user to easily check the plan.

[0066] The reception unit can estimate the user's emotions and adjust the input method for the experience content based on the estimated user emotions. The reception unit is a component for inputting the content the user wants to experience. The reception unit can, for example, estimate the user's emotions and adjust the input method for the experience content based on the estimated user emotions. Emotion estimation is achieved using an emotion estimation function, for example, with an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the user is feeling stressed, the reception unit can provide a simple interface and minimize the input steps. Alternatively, if the user is relaxed, the reception unit can provide detailed input options and suggest a customizable input method. Furthermore, if the user is in a hurry, the reception unit can prioritize voice input to allow the user to quickly input the experience content. This allows the reception unit to provide the optimal input method according to the user's emotions.

[0067] The reception unit can analyze the user's past input history and suggest the optimal input format. The reception unit is a component for the user to input the content they want to experience. The reception unit can, for example, analyze the user's past input history and suggest the optimal input format. Analysis of the input history includes past input data and frequency of use. For example, the reception unit can automatically display experience content that the user has frequently input in the past as candidates. The reception unit can also preferentially suggest input methods (voice, text, etc.) that the user has used in the past. Furthermore, the reception unit can predict and suggest the experience content that will be used in a specific time period based on the user's past input history. This allows the reception unit to provide the optimal input format based on the user's past input history.

[0068] The reception unit can present input candidates based on the user's current interests and concerns when inputting experience content. The reception unit is a component for inputting the content the user wants to experience. For example, the reception unit can present input candidates based on the user's current interests and concerns when inputting experience content. Identification of interests and concerns includes survey results, past behavioral history, and the like. For example, the reception unit presents related experience content as candidates based on keywords recently searched by the user. The reception unit can also analyze posts that the user has "liked" on social media and suggest related experience content. Furthermore, the reception unit can present related experience content as candidates based on events that the user recently participated in. This allows the reception unit to suggest more appropriate experience content based on the user's interests and concerns.

[0069] The reception unit can estimate the user's emotions and prioritize input contents based on the estimated user emotions. The reception unit is a component for inputting content that the user wants to experience. The reception unit can, for example, estimate the user's emotions and prioritize input contents based on the estimated user emotions. Emotion estimation is achieved using an emotion estimation function, for example, with an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the user is excited, the reception unit can prioritize displaying active experience contents. Furthermore, if the user is relaxed, the reception unit can prioritize displaying relaxing experience contents. Furthermore, if the user is stressed, the reception unit can prioritize displaying experience contents that are useful for stress relief. This allows the reception unit to provide more appropriate experience contents based on the user's emotions.

[0070] The reception unit can present highly relevant input candidates in consideration of the user's geographical location information when the user inputs experience content. The reception unit is a component for inputting the content the user wants to experience. For example, the reception unit can present highly relevant input candidates in consideration of the user's geographical location information when the user inputs experience content. Examples of acquired geographical location information include GPS data and location information services. For example, the reception unit can preferentially display experience content in locations close to the user's current location. Furthermore, if the user is traveling, the reception unit can preferentially display experience content at the user's travel destination. Furthermore, if the user is interested in a specific region, the reception unit can also preferentially display experience content related to that region. In this way, the reception unit can provide more relevant experience content in consideration of the user's geographical location information.

[0071] The reception unit can analyze the user's social media activity when inputting experience content and present related input candidates. The reception unit is a component for inputting the experience content the user wants to have. For example, the reception unit can analyze the user's social media activity when inputting experience content and present related input candidates. Analysis of social media activity includes the content of posts, the number of likes, the number of followers, etc. For example, the reception unit presents related experience content as candidates based on posts that the user has "liked" on social media. The reception unit can also analyze posts from accounts the user follows on social media and suggest related experience content. Furthermore, the reception unit can present related experience content as candidates based on posts the user has shared on social media. This allows the reception unit to provide more relevant experience content based on the user's social media activity.

[0072] The analysis unit can estimate the user's emotions and adjust the analysis algorithm based on the estimated user emotions. The analysis unit is a component for analyzing the information received by the reception unit. The analysis unit can, for example, estimate the user's emotions and adjust the analysis algorithm based on the estimated user emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the user is relaxed, the analysis unit can perform a detailed analysis and provide multiple options. Alternatively, if the user is in a hurry, the analysis unit can perform a quick analysis and provide only one optimal option. Furthermore, if the user is excited, the analysis unit can provide a visually appealing analysis result. This allows the analysis unit to provide a more appropriate analysis result based on the user's emotions.

[0073] The analysis unit can improve the accuracy of the analysis by referring to the user's past travel history during analysis. The analysis unit is a component for analyzing information received by the reception unit. The analysis unit can improve the accuracy of the analysis by, for example, referring to the user's past travel history during analysis. Reference to the travel history includes past travel data and records of places visited. For example, the analysis unit can suggest related destinations based on places the user has visited in the past. The analysis unit can also analyze the user's preferred travel style from the user's past travel history and suggest an optimal plan. Furthermore, the analysis unit can also suggest an optimal route based on the means of transportation used by the user in the past. This allows the analysis unit to provide more accurate analysis results based on the user's past travel history.

[0074] The analysis unit can customize the analysis results based on the user's current living situation and areas of interest during analysis. The analysis unit is a component for analyzing the information received by the reception unit. The analysis unit can customize the analysis results based on the user's current living situation and areas of interest during analysis, for example. Identifying living situations includes occupation, family composition, income, etc. Identifying areas of interest includes hobbies and topics of interest, etc. For example, the analysis unit can suggest an appropriate travel plan based on the user's current living situation. The analysis unit can also suggest related destinations based on the user's areas of interest (nature, history, art, etc.). Furthermore, the analysis unit can suggest a reasonable travel plan taking into account the user's current health condition. This allows the analysis unit to provide more appropriate analysis results based on the user's living situation and areas of interest.

[0075] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the estimated user emotions. The analysis unit is a component for analyzing the information received by the reception unit. The analysis unit can, for example, estimate the user's emotions and adjust the display method of the analysis results based on the estimated user emotions. Emotion estimation is achieved using an emotion estimation function, for example, with an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the user is nervous, the analysis unit can provide a simple, highly visible display method. If the user is relaxed, the analysis unit can provide a display method that includes detailed information. Furthermore, if the user is in a hurry, the analysis unit can also provide a display method that focuses on the main points. This allows the analysis unit to provide more visible analysis results based on the user's emotions.

[0076] The analysis unit can customize the analysis results by taking into account the user's geographical location information during analysis. The analysis unit is a component for analyzing the information received by the reception unit. For example, the analysis unit can customize the analysis results by taking into account the user's geographical location information during analysis. Acquisition of geographical location information includes GPS data, location information services, and the like. For example, the analysis unit can prioritize displaying experience content in locations close to the user's current location. Furthermore, if the user is traveling, the analysis unit can prioritize displaying experience content at the user's travel destination. Furthermore, if the user is interested in a specific region, the analysis unit can also prioritize displaying experience content related to that region. In this way, the analysis unit can provide more relevant analysis results by taking into account the user's geographical location information.

[0077] The analysis unit can analyze the user's social media activity during the analysis and provide related analysis results. The analysis unit is a component for analyzing the information received by the reception unit. For example, the analysis unit can analyze the user's social media activity during the analysis and provide related analysis results. Analysis of social media activity includes the content of posts, the number of likes, the number of followers, etc. For example, the analysis unit can provide related experience content as analysis results based on posts that the user has "liked" on social media. The analysis unit can also analyze posts from accounts that the user follows on social media and suggest related experience content. Furthermore, the analysis unit can also provide related experience content as analysis results based on posts that the user has shared on social media. This allows the analysis unit to provide more relevant analysis results based on the user's social media activity.

[0078] The design unit can estimate the user's emotions and adjust the plan design method based on the estimated user emotions. The design unit is a component for designing a plan based on the results of analysis by the analysis unit. The design unit can, for example, estimate the user's emotions and adjust the plan design method based on the estimated user emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the user is relaxed, the design unit can design a detailed plan. If the user is in a hurry, the design unit can provide a simple plan that can be designed quickly. Furthermore, if the user is excited, the design unit can design a visually appealing plan. This allows the design unit to provide a more appropriate plan based on the user's emotions.

[0079] The design unit can design an optimal plan by referring to the user's past travel history during design. The design unit is a component for designing a plan based on the results of analysis by the analysis unit. For example, the design unit can design an optimal plan by referring to the user's past travel history during design. Reference to travel history includes past travel data and records of places visited. For example, the design unit can suggest related destinations based on places the user has visited in the past. The design unit can also analyze the user's preferred travel style from the user's past travel history and suggest an optimal plan. Furthermore, the design unit can suggest an optimal route based on the means of transportation the user has used in the past. This allows the design unit to provide a more appropriate plan based on the user's past travel history.

[0080] The design unit can customize the plan based on the user's current living situation and areas of interest during design. The design unit is a component for designing a plan based on the results of analysis by the analysis unit. For example, the design unit can customize the plan based on the user's current living situation and areas of interest during design. Identifying living situations includes occupation, family composition, income, etc. Identifying areas of interest includes hobbies and topics of interest, etc. For example, the design unit proposes an appropriate travel plan based on the user's current living situation. The design unit can also propose related destinations based on the user's areas of interest (nature, history, art, etc.). Furthermore, the design unit can propose a reasonable travel plan taking into account the user's current health condition. This allows the design unit to provide a more appropriate plan based on the user's living situation and areas of interest.

[0081] The design unit can estimate the user's emotions and prioritize plans based on the estimated user emotions. The design unit is a component for designing plans based on the results of analysis by the analysis unit. The design unit can, for example, estimate the user's emotions and prioritize plans based on the estimated user emotions. Emotion estimation is achieved using an emotion estimation function, for example, with an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the user is excited, the design unit can prioritize designing active experience content. Also, if the user is relaxed, the design unit can prioritize designing relaxing experience content. Furthermore, if the user is stressed, the design unit can prioritize designing experience content that helps relieve stress. This allows the design unit to provide a more appropriate plan based on the user's emotions.

[0082] The design unit can design an optimal plan taking into account the user's geographical location information during design. The design unit is a component for designing a plan based on the results of analysis by the analysis unit. For example, the design unit can design an optimal plan taking into account the user's geographical location information during design. Examples of acquired geographical location information include GPS data and location information services. For example, the design unit prioritizes designing experience content in locations close to the user's current location. Also, if the user is traveling, the design unit can prioritize designing experience content at the user's travel destination. Furthermore, if the user is interested in a specific region, the design unit can also prioritize designing experience content related to that region. This allows the design unit to provide a more relevant plan taking into account the user's geographical location information.

[0083] The design unit can analyze the user's social media activity during design and design a related plan. The design unit is a component for designing a plan based on the results of analysis by the analysis unit. For example, the design unit can analyze the user's social media activity during design and design a related plan. Analysis of social media activity includes the content of posts, the number of likes, the number of followers, etc. For example, the design unit can incorporate related experience content into the plan based on posts that the user has "liked" on social media. The design unit can also analyze posts from accounts that the user follows on social media and suggest related experience content. Furthermore, the design unit can incorporate related experience content into the plan based on posts that the user has shared on social media. This allows the design unit to provide a more relevant plan based on the user's social media activity.

[0084] The provision unit can estimate the user's emotions and adjust the plan provision method based on the estimated user emotions. The provision unit is a component for providing the plan designed by the design unit to the user. The provision unit can, for example, estimate the user's emotions and adjust the plan provision method based on the estimated user emotions. Emotion estimation is achieved using an emotion estimation function, for example, with an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the user is relaxed, the provision unit can select a provision method that includes detailed explanations. If the user is in a hurry, the provision unit can select a concise provision method that focuses on the main points. Furthermore, if the user is excited, the provision unit can select a visually appealing provision method. This allows the provision unit to select a more appropriate provision method based on the user's emotions.

[0085] The providing unit can select the optimal delivery method by referring to the user's past feedback when providing the plan. The providing unit is a component for providing the plan designed by the design unit to the user. For example, the providing unit can select the optimal delivery method by referring to the user's past feedback when providing the plan. Reference to feedback includes survey results, user comments, and the like. For example, the providing unit preferentially selects a delivery method (email, in-app notification, etc.) that the user has previously preferred. Furthermore, the providing unit can select a detailed delivery method if the user's past feedback indicates that detailed explanations are preferred. Furthermore, the providing unit can select a visually attractive delivery method based on the user's past feedback. This allows the providing unit to select a more appropriate delivery method based on the user's past feedback.

[0086] The providing unit can estimate the user's emotions and adjust the order in which the plans are provided based on the estimated user emotions. The providing unit is a component for providing the user with plans designed by the design unit. The providing unit can, for example, estimate the user's emotions and adjust the order in which the plans are provided based on the estimated user emotions. The emotion estimation is realized using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the user is excited, the providing unit can first provide active experience content. Also, if the user is relaxed, the providing unit can first provide relaxing experience content. Furthermore, if the user is stressed, the providing unit can first provide experience content that helps relieve stress. This allows the providing unit to provide plans in a more appropriate order based on the user's emotions.

[0087] The provision unit can select the optimal provision method by taking into account the user's device information when providing the plan. The provision unit is a component for providing the plan designed by the design unit to the user. For example, the provision unit can select the optimal provision method by taking into account the user's device information when providing the plan. Acquired device information includes the device type and OS version. For example, if the user is using a smartphone, the provision unit selects a provision method that matches the screen size. Furthermore, if the user is using a tablet, the provision unit can select a provision method that is optimized for a large screen. Furthermore, if the user is using a smartwatch, the provision unit can select a provision method that is concise and highly visible. This allows the provision unit to select a more appropriate provision method by taking into account the user's device information.

[0088] The correction unit can estimate the user's emotions and adjust the correction suggestion method based on the estimated user emotions. The correction unit is a component that allows the user to correct the plan provided by the provision unit. The correction unit can, for example, estimate the user's emotions and adjust the correction suggestion method based on the estimated user emotions. Emotion estimation is achieved using an emotion estimation function, for example, with an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the user is relaxed, the correction unit can provide detailed correction options. If the user is in a hurry, the correction unit can provide simple options that allow for quick corrections. Furthermore, if the user is excited, the correction unit can also provide visually appealing correction options. This allows the correction unit to provide a more appropriate correction method based on the user's emotions.

[0089] The correction unit can suggest the optimal correction method by referring to the user's past correction history when making a correction. The correction unit is a component that allows the user to correct the plan provided by the provision unit. For example, the correction unit can suggest the optimal correction method by referring to the user's past correction history when making a correction. The reference to the correction history includes the content of past corrections and the frequency of corrections. For example, the correction unit can suggest related correction options based on the content of corrections made by the user in the past. The correction unit can also analyze the user's preferred correction style from the user's past correction history and suggest the optimal option. Furthermore, the correction unit can preferentially suggest correction methods (such as voice or text) that the user has used in the past. This allows the correction unit to provide a more appropriate correction method based on the user's past correction history.

[0090] The correction unit can estimate the user's emotions and determine the priority of corrections based on the estimated user emotions. The correction unit is a component that allows the user to correct the plan provided by the provision unit. The correction unit can, for example, estimate the user's emotions and determine the priority of corrections based on the estimated user emotions. The emotion estimation is realized using an emotion estimation function, for example, with an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the user is excited, the correction unit can prioritize correction of active experience content. Also, if the user is relaxed, the correction unit can prioritize correction of relaxing experience content. Furthermore, if the user is stressed, the correction unit can prioritize correction of experience content that helps relieve stress. This allows the correction unit to provide more appropriate corrections based on the user's emotions.

[0091] The correction unit can propose an optimal correction method by taking into account the user's device information when making corrections. The correction unit is a component that allows the user to correct the plan provided by the provision unit. For example, the correction unit can propose an optimal correction method by taking into account the user's device information when making corrections. Acquired device information includes the device type and OS version. For example, if the user is using a smartphone, the correction unit can propose a correction method that matches the screen size. Furthermore, if the user is using a tablet, the correction unit can propose a correction method that is optimized for a large screen. Furthermore, if the user is using a smartwatch, the correction unit can propose a simple and highly visible correction method. This allows the correction unit to provide a more appropriate correction method by taking into account the user's device information. === Hard Collateral 1-1 === Each of the multiple elements, including the above-mentioned reception unit, analysis unit, design unit, provision unit, and correction unit, is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart device 14 and provides an interface for the user to input the content of the experience they would like to have. The analysis unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes the information input by the user. The design unit is realized by the specific processing unit 290 of the data processing device 12 and designs a travel plan based on the analysis results. The provision unit is realized by the control unit 46A of the smart device 14 and provides the designed plan to the user. The correction unit is realized by the control unit 46A of the smart device 14 and provides an interface for the user to correct the provided plan. === Hard Collateral 1-2 === Each of the multiple elements, including the above-mentioned reception unit, analysis unit, design unit, provision unit, and correction unit, is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart glasses 214 and provides an interface for the user to input the content of the experience they wish to have. The analysis unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes the user's input information. The design unit is realized by the specific processing unit 290 of the data processing device 12 and designs a travel plan based on the analysis results. The provision unit is realized by the control unit 46A of the smart glasses 214 and provides the designed plan to the user. The correction unit is realized by the control unit 46A of the smart glasses 214 and provides an interface for the user to correct the provided plan. === Hard Collateral 1-3 === Each of the multiple elements including the above-mentioned reception unit, analysis unit, design unit, provision unit, and correction unit is realized, for example, by at least one of the headset type terminal 314 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the headset type terminal 314 and provides an interface for the user to input the content of the experience they would like to have. The analysis unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes the information input by the user. The design unit is realized by the specific processing unit 290 of the data processing device 12 and designs a travel plan based on the analysis results. The provision unit is realized by the control unit 46A of the headset type terminal 314 and provides the designed plan to the user. The correction unit is realized by the control unit 46A of the headset type terminal 314 and provides an interface for the user to correct the provided plan. === Hard Collateral 1-4 === Each of the multiple elements including the above-mentioned reception unit, analysis unit, design unit, provision unit, and correction unit is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the robot 414 and provides an interface for the user to input the content of the experience they would like to have. The analysis unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes the information input by the user. The design unit is realized by the specific processing unit 290 of the data processing device 12 and designs a travel plan based on the analysis results. The provision unit is realized by the control unit 46A of the robot 414 and provides the designed plan to the user. The correction unit is realized by the control unit 46A of the robot 414 and provides an interface for the user to correct the provided plan.

[0092] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0093] The travel plan design system can further include a health management unit that takes into account the user's health condition. The health management unit can acquire the user's health data (e.g., heart rate, number of steps, sleep time, etc.) and reflect it in the design of the travel plan. For example, if the user gets tired easily, the health management unit can suggest a plan that includes plenty of rest time. Also, if the user has an active lifestyle, the health management unit can suggest a plan that includes activities such as hiking or cycling. Furthermore, if the user has specific health restrictions (e.g., dietary restrictions or allergies), the health management unit can also select restaurants and accommodations that accommodate those restrictions. This allows the travel plan design system to provide an optimal travel plan that suits the user's health condition.

[0094] The travel plan design system can further include a history reference unit that references the user's past travel history. The history reference unit records the places the user has visited and the activities the user has experienced in the past, and can refer to these when designing the next travel plan. For example, the system can suggest related new destinations based on the places the user has visited in the past. It can also suggest similar activities based on the activities the user has preferred in the past. It can also suggest optimal options based on the ratings of transportation methods and accommodations the user has used in the past. This allows the travel plan design system to provide a more personalized travel plan based on the user's past travel history.

[0095] The travel plan design system can further include a social media analysis unit that analyzes the user's social media activity. The social media analysis unit can analyze posts that the user has "liked" and content that the user has shared on social media and reflect the results in the design of the travel plan. For example, the social media analysis unit can suggest related tourist spots and activities based on posts that the user has "liked." It can also design travel plans related to themes of interest based on content that the user has shared. It can also analyze posts from accounts that the user follows and suggest related experiences. This allows the travel plan design system to provide more relevant travel plans based on the user's social media activity.

[0096] The travel plan design system can further include a lifestyle situation analysis unit that takes into account the user's current lifestyle situation. The lifestyle situation analysis unit can acquire information such as the user's occupation, family composition, and income, and reflect this in the design of the travel plan. For example, if the user has a busy job, the system can suggest a plan that allows them to refresh themselves in a short period of time. Also, if the user is traveling with their family, the system can suggest a plan that includes activities that the whole family can enjoy. Furthermore, the system can design a travel plan that can be enjoyed within the user's budget based on the user's income. This allows the travel plan design system to provide the optimal travel plan that suits the user's lifestyle situation.

[0097] The travel plan design system can further include a location information analysis unit that takes into account the user's geographical location information. The location information analysis unit can acquire location information of the user's current location and travel destination and reflect it in the design of the travel plan. For example, if the user wishes to travel to a location close to their current location, the location information analysis unit can suggest nearby tourist attractions and activities. Also, if the user is interested in a specific area, the system can design a travel plan related to that area. Furthermore, if the user is traveling, the system can prioritize suggestions for experiences at the travel destination. This allows the travel plan design system to provide more relevant travel plans based on the user's geographical location information.

[0098] The travel plan design system may further include an emotion adjustment unit that estimates the user's emotions and adjusts the travel plan based on the estimated emotions. The emotion adjustment unit can estimate the user's emotions based on the user's input and past behavioral history and reflect them in the design of the travel plan. For example, if the user is feeling stressed, the emotion adjustment unit can suggest a plan that includes many relaxing activities. Alternatively, if the user is excited, the emotion adjustment unit can suggest a plan that includes many active activities. Furthermore, if the user is relaxed, the emotion adjustment unit can provide a detailed plan and suggest customizable options. This allows the travel plan design system to provide an optimal travel plan that matches the user's emotions.

[0099] The travel plan design system can further include an emotion prioritization unit that estimates the user's emotions and determines the priority of the plan based on the estimated emotions. The emotion prioritization unit can determine which activities and destinations to prioritize in the travel plan based on the user's emotions. For example, if the user is excited, the emotion prioritization unit can prioritize designing active experience content. Also, if the user is relaxed, the emotion prioritization unit can prioritize designing relaxing experience content. Furthermore, if the user is stressed, the emotion prioritization unit can prioritize designing experience content that helps relieve stress. This allows the travel plan design system to provide a more appropriate plan based on the user's emotions.

[0100] The travel plan design system may further include an emotion providing unit that estimates the user's emotion and adjusts the plan presentation method based on the estimated emotion. The emotion providing unit can adjust the travel plan presentation method based on the user's emotion. For example, if the user is relaxed, the emotion providing unit may select a presentation method that includes detailed explanations. If the user is in a hurry, the emotion providing unit may select a concise presentation method that focuses on the main points. Furthermore, if the user is excited, the emotion providing unit may select a visually appealing presentation method. This allows the travel plan design system to select a more appropriate presentation method based on the user's emotion.

[0101] The travel plan planning system may further include an emotion modification unit that estimates the user's emotion and adjusts a method for modifying the plan based on the estimated emotion. The emotion modification unit can adjust a method for modifying the travel plan based on the user's emotion. For example, if the user is relaxed, the emotion modification unit can provide detailed modification options. If the user is in a hurry, the emotion modification unit can provide simple options that allow for quick modification. Furthermore, if the user is excited, the emotion modification unit can also provide visually appealing modification options. This allows the travel plan planning system to provide a more appropriate modification method based on the user's emotion.

[0102] The travel plan design system may further include an emotion analysis unit that estimates the user's emotion and adjusts the plan analysis method based on the estimated emotion. The emotion analysis unit can adjust the travel plan analysis method based on the user's emotion. For example, if the user is relaxed, the emotion analysis unit can perform a detailed analysis and provide multiple options. If the user is in a hurry, the emotion analysis unit can perform a quick analysis and provide only one optimal option. Furthermore, if the user is excited, the emotion analysis unit can provide a visually appealing analysis result. This allows the travel plan design system to provide more appropriate analysis results based on the user's emotion.

[0103] The processing flow of the second embodiment will be briefly explained below.

[0104] Step 1: The reception unit is a section for inputting the specific content of the experience the user wants to have. The content of the experience the user wants to have includes, but is not limited to, travel, events, activities, etc. The reception unit supports, for example, both text input and a format for selecting from options. Text input includes free description and standard phrases. Formats for selecting from options include drop-down menus and radio buttons. Step 2: The analysis unit analyzes the information received by the reception unit. The analysis unit analyzes the information using methods such as data analysis, text analysis, and sentiment analysis. The analysis unit generates basic data for designing the optimal destination, number of days, route, and cost based on the user's preferences. Step 3: The design section designs a plan based on the results of the analysis performed by the analysis section. The design section designs, for example, travel plans, event plans, activity plans, etc. The design section specifically designs destinations, number of days, route, and cost. Criteria for selecting destinations include tourist spots, restaurants, accommodations, etc. Criteria for setting number of days include travel period and number of days of stay, etc. Criteria for designing routes include means of transportation, stopovers, etc. Cost calculation methods include budgets, cost items, etc.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0109] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0110] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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).

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0125] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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).

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0141] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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).

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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).

[0162] 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.

[0163] 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."

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0175] 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.

[0176] [Explanation of symbols]

[0177] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A reception desk where you can input the details of your experience; an analysis unit that analyzes the information received by the reception unit; a design unit that designs a plan based on the results of the analysis by the analysis unit; Equipped with A system characterized by:

2. The design unit Plan specific destinations, duration, route, and costs 2. The system of claim 1.

3. A provision unit that provides the plan designed by the design unit to the user in detail.

2. The system of claim 1.

4. a providing unit that provides a user with the plan designed by the design unit; a modification unit that allows a user to specifically modify the plan provided by the provision unit; 3. The system of claim 2.

5. The reception unit Supports both specific text input and multiple choice format 2. The system of claim 1.

6. The providing unit Provided in PDF format 5. The system of claim 4.

7. The reception unit Specifically estimates the user's emotions and adjusts the input method for the experience content based on the estimated user emotions.

2. The system of claim 1.

8. The reception unit Analyzes the user's past input history and suggests appropriate input formats 2. The system of claim 1.

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