System

Abstract

A system is provided.SOLUTION: A means for collecting information related to a budget of a user, a travel destination, and a preference of a partner, a means for executing an artificial intelligence model for proposing an optimal souvenir to the user based on the collected information, a means for selecting a purchase place of the proposed souvenir from position information, a means for providing an online purchase option of the proposed souvenir, and a means for collecting word-of-mouth information related to the proposed souvenir; The system includes a means for providing the memorial day information to the user, a means for generating a reminder on the basis of the memorial day information and notifying the user of the reminder, and a means for preferentially recommending the local specialty from the proposed souvenir.SELECTED DRAWING: Figure 1

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] When travelers choose souvenirs at their travel destinations, they often find it difficult to easily find the right souvenir that suits their budget and the tastes of the recipient. Searching for an effective place to buy souvenirs can also take time and effort, which can detract from the enjoyment of the trip. In addition, there is a lack of ways to encourage people to prioritize purchasing local specialties in order to stimulate the local economy. [Means for solving the problem]

[0005] The present invention provides a system that includes: means for collecting information on a user's budget, travel destination, and the recipient's preferences; means for running an artificial intelligence model to suggest optimal souvenirs to the user based on the collected information; means for selecting a place to purchase the suggested souvenirs based on location information; means for providing online purchase options for the suggested souvenirs; means for collecting word-of-mouth information about the suggested souvenirs and providing it to the user; means for generating reminders based on anniversary information and notifying the user; and means for preferentially recommending regional specialties from among the suggested souvenirs. This allows travelers to reduce the effort required for souvenir selection and improves their travel experience. Furthermore, preferentially recommending local specialties can contribute to revitalizing the local economy.

[0006] "User" refers to an individual or organization who uses this system to input information to select a souvenir and receives the results.

[0007] "Budget" refers to the amount of money a user can spend on purchasing souvenirs.

[0008] "Travel destination" refers to a destination or place that a user visits.

[0009] "Preferences of the recipient" refers to the items or categories that the recipient to whom the user intends to give a gift particularly likes.

[0010] "Means for collecting information" refers to a process or device that provides an interface for users to input information such as budget, travel destination, and partner preferences, and then stores the information.

[0011] "Artificial intelligence model" refers to an algorithm or program that processes collected user information and selects the most suitable souvenir.

[0012] "Souvenirs" refer to items or gifts that users purchase at their travel destinations and give to others.

[0013] "Purchase location" refers to the location of a store or facility where the user can actually purchase the suggested souvenir.

[0014] "Location information" refers to geographic data of a user's current location or the place of purchase.

[0015] "Online Purchase Option" refers to a link or means to purchase the suggested souvenir via the Internet.

[0016] "Word-of-mouth information" refers to feedback from past purchasers and users who have given their evaluations and impressions of the suggested souvenirs.

[0017] "Anniversary information" refers to data relating to the birthdays and dates of special events of the user or the other person.

[0018] A "reminder" is a message or alert that notifies a user of a specific date, time, or event.

[0019] "Regional specialties" refer to items or gifts that are produced in a particular region and are representative of that region.

[0020] "Preferential recommendation means" refers to a process or device that selects local specialties and suggests them to the user before other souvenirs. [Brief explanation of the drawings]

[0021] [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. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0022] 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.

[0023] First, the terms used in the following description will be explained.

[0024] 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, a 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), and an APU (Accelerated Processing Unit).

[0025] 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.

[0026] 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.

[0027] 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), Bluetooth (registered trademark), etc.

[0028] 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."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 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.

[0032] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[0033] 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.

[0034] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. 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 acquires the data indicating the user input.

[0035] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The 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.

[0036] 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.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 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.

[0039] 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.

[0040] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0041] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0042] This invention is a system that allows users to select the best souvenirs for their travels, and AI makes suggestions based on information such as budget, destination, and the recipient's preferences. This system is specifically implemented as follows.

[0043] First, the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. The terminal provides an interface to send this information to the server. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets."

[0044] The server uses an AI model to recommend the best souvenir based on the received user data. This AI model selects souvenir items that best fit the user's input criteria based on past data and trend information.

[0045] The server then selects a place to purchase the recommended souvenir based on the location information. Specifically, it searches for the nearest store that offers the recommended souvenir based on the user's current location information and provides the user with the location information of that store.

[0046] The server also provides the option of souvenirs that can be purchased online, allowing users to purchase souvenirs over the Internet even if they do not have time to purchase them locally.

[0047] Furthermore, the server collects and provides user-review information, which is information about the evaluations and experiences of past purchasers, to help users make purchasing decisions.

[0048] The server also generates reminders based on the user's anniversary information and notifies the user, allowing the user to select the perfect souvenir for a specific anniversary or event.

[0049] Finally, the server includes a means for preferentially recommending local specialties. By preferentially recommending local specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Tokyo," the server can recommend specialties unique to Tokyo, thereby contributing to the spread of local culture and specialties.

[0050] For example, if a user inputs "Kyoto" as their travel destination, a budget of "5,000 yen," and "sake" as their partner's preference, the system will suggest the best sake based on past data and trends. It will then suggest the nearest store to the user's current location or provide a link to an online shop. It will also display reviews from past users and set reminders related to upcoming anniversaries. It also contributes to promoting local specialties by prioritizing recommendations of sake that is particularly famous in Kyoto.

[0051] In this way, the system of this invention uses AI to make appropriate suggestions based on the user's budget and preferences, eliminating the hassle of choosing souvenirs and improving the travel experience. In addition, by recommending local specialties, it can contribute to revitalizing local economies.

[0052] The processing flow will be explained below.

[0053] Step 1:

[0054] The terminal provides the user with an interface to input budget, destination, and partner preferences. The user enters the information in the appropriate fields and clicks the submit button.

[0055] Step 2:

[0056] The terminal sends the information entered by the user, such as budget, travel destination, and partner preferences, to the server, which is then ready to receive the user's request.

[0057] Step 3:

[0058] The server uses an AI model to suggest the best souvenirs based on the received user data. The AI ​​model analyzes past data, trends, and the purchasing history of other users to generate a list of suggested souvenirs.

[0059] Step 4:

[0060] The server searches for a place to purchase each souvenir based on the created souvenir list, finds the nearest store based on the user's current location, and acquires its location information.

[0061] Step 5:

[0062] The server retrieves online shopping links for each item to provide online purchasing options for the suggested souvenirs, and if available, provides the link to the user.

[0063] Step 6:

[0064] The server collects word-of-mouth information about the proposed souvenirs, including reviews and ratings left by past buyers, and gathers data to provide useful information to users.

[0065] Step 7:

[0066] The server generates reminders based on the user's anniversary information, helping them select the appropriate souvenir for a specific anniversary or event.

[0067] Step 8:

[0068] The server prioritizes and recommends regional specialties from among the suggested souvenirs. Based on data related to regional specialties, it recommends local products to help revitalize the local economy.

[0069] Step 9:

[0070] The server then sends all the results back to the device, including a list of the best souvenirs, where to buy, online options, reviews, reminders, and preferred recommendations for local specialties.

[0071] Step 10:

[0072] The terminal displays the information received from the server to the user, who then selects from the list of suitable souvenirs displayed on the terminal screen and obtains the desired product using the provided purchasing locations or online options.

[0073] Example 1

[0074] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0075] When choosing souvenirs, users currently spend a lot of time and effort selecting the best one from a wide range of options. Furthermore, there are a lack of effective ways to purchase local specialties and to refer to word-of-mouth information. This makes it difficult for users to choose a souvenir that satisfies them. Furthermore, there is no system that prioritizes and recommends local specialties, which is a problem that does not contribute to the development of local economies.

[0076] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0077] In this invention, the server includes: means for collecting information on a user's budget, travel destination, and other party preferences; means for running a generative AI model to suggest optimal souvenirs to the user based on the collected information; means for selecting a purchase location for the suggested souvenir based on location information; means for providing online purchase options for the suggested souvenir; means for collecting and providing user reviews about the suggested souvenir; means for generating reminders based on anniversary information and notifying the user; means for preferentially recommending regional specialties from among the suggested souvenirs; means for selecting and providing information about the optimal purchase location based on the user's current location information; means for providing links to online purchases of the suggested souvenirs if they are available; and means for selecting souvenirs based on past trend information using the generative AI model. This allows users to easily select and purchase optimal souvenirs and refer to reviews, and further contributes to the development of local economies by recommending regional specialties. A "user" refers to an individual who uses a terminal to input information such as a travel destination, budget, and other party preferences.

[0078] A "terminal" is a device through which a user inputs information such as travel destination, budget, and the other person's preferences, and includes smartphones, PCs, tablets, etc.

[0079] "Server" refers to a central computer system that processes information received from users and suggests the most suitable souvenirs.

[0080] "Budget" refers to the range of amounts set by the user for purchasing souvenirs.

[0081] "Travel destination" indicates a place where the user is traveling and includes geographic information about the place.

[0082] "Recipient's preferences" is information input by the user, and includes elements related to the recipient's tastes and preferences.

[0083] A "generative AI model" is an artificial intelligence model used to suggest the best souvenirs based on information entered by the user.

[0084] "Online Purchase Option" refers to the means provided for users to purchase suggested souvenirs over the Internet.

[0085] "Word-of-mouth information" refers to information including ratings and reviews provided by users who have previously purchased a product.

[0086] "Reminder" refers to an alert or message provided to notify a user of a particular anniversary or event.

[0087] "Regional specialty products" refer to products that are produced in a particular region and are characteristic of that region.

[0088] "Location information" refers to information including geographical data indicating a user's current location or a specific point.

[0089] "Purchase location" refers to the physical store or online shop where the suggested souvenir can be purchased.

[0090] "Past trend information" refers to information based on market trends and data on popular products.

[0091] This invention relates to a system for selecting the perfect souvenir for a travel destination. Users use a terminal to input information such as their travel destination, budget, and the recipient's preferences. Based on the information received, a server suggests the perfect souvenir and provides information such as where to buy it, online purchasing options, and reviews. The system also provides reminders based on anniversary information and recommends local specialties.

[0092] First, the user uses a device (such as a smartphone or PC) to input information such as the travel destination, budget, and the recipient's preferences. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets." The necessary information is then sent from the device to the server.

[0093] Based on the received user data, the server uses a generative AI model, a TensorFlow neural network model implemented in Python, to suggest the best souvenir. This generative AI model selects the souvenir item that best suits the user's input criteria based on past data and trend information. For example, if a user inputs a prompt such as "Travel destination: Tokyo, Budget: 3,000 yen, Favorites: Japanese sweets," the model will select Japanese sweets for Tokyo based on past trend information.

[0094] Next, the server selects the recommended souvenir purchasing location based on the location information. Specifically, it uses a location information API to obtain the user's current location and searches the PostgreSQL database for related stores within a specific range based on those coordinates. As a result, information on the nearest store is provided to the user. For example, if the user is near Tokyo Station, information on nearby Japanese confectionery stores is provided.

[0095] The server also provides souvenir options that can be purchased online. It uses the Amazon API and Rakuten API to check whether the suggested souvenirs are available online, and if so, generates and provides a link. This allows users to purchase souvenirs over the Internet even if they don't have time to buy them locally.

[0096] The server also collects user reviews and provides them to users. Specifically, it uses Python's BeautifulSoup to scrape relevant user reviews from the web, formatting them, and sending them to users for viewing. For example, it displays ratings and reviews from past buyers of the suggested Japanese sweets.

[0097] The server also generates reminders based on the anniversary information and notifies the user. It references the anniversary database and uses Firebase Cloud Messaging to trigger reminder notifications for specific dates. For example, when a user's wedding anniversary is approaching, a notification is sent with a suggestion for the perfect souvenir.

[0098] In addition, the server prioritizes recommendations of local specialties. By referencing a database of local specialties, it selects and recommends specialties that correspond to the user's travel destination (for example, Japanese sweets from Tokyo), which contributes to the development of the local economy.

[0099] An example of a prompt is as follows:

[0100] "Destination: Tokyo, Budget: 3000 yen, Favorites: Japanese sweets"

[0101] "Travel destination: Kyoto, Budget: 5,000 yen, Favorites: Sake"

[0102] In this way, the system of this invention uses AI to make appropriate suggestions based on the user's budget and preferences, eliminating the hassle of choosing souvenirs and improving the travel experience. In addition, by recommending local specialties, it also contributes to revitalizing the local economy.

[0103] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0104] Step 1: Enter your information

[0105] The user uses a device to input information such as travel destination, budget, and the other person's preferences. Specifically, the user enters information such as "Travel destination: Kyoto, Budget: 5,000 yen, Other person's preference: Japanese sake" into a form displayed on the screen of their smartphone or PC, and clicks the send button. This causes the input information to be displayed on the device screen, and the device then sends this information to the server.

[0106] Step 2: Send data from the device to the server

[0107] The terminal sends the information entered by the user to the server. Specifically, the terminal generates an HTTP request and sends the input information to the server in JSON format. This request includes the travel destination, budget, and the other person's preferences. The input is the information "Travel destination: Kyoto, Budget: 5,000 yen, Other person's preference: Sake," and the output is the information received on the server side.

[0108] Step 3: Server selects the gift

[0109] The server uses a generative AI model to select the optimal souvenir based on the received user data. Specifically, the server calls a TensorFlow neural network model implemented in Python and inputs the received information as a prompt. The generative AI model uses an internal database and past trend information to select souvenir items that fit the input criteria. The input is information such as "Travel destination: Kyoto, Budget: 5,000 yen, Recipient's preference: Sake," and the output is a recommended sake item.

[0110] Step 4: Choose a place to buy

[0111] The server selects the recommended souvenir purchasing location based on location information. Specifically, the server obtains the user's current location using a location information API and searches the PostgreSQL database for nearby stores based on those coordinates. The server extracts information about related stores within a specific range and selects the nearest store. The input is the user's current location information, and the output is information about the nearest store where the souvenir can be purchased.

[0112] Step 5: Offer online purchasing options

[0113] The server also provides souvenir options that can be purchased online. Specifically, the server uses the Amazon API or Rakuten API to check whether the recommended souvenirs are available for purchase online. If so, it generates and provides a corresponding link. The input is the information about the recommended souvenir item, and the output is the link to the corresponding online shop.

[0114] Step 6: Collect and provide reviews

[0115] The server collects reviews about recommended souvenirs and provides them to users. Specifically, the server uses Python's BeautifulSoup to scrape relevant reviews from the web and format them in a user-viewable format. The input is the recommended souvenir item information, and the output is the reviews about that item.

[0116] Step 7: Set reminders and notifications

[0117] The server generates a reminder based on the anniversary information and notifies the user. Specifically, the server references the anniversary database and uses Firebase Cloud Messaging to send a reminder notification for a specific date. The input is the user's anniversary information, and the output is the reminder notification.

[0118] Step 8: Recommend local specialties

[0119] The server prioritizes regional specialty products from the recommended souvenirs. Specifically, the server references a regional specialty product database and prioritizes the specialty products that correspond to the user's travel destination. The input is the travel destination and specialty product data, and the output is the suggested regional specialty products.

[0120] (Application example 1)

[0121] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0122] Conventional systems make it difficult for users to select the perfect souvenir when visiting a particular location, making it difficult to improve the quality of their travel experience. Furthermore, virtual shopping experiences using virtual reality devices were not readily available, preventing users from enjoying a detailed remote shopping experience. Furthermore, there were insufficient means to effectively recommend local specialties and contribute to the development of the local economy.

[0123] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0124] In this invention, the server includes: means for collecting information on a user's budget, travel destination, and the recipient's preferences; means for running an artificial intelligence model to suggest optimal souvenirs to the user based on the collected information; means for selecting a place to purchase the suggested souvenirs based on location information; means for providing online purchasing options for the suggested souvenirs; means for collecting word-of-mouth information about the suggested souvenirs and providing it to the user; means for generating reminders based on anniversary information and notifying the user; means for preferentially recommending regional specialties from among the suggested souvenirs; and means for linking with a virtual reality device that allows the user to explore virtual stores and confirm the souvenirs they have selected. This allows users to enjoy a sophisticated shopping experience using virtual reality from their travel destination or at home, eliminating the need to select the optimal souvenir and contributing to the spread of regional specialties and the development of the local economy.

[0125] "User's budget" is the upper limit of the amount that a user sets for the products that he or she wishes to purchase.

[0126] "Travel destination" refers to a place or city that the user plans to visit.

[0127] "Preferences of the recipient" refers to the specific tastes and hobbies of the recipient to whom the user is giving a souvenir.

[0128] "Means for collecting information" refers to a method or device for obtaining the necessary information from the user.

[0129] An "artificial intelligence model" is an algorithm or system that learns from past data and trend information and makes optimal suggestions.

[0130] "Purchase location" refers to the geographic location or store where the user can actually purchase the recommended souvenir.

[0131] "Location Information" means data regarding a user's current geographic location.

[0132] An "online purchase option" is a choice that allows a user to purchase products over the Internet.

[0133] "Word-of-mouth information" is information about ratings and comments made by past users about products.

[0134] A "reminder" is a function or system that notifies users of specific dates, times, or anniversaries.

[0135] "Regional specialties" are products or foods that are produced in a particular region and are representative of that region.

[0136] A "virtual reality device" is a device that allows users to immerse themselves in a virtual space and experience it, and mainly includes head-mounted displays and VR goggles.

[0137] This invention provides a system that allows users to select the best souvenirs for their travels, with AI making suggestions based on information such as budget, destination, and the recipient's preferences, allowing users to efficiently select souvenirs.

[0138] First, the user uses a device to input information such as the travel destination, budget, and the recipient's preferences. The device provides an interface that sends this information to the server. For example, a user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets." This information is then sent to the server via a web browser or a dedicated application.

[0139] The server uses an artificial intelligence model to recommend the best souvenir based on the received user data. This artificial intelligence model is built using frameworks such as TensorFlow and PyTorch. The model learns from past data and trend information to select the souvenir item that best suits the user's input criteria. For example, "Japanese sweets from Tokyo" may be recommended.

[0140] Next, the server selects the place to purchase the recommended souvenir based on the location information. Specifically, it obtains the user's current location information using Google Maps API or similar, and searches for the nearest store that offers the recommended souvenir. The location information of that store is then provided to the user.

[0141] The server also provides the option of souvenirs available for purchase online, allowing users to purchase souvenirs over the Internet even if they don't have time to do so locally. Users can click on the provided link to access the online shop and complete the purchase.

[0142] Furthermore, the server collects and provides user-review information, which includes information on the evaluations and experiences of past purchasers. This information helps users confirm the reliability of the recommended souvenirs and assists them in making a purchasing decision.

[0143] The server also generates reminders based on the user's anniversary information and notifies the user. This function is often implemented using the Google Calendar API, and helps users choose the perfect souvenir for a particular anniversary or event.

[0144] Finally, the server includes a means for preferentially recommending local specialties. By preferentially recommending local specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Tokyo," the server can recommend specialties unique to Tokyo, thereby contributing to the spread of local culture and specialties.

[0145] Furthermore, this invention can be applied to virtual stores. By using a virtual reality device such as a head-mounted display or VR goggles, users can visit stores in a virtual space and check recommended souvenirs. Users can operate an avatar to explore the virtual store and experience the realistic shopping experience of the selected souvenir.

[0146] As a concrete example, consider the case where a user enters "Kyoto" as the travel destination, a budget of "5,000 yen," and "sake" as the recipient's preference. Based on this information, the server will recommend the most suitable sake based on past data and trend information. Furthermore, based on the user's current location, the server will provide the nearest store where the sake can be purchased and also provide a link to the online shop. Reviews will also be displayed, and a reminder related to the next anniversary will be set. Recommendations will also be prioritized for regional specialties, such as sake that is particularly famous in Kyoto.

[0147] Example prompt sentence:

[0148] Travel destination: Kyoto

[0149] Budget: 5,000 yen

[0150] Partner's preference: Sake

[0151] Current location: Tokyo

[0152] In this way, the system of this invention improves the travel experience while reducing the effort required for souvenir selection by making appropriate suggestions based on the user's budget and preferences using AI. In addition, by recommending local specialties, it can contribute to revitalizing the local economy.

[0153] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0154] Step 1:

[0155] The user uses a device to input information such as travel destination, budget, and the other person's preferences. The user provides information through an input form on the device, such as "Travel destination: Tokyo, budget: 3,000 yen, other person's preferences: Japanese sweets." This information is structured in JSON format or similar and sent to the server.

[0156] Step 2:

[0157] The server analyzes the information received from the user. To analyze the information, the server accesses a database and searches for past data and trend information. This process uses SQL queries and other methods to extract information based on the input travel destination, budget, and preferences. As a result of the analysis, a list of multiple potential souvenir items is generated.

[0158] Step 3:

[0159] The server runs an artificial intelligence model (using, for example, TensorFlow or PyTorch) based on the list of candidate items. The model learns from past user data and trend information and selects the souvenir item that best suits the input criteria. This process identifies recommended items such as "Japanese sweets from Tokyo."

[0160] Step 4:

[0161] The server selects the place to purchase the recommended souvenir items. It uses the Google Maps API to obtain the user's current location and search for the nearest store. The store's location is selected by calculating the distance between the user's current location and the destination based on the data obtained from Google Maps.

[0162] Step 5:

[0163] The server provides online purchasing options and generates links to online shops where the suggested souvenir items can be purchased in case the user is unable to purchase them locally. This is done by using the API of each online shop to search for the product ID and obtain the link to its purchase page.

[0164] Step 6:

[0165] The server collects reviews of recommended souvenir items and provides them to users. It retrieves ratings and comments from past users from a database such as MongoDB and displays them along with the analysis results. This allows users to confirm the reliability of the products.

[0166] Step 7:

[0167] The server generates reminders based on the anniversary information and notifies the user. It uses the Google Calendar API to retrieve the user's anniversary data and sets notifications when the date approaches. Notifications are sent as emails or in-app notifications.

[0168] Step 8:

[0169] The server prioritizes recommendations of local specialty products. Based on the analysis results, it extracts specialty product data related to the user's travel destination and adds them to the recommendation list with priority. This contributes to the spread of specialty products and the development of the local economy.

[0170] Step 9:

[0171] Users use a virtual reality device to explore virtual stores. They wear a head-mounted display and check recommended souvenir items in the virtual space. Users can control an avatar to visit stores and check detailed souvenir information and reviews in real time.

[0172] In this way, a system is constructed that realizes complex processing through the roles of the server, terminal, and user, and supports efficient and effective souvenir selection.

[0173] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0174] This invention is a system that allows users to select the best souvenirs for their travels. AI makes suggestions based on information such as budget, destination, and the recipient's preferences. It also has a function to adjust the suggestions by combining it with an emotion engine that recognizes the user's emotions. This system is specifically implemented as follows.

[0175] First, the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. The terminal provides an interface to send this information to the server. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets."

[0176] The server uses an AI model to suggest the best souvenir based on the received user data. This AI model selects the souvenir item that best suits the user's input criteria based on past data and trend information.

[0177] Furthermore, the server uses an emotion engine to recognize the user's emotions. It analyzes the user's facial expressions and tone of voice through emotion recognition devices (such as cameras and microphones) to understand their current emotional state. For example, if the user has a happy face, the server recognizes their emotional state as "happy."

[0178] The server adjusts the suggestions based on the user's emotional state as recognized by the emotion engine. For example, if the user is in a "happy" emotional state, the server will recommend souvenirs that will further enhance the user's joyful mood. In this way, suggestions that are tailored to the user's emotions will help the user select souvenirs that will provide greater satisfaction.

[0179] The server also monitors the user's emotional state in real time and updates the suggestions as needed. For example, if the user suddenly changes their mood or is not interested in a suggested souvenir, it can instantly suggest other options.

[0180] Furthermore, the server learns the user's past emotional data and reflects it in future souvenir suggestions, enabling more accurate suggestions based on the user's past emotional state and the type of souvenir they chose.

[0181] The server then selects a place to purchase the recommended souvenir based on the location information. Specifically, it searches for the nearest store that offers the recommended souvenir based on the user's current location information and provides the user with the location information of that store.

[0182] The server also provides the option of souvenirs that can be purchased online, allowing users to purchase souvenirs over the Internet even if they do not have time to purchase them locally.

[0183] Furthermore, the server collects and provides user-review information, which is information about the evaluations and experiences of past purchasers, to help users make purchasing decisions.

[0184] The server also generates reminders based on the user's anniversary information and notifies the user, allowing the user to select the perfect souvenir for a specific anniversary or event.

[0185] Finally, the server includes a means for preferentially recommending local specialties. By preferentially recommending local specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Tokyo," the server can recommend specialties unique to Tokyo, thereby contributing to the spread of local culture and specialties.

[0186] For example, if a user inputs "Kyoto" as their travel destination, a budget of "5,000 yen," and the other person's preference of "sake," and the emotion engine recognizes the emotion of "expectation," the system will suggest the most suitable sake based on past data and trends. The system will then provide the nearest store to the user's current location or a link to an online shop. It will also display reviews from past users and set reminders related to upcoming anniversaries. By prioritizing recommendations of sake that is particularly famous in Kyoto, the system also contributes to promoting local specialties.

[0187] In this way, the system of this invention not only uses AI to make appropriate suggestions based on the user's budget and preferences, but also uses an emotion engine to make suggestions that match the user's emotions, helping them choose souvenirs with greater satisfaction. Furthermore, by recommending local specialties, it can also contribute to revitalizing local economies.

[0188] The processing flow will be explained below.

[0189] Step 1:

[0190] The terminal provides the user with an interface to input budget, destination, and partner preferences. The user enters the information in the appropriate fields and clicks the submit button.

[0191] Step 2:

[0192] The terminal sends the information entered by the user, such as budget, travel destination, and partner preferences, to the server, which is then ready to receive the user's request.

[0193] Step 3:

[0194] The server uses an artificial intelligence model to suggest the best souvenir based on the received user data. This AI model analyzes past data and trend information to select the souvenir item that best suits the user's requirements.

[0195] Step 4:

[0196] The server uses an emotion engine to recognize the user's emotions. It analyzes the user's facial expressions and voice through the camera and microphone connected to the device to determine their current emotional state. For example, if the user is smiling, it will recognize that they are "happy."

[0197] Step 5:

[0198] The server adjusts the suggestions based on the user's emotional state as recognized by the emotion engine. For example, if the user is in a "happy" emotional state, the server will recommend souvenirs that will further enhance the user's joyful mood.

[0199] Step 6:

[0200] The server selects the place to purchase the suggested souvenir based on the user's current location information. Based on the user's current location information, it searches for the nearest store that offers the recommended souvenir and obtains the store's location information.

[0201] Step 7:

[0202] The server retrieves online shopping links for each item to provide online purchasing options for the suggested souvenirs, and if available, provides the link to the user.

[0203] Step 8:

[0204] The server collects word-of-mouth information about the proposed souvenirs, pulls out reviews and ratings left by past buyers from a database, and provides them to the user.

[0205] Step 9:

[0206] The server generates reminders based on the user's anniversary information, helping them select the appropriate souvenir for a specific anniversary or event.

[0207] Step 10:

[0208] The server prioritizes regional specialty products from among the recommended souvenirs. Based on data related to regional specialty products, the server prioritizes local products to support the revitalization of the local economy.

[0209] Step 11:

[0210] The server then sends all the results back to the device, including a list of the best souvenirs, where to buy, online options, reviews, reminders, and preferred recommendations for local specialties.

[0211] Step 12:

[0212] The terminal displays the information received from the server to the user, who then selects from the list of suitable souvenirs displayed on the terminal screen and obtains the desired product using the provided purchasing locations or online options.

[0213] As a specific example, if a user inputs "Kyoto" as their travel destination, a budget of "5,000 yen," and the recipient's preference of "sake," and the emotion engine recognizes the emotion of "expectation," the server will use an AI model to suggest the most suitable sake. The server will then provide the store closest to the user's current location, along with reviews. It will also provide an online purchase link. Furthermore, a reminder related to the next anniversary will be generated, with priority given to recommendations of local sake, a Kyoto specialty. Based on this information, users can select and purchase the perfect souvenir.

[0214] Example 2

[0215] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0216] Traditionally, choosing the right souvenirs for a trip has been challenging, especially when it comes to making optimal choices based on the user's budget and the recipient's preferences. Furthermore, there has been a lack of methods to improve satisfaction by adjusting recommendations based on the user's emotional state. Furthermore, there have been insufficient efforts to revitalize local economies through preferential recommendations of regional specialties. Therefore, there is a need for a system that collects user information, considers the user's emotional state, makes optimal recommendations, and prioritizes regional specialties.

[0217] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0218] In this invention, the server includes means for collecting information on a user's budget, travel destination, and partner preferences, means for executing an artificial intelligence model to suggest optimal products to the user based on the collected information, means for executing an emotion recognition engine to recognize the user's emotional state regarding the suggested products, means for adjusting the content of the suggestions based on the user's emotional state, means for selecting and providing a purchase location for the suggested products based on location information, means for providing an online purchase option for the suggested products, means for collecting and providing evaluation information on the suggested products to the user, means for generating a reminder based on anniversary information and notifying the user, and means for preferentially recommending regional specialties from among the suggested products. This makes it possible to provide highly satisfying suggestions that are in line with the user's emotional state and to revitalize local economies through preferential recommendations of regional specialties.

[0219] "User" refers to a person who uses the system to select souvenirs at a travel destination.

[0220] "Budget" refers to the upper limit of the amount of money that a user sets for purchasing souvenirs at a travel destination.

[0221] "Travel destination" refers to a place that a user visits during a trip.

[0222] "The recipient's tastes" refers to the preferences and interests of the person receiving the souvenir.

[0223] "Means for collecting information" refers to methods and devices for obtaining data about a user's budget, travel destinations, and partner preferences.

[0224] An "artificial intelligence model" refers to an algorithm or program that selects the most suitable product based on collected information.

[0225] An "emotion recognition engine" refers to a system that analyzes and recognizes a user's emotional state from facial expressions, tone of voice, etc.

[0226] The "means for adjusting the content of the proposal" refers to a method or device for changing the optimal product proposal based on the emotional state of the user obtained by the emotion recognition engine.

[0227] "Location information" refers to geographical data used to identify a user's current location.

[0228] "Means for selecting a purchasing location" refers to a method or device for identifying the optimal product purchasing location based on location information.

[0229] "Online Purchase Option" refers to an option for a User to purchase Products over the Internet.

[0230] "Evaluation Information" refers to feedback and reviews of products provided by past users.

[0231] "Reminder" refers to a function or message that notifies the user on special occasions or specific events.

[0232] "Regional specialty products" refer to products that are produced in a specific region and are representative of that region.

[0233] The present invention is a system that allows users to select the best souvenir for their travel destination, and is implemented through the following process. The process begins when the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. The terminal is equipped with an interface for collecting this information and sending it to a server. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to select a souvenir for someone who likes Japanese sweets."

[0234] The device sends this information to a server via the internet. The server then uses the information it receives to run an artificial intelligence (AI) model, which then suggests the best souvenir. This AI model uses past data and trend information to select the souvenir item that best suits the user's input criteria. For example, it suggests the most highly rated Japanese sweets available in Tokyo.

[0235] Furthermore, the server is equipped with an emotion recognition engine that analyzes the user's emotions through emotion recognition devices (cameras and microphones). The emotion recognition engine analyzes the user's facial expressions and tone of voice to determine their current emotional state. For example, if the user has a happy face, the emotional state is recognized as "happy."

[0236] The server has the ability to adjust the content of suggestions based on the user's emotional state as recognized by the emotion recognition engine. For example, if the user is in a "happy" emotional state, the server will recommend items that will further increase the user's joy. This can increase user satisfaction.

[0237] Next, the server selects the place to purchase the recommended product based on the user's current location information. For example, the server uses GPS data to confirm that the user is currently in "Shinjuku," searches for stores selling the recommended Japanese sweets in the Shinjuku area, and provides the user with their location information.

[0238] The server can also provide online purchasing options, allowing users to purchase souvenirs over the Internet if they don't have time to shop locally. Additionally, the server can provide reviews collected from past users, allowing users to see other people's ratings and feedback.

[0239] The server also includes a function to generate reminders based on anniversary information and notify users. For example, it can notify users that their wedding anniversary is approaching and suggest suitable souvenirs.

[0240] Finally, the server has a means to recommend regional specialties to the user. For example, if a user is looking for souvenirs in "Tokyo," the server will recommend regional specialties unique to Tokyo, such as "Tokyo Banana" and "Kaminariokoshi."

[0241] As a concrete example, let's consider a scenario in which a user inputs "Kyoto" as the travel destination, a budget of "5,000 yen," and the other person's preference of "sake," and the emotion engine recognizes the emotion of "expectation." The system uses an AI model to suggest highly rated sake in Kyoto and provides information on the nearest store to purchase it from the user's current location. At the same time, the system also provides links to online shops, reviews from past users, and reminders related to the next anniversary, and prioritizes recommendations of famous sake, a Kyoto specialty.

[0242] An example of a specific prompt for a generative AI model is, "Please suggest a souvenir for someone who is traveling to Kyoto, has a budget of 5,000 yen, and likes sake. The user is currently in an emotional state of expectation."

[0243] In this way, AI makes appropriate suggestions based on the user's budget and preferences, and the emotion engine makes suggestions that match the user's emotions, helping them choose souvenirs that will leave them satisfied. Recommending local specialties also contributes to the development of local economies.

[0244] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0245] Step 1: The user uses the terminal to input information such as travel destination, budget, partner preferences, etc. The input information is sent to the server through the interface.

[0246] Input: "Travel destination (e.g. Tokyo)", "Budget (e.g. 3,000 yen)", "Partner's preferences (e.g. Japanese sweets)"

[0247] Output: Request data sent from the terminal to the server

[0248] Step 2: The server receives the information sent from the device and inputs it into an artificial intelligence (AI) model, which then selects the best souvenir based on past data and trend information.

[0249] Input: User's "travel destination", "budget", and "preferences" data

[0250] Data processing / calculation: The AI ​​model analyzes this data and uses historical databases and trend algorithms to extract the most suitable products.

[0251] Output: Data suggesting the best souvenirs (e.g., highly rated Japanese sweets available in Tokyo)

[0252] Step 3: The server uses an emotion recognition engine to collect the user's emotion data from the emotion recognition device (camera or microphone) and recognize the user's current emotional state.

[0253] Input: User's facial expressions and tone of voice obtained from emotion recognition device

[0254] Data processing / calculation: An emotion recognition engine analyzes this data and classifies the emotional state as "happy," for example.

[0255] Output: Data on the user's emotional state (e.g., "happy")

[0256] Step 4: The server adjusts the suggestions based on the emotional state data. Appropriate suggestions are made based on the emotional state.

[0257] Input: optimal souvenir suggestion data, user emotional state data

[0258] Data processing / calculation: Filtering and adjusting the suggestions to reselect the souvenir that best suits the user's emotional state.

[0259] Output: Tailored souvenir suggestion data (e.g. Japanese sweets in special packaging)

[0260] Step 5: The server selects the recommended product purchasing location based on the user's current location information and provides the specific location information of the store where the product was purchased.

[0261] Input: User's current location information (GPS data), tailored souvenir suggestion data

[0262] Data processing / calculation: Search for the nearest store to your current location and identify its location information.

[0263] Output: Location information of the nearest store (e.g., a list of stores in Shinjuku)

[0264] Step 6: The server also provides an online purchase option, allowing users to purchase souvenirs over the Internet.

[0265] Input: Adjusted souvenir suggestion data

[0266] Data processing / calculation: Generate an online shop link and provide it as a purchasing option.

[0267] Output: Online purchase option link (e.g. Japanese sweets online shop URL)

[0268] Step 7: The server collects evaluation information about the proposed souvenir and provides it to the user. It also displays reviews from past users.

[0269] Input: Adjusted souvenir suggestion data

[0270] Data processing / calculation: Obtain and organize relevant word-of-mouth information from the evaluation database.

[0271] Output: User reviews (e.g., "This Japanese sweet was really delicious!")

[0272] Step 8: The server generates a reminder based on the anniversary information and notifies the user.

[0273] Input: User's anniversary information, tailored souvenir suggestion data

[0274] Data Processing / Calculation: Schedule reminder notifications when an anniversary is approaching.

[0275] Output: Reminder notification (e.g. "Let's prepare a souvenir for our anniversary!")

[0276] Step 9: The server recommends regional specialties from the proposed products with priority.

[0277] Input: Adjusted souvenir suggestion data

[0278] Data processing / calculation: Refer to the regional specialty product database and prioritize recommendations of products unique to that region.

[0279] Output: Recommendation data for local specialties (e.g., "Tokyo Banana" and "Kaminariokoshi")

[0280] (Application example 2)

[0281] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0282] With conventional technology, it was difficult to provide optimal recommendations for souvenirs when choosing them at a travel destination, taking into account the user's personal preferences and emotional state. This resulted in users choosing inappropriate souvenirs, which reduced user satisfaction. Furthermore, recommendations of local specialties were weak, and the promotion of local economies was insufficient. It is necessary to solve these issues, provide more useful information to users, and contribute to the development of local economies.

[0283] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0284] In this invention, the server includes means for collecting information on the user's budget, travel destination, and partner's preferences, emotion recognition means for recognizing the user's emotions, means for executing an artificial intelligence model to suggest optimal souvenirs to the user based on the collected information and the emotional state obtained by the emotion recognition means, means for selecting a place to purchase the suggested souvenirs from location information, means for providing online purchase options for the suggested souvenirs, means for collecting word-of-mouth information on the suggested souvenirs and providing it to the user, means for generating reminders based on anniversary information and notifying the user, and means for preferentially recommending regional specialties from among the suggested souvenirs. This makes it possible to suggest optimal souvenirs tailored to the user's emotional state and also to preferentially recommend regional specialties.

[0285] A "user budget" is a monetary limit that a user is willing to spend on a particular product or service.

[0286] A "travel destination" is a geographic location or destination that a user plans to visit.

[0287] "The recipient's preferences" refer to the things or tastes that the person receiving the souvenir is particularly interested in.

[0288] "Means of collecting information" refers to the interface and functions for obtaining the necessary data from the user.

[0289] "Emotion recognition means" refers to devices or algorithms that evaluate and identify a user's emotional state, such as facial expressions or voice.

[0290] An "artificial intelligence model" is a computer program that uses specific algorithms and statistical models to analyze data and suggest the best souvenirs for users.

[0291] The "means for selecting a place to purchase" refers to a function for identifying the most suitable place to purchase based on the user's current location information, etc.

[0292] "Means for providing online purchase options" refers to a function that provides links and information that allow users to purchase souvenirs over the Internet.

[0293] "Means for collecting and providing word-of-mouth information" refers to a function for collecting ratings and reviews from past purchasers and displaying that information to users.

[0294] "Means for generating and notifying reminders based on anniversary information" refers to a function that creates reminders for the user's anniversaries or specific events and notifies the user.

[0295] The "means for preferentially recommending local specialty products" is a function for preferentially recommending to the user specialty products produced in a specific region.

[0296] The present invention is a system for allowing users to select the best souvenirs at their travel destinations. The system includes the following components:

[0297] First, the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. For example, the user might input, "I'm traveling to Kyoto, my budget is 5,000 yen, and I want to choose a souvenir for someone who likes sake." The terminal provides an interface that sends the input information to the server.

[0298] Next, the server uses the received information to suggest the best souvenirs using an AI model. This AI model selects souvenir items that best fit the user's input criteria based on past data and trend information. Specifically, the AI ​​model analyzes the user's input criteria and suggests the best items from products specific to the travel destination.

[0299] Furthermore, the server uses emotion recognition means to recognize the user's emotional state. It analyzes the user's facial expressions and tone of voice through emotion recognition devices (such as cameras and microphones) to understand the user's current emotional state. For example, if the user has a happy face, the server recognizes the user's emotional state as "happy."

[0300] The server adjusts the suggestions based on the user's emotional state. For example, if the user is in a "happy" emotional state, it will recommend souvenirs that will further enhance the user's joyful mood. In this way, by making suggestions that are in line with the user's emotions, the server helps the user choose souvenirs that will give them greater satisfaction.

[0301] The server also searches for recommended souvenir purchasing locations based on the user's current location information. It provides the location information of the nearest store from the user's current location or a link to an online shop. This allows users to purchase souvenirs over the Internet even if they don't have time to buy them locally.

[0302] In addition, the server collects and provides user-review information, including information on the evaluations and experiences of past purchasers, to assist users in making purchasing decisions.

[0303] The server generates reminders based on the user's anniversary information and notifies the user, allowing the user to select the perfect souvenir for a specific anniversary or event.

[0304] Finally, the server includes a means for preferentially recommending regional specialties. By preferentially recommending regional specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Kyoto," the server can recommend Kyoto-specific specialties, thereby contributing to the spread of local culture and specialties.

[0305] Examples:

[0306] If the user inputs "Kyoto" as the travel destination, a budget of "5,000 yen," and the other person's preference of "sake," and the emotion of "expectation" is recognized from the camera image, the system will make specific suggestions such as the following.

[0307] Recommended souvenir: Kyoto's famous local sake

[0308] Where to buy: Select local stores

[0309] Online option: Online shop link for the product

[0310] Example prompt sentence:

[0311] The user has selected "Kyoto" as their travel destination, their budget is "5000 yen", and their partner's preference is "sake". The user's emotional state is "expectation". Please suggest the best sake souvenir. Also provide where to buy it and online options.

[0312] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0313] Step 1:

[0314] The user uses the terminal to input information such as the travel destination, budget, and the partner's preferences.

[0315] Input: Travel destination (e.g. Kyoto), budget (5,000 yen), partner's preference (sake)

[0316] Output: User input data

[0317] Specific operation: The user enters the required information through the device interface, and the data is saved in the device.

[0318] Step 2:

[0319] The terminal transmits the user input data to the server.

[0320] Input: User-entered data

[0321] Output: User data sent to the server

[0322] Specific operation: The terminal transmits the collected user input data to a server via the Internet.

[0323] Step 3:

[0324] Based on the user data received by the server, a generative AI model is used to suggest the best souvenir.

[0325] Input: User data sent to the server

[0326] Output: Perfect souvenir item

[0327] Specific operation: The server runs an AI model based on the received data and selects the souvenir that best suits the user's requirements.

[0328] Step 4:

[0329] The server uses emotion recognition means to recognize the emotional state of the user.

[0330] Input: User facial or voice data

[0331] Output: Emotional state (e.g., "happy," "expected")

[0332] How it works: The server analyzes data obtained from the camera and microphone and uses emotion recognition models to identify the user's emotional state.

[0333] Step 5:

[0334] The server adjusts the souvenir suggestions based on the emotional state.

[0335] Input: Best souvenir item, user's emotional state

[0336] Output: Tailored souvenir suggestions

[0337] Specific operation: The server selects souvenirs that match the user's emotional state and updates the recommendations.

[0338] Step 6:

[0339] The server selects the place to purchase the suggested souvenir based on the location information.

[0340] Input: Best souvenir item, user's current location

[0341] Output: Location of nearest store

[0342] Specific operation: The server obtains the user's current location information and searches for the nearest store that offers the best souvenirs.

[0343] Step 7:

[0344] The server provides an online purchase option for the suggested souvenirs.

[0345] Enter: Perfect souvenir item

[0346] Output: Online store link

[0347] What it does: The server searches a database on the Internet and generates links to purchase the suggested souvenirs online.

[0348] Step 8:

[0349] The server collects word-of-mouth information about the proposed souvenirs and provides it to the user.

[0350] Enter: Perfect souvenir item

[0351] Output: Reviews

[0352] Specific operation: The server collects reviews and ratings from past buyers and selects the data to provide to the user.

[0353] Step 9:

[0354] The server generates a reminder based on the anniversary information and notifies the user.

[0355] Input: User's anniversary information

[0356] Output: Reminder notification

[0357] Specific operation: The server generates reminders based on the user's anniversary information and sends notifications to the user at the specified time.

[0358] Step 10:

[0359] The server will prioritize recommendations of local specialties.

[0360] Input: Best souvenir items, local specialty information

[0361] Output: A list of recommended local specialties

[0362] Specific operation: The server prioritizes and recommends local specialties based on the user's input conditions and information on local specialties, and creates suggestions.

[0363] 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.

[0364] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0365] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0366] [Second embodiment]

[0367] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0368] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0369] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[0370] 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.

[0371] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0372] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0373] 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. 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.

[0374] 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.

[0375] 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 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.

[0376] 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.

[0377] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0378] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0379] This invention is a system that allows users to select the best souvenirs for their travels, and AI makes suggestions based on information such as budget, destination, and the recipient's preferences. This system is specifically implemented as follows.

[0380] First, the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. The terminal provides an interface to send this information to the server. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets."

[0381] The server uses an AI model to recommend the best souvenir based on the received user data. This AI model selects souvenir items that best fit the user's input criteria based on past data and trend information.

[0382] The server then selects a place to purchase the recommended souvenir based on the location information. Specifically, it searches for the nearest store that offers the recommended souvenir based on the user's current location information and provides the user with the location information of that store.

[0383] The server also provides the option of souvenirs that can be purchased online, allowing users to purchase souvenirs over the Internet even if they do not have time to purchase them locally.

[0384] Furthermore, the server collects and provides user-review information, which is information about the evaluations and experiences of past purchasers, to help users make purchasing decisions.

[0385] The server also generates reminders based on the user's anniversary information and notifies the user, allowing the user to select the perfect souvenir for a specific anniversary or event.

[0386] Finally, the server includes a means for preferentially recommending local specialties. By preferentially recommending local specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Tokyo," the server can recommend specialties unique to Tokyo, thereby contributing to the spread of local culture and specialties.

[0387] For example, if a user inputs "Kyoto" as their travel destination, a budget of "5,000 yen," and "sake" as their partner's preference, the system will suggest the best sake based on past data and trends. It will then suggest the nearest store to the user's current location or provide a link to an online shop. It will also display reviews from past users and set reminders related to upcoming anniversaries. It also contributes to promoting local specialties by prioritizing recommendations of sake that is particularly famous in Kyoto.

[0388] In this way, the system of this invention uses AI to make appropriate suggestions based on the user's budget and preferences, eliminating the hassle of choosing souvenirs and improving the travel experience. In addition, by recommending local specialties, it can contribute to revitalizing local economies.

[0389] The processing flow will be explained below.

[0390] Step 1:

[0391] The terminal provides the user with an interface to input budget, destination, and partner preferences. The user enters the information in the appropriate fields and clicks the submit button.

[0392] Step 2:

[0393] The terminal sends the information entered by the user, such as budget, travel destination, and partner preferences, to the server, which is then ready to receive the user's request.

[0394] Step 3:

[0395] The server uses an AI model to suggest the best souvenirs based on the received user data. The AI ​​model analyzes past data, trends, and the purchasing history of other users to generate a list of suggested souvenirs.

[0396] Step 4:

[0397] The server searches for a place to purchase each souvenir based on the created souvenir list, finds the nearest store based on the user's current location, and acquires its location information.

[0398] Step 5:

[0399] The server retrieves online shopping links for each item to provide online purchasing options for the suggested souvenirs, and if available, provides the link to the user.

[0400] Step 6:

[0401] The server collects word-of-mouth information about the proposed souvenirs, including reviews and ratings left by past buyers, and gathers data to provide useful information to users.

[0402] Step 7:

[0403] The server generates reminders based on the user's anniversary information, helping them select the appropriate souvenir for a specific anniversary or event.

[0404] Step 8:

[0405] The server prioritizes and recommends regional specialties from among the suggested souvenirs. Based on data related to regional specialties, it recommends local products to help revitalize the local economy.

[0406] Step 9:

[0407] The server then sends all the results back to the device, including a list of the best souvenirs, where to buy, online options, reviews, reminders, and preferred recommendations for local specialties.

[0408] Step 10:

[0409] The terminal displays the information received from the server to the user, who then selects from the list of suitable souvenirs displayed on the terminal screen and obtains the desired product using the provided purchasing locations or online options.

[0410] Example 1

[0411] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0412] When choosing souvenirs, users currently spend a lot of time and effort selecting the best one from a wide range of options. Furthermore, there are a lack of effective ways to purchase local specialties and to refer to word-of-mouth information. This makes it difficult for users to choose a souvenir that satisfies them. Furthermore, there is no system that prioritizes and recommends local specialties, which is a problem that does not contribute to the development of local economies.

[0413] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0414] In this invention, the server includes: means for collecting information on a user's budget, travel destination, and other party preferences; means for running a generative AI model to suggest optimal souvenirs to the user based on the collected information; means for selecting a purchase location for the suggested souvenir based on location information; means for providing online purchase options for the suggested souvenir; means for collecting and providing user reviews about the suggested souvenir; means for generating reminders based on anniversary information and notifying the user; means for preferentially recommending regional specialties from among the suggested souvenirs; means for selecting and providing information about the optimal purchase location based on the user's current location information; means for providing links to online purchases of the suggested souvenirs if they are available; and means for selecting souvenirs based on past trend information using the generative AI model. This allows users to easily select and purchase optimal souvenirs and refer to reviews, and further contributes to the development of local economies by recommending regional specialties. A "user" refers to an individual who uses a terminal to input information such as a travel destination, budget, and other party preferences.

[0415] A "terminal" is a device through which a user inputs information such as travel destination, budget, and the other person's preferences, and includes smartphones, PCs, tablets, etc.

[0416] "Server" refers to a central computer system that processes information received from users and suggests the most suitable souvenirs.

[0417] "Budget" refers to the range of amounts set by the user for purchasing souvenirs.

[0418] "Travel destination" indicates a place where the user is traveling and includes geographic information about the place.

[0419] "Recipient's preferences" is information input by the user, and includes elements related to the recipient's tastes and preferences.

[0420] A "generative AI model" is an artificial intelligence model used to suggest the best souvenirs based on information entered by the user.

[0421] "Online Purchase Option" refers to the means provided for users to purchase suggested souvenirs over the Internet.

[0422] "Word-of-mouth information" refers to information including ratings and reviews provided by users who have previously purchased a product.

[0423] "Reminder" refers to an alert or message provided to notify a user of a particular anniversary or event.

[0424] "Regional specialty products" refer to products that are produced in a particular region and are characteristic of that region.

[0425] "Location information" refers to information including geographical data indicating a user's current location or a specific point.

[0426] "Purchase location" refers to the physical store or online shop where the suggested souvenir can be purchased.

[0427] "Past trend information" refers to information based on market trends and data on popular products.

[0428] This invention relates to a system for selecting the perfect souvenir for a travel destination. Users use a terminal to input information such as their travel destination, budget, and the recipient's preferences. Based on the information received, a server suggests the perfect souvenir and provides information such as where to buy it, online purchasing options, and reviews. The system also provides reminders based on anniversary information and recommends local specialties.

[0429] First, the user uses a device (such as a smartphone or PC) to input information such as the travel destination, budget, and the recipient's preferences. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets." The necessary information is then sent from the device to the server.

[0430] Based on the received user data, the server uses a generative AI model, a TensorFlow neural network model implemented in Python, to suggest the best souvenir. This generative AI model selects the souvenir item that best suits the user's input criteria based on past data and trend information. For example, if a user inputs a prompt such as "Travel destination: Tokyo, Budget: 3,000 yen, Favorites: Japanese sweets," the model will select Japanese sweets for Tokyo based on past trend information.

[0431] Next, the server selects the recommended souvenir purchasing location based on the location information. Specifically, it uses a location information API to obtain the user's current location and searches the PostgreSQL database for related stores within a specific range based on those coordinates. As a result, information on the nearest store is provided to the user. For example, if the user is near Tokyo Station, information on nearby Japanese confectionery stores is provided.

[0432] The server also provides souvenir options that can be purchased online. It uses the Amazon API and Rakuten API to check whether the suggested souvenirs are available online, and if so, generates and provides a link. This allows users to purchase souvenirs over the Internet even if they don't have time to buy them locally.

[0433] The server also collects user reviews and provides them to users. Specifically, it uses Python's BeautifulSoup to scrape relevant user reviews from the web, formatting them, and sending them to users for viewing. For example, it displays ratings and reviews from past buyers of the suggested Japanese sweets.

[0434] The server also generates reminders based on the anniversary information and notifies the user. It references the anniversary database and uses Firebase Cloud Messaging to trigger reminder notifications for specific dates. For example, when a user's wedding anniversary is approaching, a notification is sent with a suggestion for the perfect souvenir.

[0435] In addition, the server prioritizes recommendations of local specialties. By referencing a database of local specialties, it selects and recommends specialties that correspond to the user's travel destination (for example, Japanese sweets from Tokyo), which contributes to the development of the local economy.

[0436] An example of a prompt is as follows:

[0437] "Destination: Tokyo, Budget: 3000 yen, Favorites: Japanese sweets"

[0438] "Travel destination: Kyoto, Budget: 5,000 yen, Favorites: Sake"

[0439] In this way, the system of this invention uses AI to make appropriate suggestions based on the user's budget and preferences, eliminating the hassle of choosing souvenirs and improving the travel experience. In addition, by recommending local specialties, it also contributes to revitalizing the local economy.

[0440] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0441] Step 1: Enter your information

[0442] The user uses a device to input information such as travel destination, budget, and the other person's preferences. Specifically, the user enters information such as "Travel destination: Kyoto, Budget: 5,000 yen, Other person's preference: Japanese sake" into a form displayed on the screen of their smartphone or PC, and clicks the send button. This causes the input information to be displayed on the device screen, and the device then sends this information to the server.

[0443] Step 2: Send data from the device to the server

[0444] The terminal sends the information entered by the user to the server. Specifically, the terminal generates an HTTP request and sends the input information to the server in JSON format. This request includes the travel destination, budget, and the other person's preferences. The input is the information "Travel destination: Kyoto, Budget: 5,000 yen, Other person's preference: Sake," and the output is the information received on the server side.

[0445] Step 3: Server selects the gift

[0446] The server uses a generative AI model to select the optimal souvenir based on the received user data. Specifically, the server calls a TensorFlow neural network model implemented in Python and inputs the received information as a prompt. The generative AI model uses an internal database and past trend information to select souvenir items that fit the input criteria. The input is information such as "Travel destination: Kyoto, Budget: 5,000 yen, Recipient's preference: Sake," and the output is a recommended sake item.

[0447] Step 4: Choose a place to buy

[0448] The server selects the recommended souvenir purchasing location based on location information. Specifically, the server obtains the user's current location using a location information API and searches the PostgreSQL database for nearby stores based on those coordinates. The server extracts information about related stores within a specific range and selects the nearest store. The input is the user's current location information, and the output is information about the nearest store where the souvenir can be purchased.

[0449] Step 5: Offer online purchasing options

[0450] The server also provides souvenir options that can be purchased online. Specifically, the server uses the Amazon API or Rakuten API to check whether the recommended souvenirs are available for purchase online. If so, it generates and provides a corresponding link. The input is the information about the recommended souvenir item, and the output is the link to the corresponding online shop.

[0451] Step 6: Collect and provide reviews

[0452] The server collects reviews about recommended souvenirs and provides them to users. Specifically, the server uses Python's BeautifulSoup to scrape relevant reviews from the web and format them in a user-viewable format. The input is the recommended souvenir item information, and the output is the reviews about that item.

[0453] Step 7: Set reminders and notifications

[0454] The server generates a reminder based on the anniversary information and notifies the user. Specifically, the server references the anniversary database and uses Firebase Cloud Messaging to send a reminder notification for a specific date. The input is the user's anniversary information, and the output is the reminder notification.

[0455] Step 8: Recommend local specialties

[0456] The server prioritizes regional specialty products from the recommended souvenirs. Specifically, the server references a regional specialty product database and prioritizes the specialty products that correspond to the user's travel destination. The input is the travel destination and specialty product data, and the output is the suggested regional specialty products.

[0457] (Application example 1)

[0458] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0459] Conventional systems make it difficult for users to select the perfect souvenir when visiting a particular location, making it difficult to improve the quality of their travel experience. Furthermore, virtual shopping experiences using virtual reality devices were not readily available, preventing users from enjoying a detailed remote shopping experience. Furthermore, there were insufficient means to effectively recommend local specialties and contribute to the development of the local economy.

[0460] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0461] In this invention, the server includes: means for collecting information on a user's budget, travel destination, and the recipient's preferences; means for running an artificial intelligence model to suggest optimal souvenirs to the user based on the collected information; means for selecting a place to purchase the suggested souvenirs based on location information; means for providing online purchasing options for the suggested souvenirs; means for collecting word-of-mouth information about the suggested souvenirs and providing it to the user; means for generating reminders based on anniversary information and notifying the user; means for preferentially recommending regional specialties from among the suggested souvenirs; and means for linking with a virtual reality device that allows the user to explore virtual stores and confirm the souvenirs they have selected. This allows users to enjoy a sophisticated shopping experience using virtual reality from their travel destination or at home, eliminating the need to select the optimal souvenir and contributing to the spread of regional specialties and the development of the local economy.

[0462] "User's budget" is the upper limit of the amount that a user sets for the products that he or she wishes to purchase.

[0463] "Travel destination" refers to a place or city that the user plans to visit.

[0464] "Preferences of the recipient" refers to the specific tastes and hobbies of the recipient to whom the user is giving a souvenir.

[0465] "Means for collecting information" refers to a method or device for obtaining the necessary information from the user.

[0466] An "artificial intelligence model" is an algorithm or system that learns from past data and trend information and makes optimal suggestions.

[0467] "Purchase location" refers to the geographic location or store where the user can actually purchase the recommended souvenir.

[0468] "Location Information" means data regarding a user's current geographic location.

[0469] An "online purchase option" is a choice that allows a user to purchase products over the Internet.

[0470] "Word-of-mouth information" is information about ratings and comments made by past users about products.

[0471] A "reminder" is a function or system that notifies users of specific dates, times, or anniversaries.

[0472] "Regional specialties" are products or foods that are produced in a particular region and are representative of that region.

[0473] A "virtual reality device" is a device that allows users to immerse themselves in a virtual space and experience it, and mainly includes head-mounted displays and VR goggles.

[0474] This invention provides a system that allows users to select the best souvenirs for their travels, with AI making suggestions based on information such as budget, destination, and the recipient's preferences, allowing users to efficiently select souvenirs.

[0475] First, the user uses a device to input information such as the travel destination, budget, and the recipient's preferences. The device provides an interface that sends this information to the server. For example, a user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets." This information is then sent to the server via a web browser or a dedicated application.

[0476] The server uses an artificial intelligence model to recommend the best souvenir based on the received user data. This artificial intelligence model is built using frameworks such as TensorFlow and PyTorch. The model learns from past data and trend information to select the souvenir item that best suits the user's input criteria. For example, "Japanese sweets from Tokyo" may be recommended.

[0477] Next, the server selects the place to purchase the recommended souvenir based on the location information. Specifically, it obtains the user's current location information using Google Maps API or similar, and searches for the nearest store that offers the recommended souvenir. The location information of that store is then provided to the user.

[0478] The server also provides the option of souvenirs available for purchase online, allowing users to purchase souvenirs over the Internet even if they don't have time to do so locally. Users can click on the provided link to access the online shop and complete the purchase.

[0479] Furthermore, the server collects and provides user-review information, which includes information on the evaluations and experiences of past purchasers. This information helps users confirm the reliability of the recommended souvenirs and assists them in making a purchasing decision.

[0480] The server also generates reminders based on the user's anniversary information and notifies the user. This function is often implemented using the Google Calendar API, and helps users choose the perfect souvenir for a particular anniversary or event.

[0481] Finally, the server includes a means for preferentially recommending local specialties. By preferentially recommending local specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Tokyo," the server can recommend specialties unique to Tokyo, thereby contributing to the spread of local culture and specialties.

[0482] Furthermore, this invention can be applied to virtual stores. By using a virtual reality device such as a head-mounted display or VR goggles, users can visit stores in a virtual space and check recommended souvenirs. Users can operate an avatar to explore the virtual store and experience the realistic shopping experience of the selected souvenir.

[0483] As a concrete example, consider the case where a user enters "Kyoto" as the travel destination, a budget of "5,000 yen," and "sake" as the recipient's preference. Based on this information, the server will recommend the most suitable sake based on past data and trend information. Furthermore, based on the user's current location, the server will provide the nearest store where the sake can be purchased and also provide a link to the online shop. Reviews will also be displayed, and a reminder related to the next anniversary will be set. Recommendations will also be prioritized for regional specialties, such as sake that is particularly famous in Kyoto.

[0484] Example prompt sentence:

[0485] Travel destination: Kyoto

[0486] Budget: 5,000 yen

[0487] Partner's preference: Sake

[0488] Current location: Tokyo

[0489] In this way, the system of this invention improves the travel experience while reducing the effort required for souvenir selection by making appropriate suggestions based on the user's budget and preferences using AI. In addition, by recommending local specialties, it can contribute to revitalizing the local economy.

[0490] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0491] Step 1:

[0492] The user uses a device to input information such as travel destination, budget, and the other person's preferences. The user provides information through an input form on the device, such as "Travel destination: Tokyo, budget: 3,000 yen, other person's preferences: Japanese sweets." This information is structured in JSON format or similar and sent to the server.

[0493] Step 2:

[0494] The server analyzes the information received from the user. To analyze the information, the server accesses a database and searches for past data and trend information. This process uses SQL queries and other methods to extract information based on the input travel destination, budget, and preferences. As a result of the analysis, a list of multiple potential souvenir items is generated.

[0495] Step 3:

[0496] The server runs an artificial intelligence model (using, for example, TensorFlow or PyTorch) based on the list of candidate items. The model learns from past user data and trend information and selects the souvenir item that best suits the input criteria. This process identifies recommended items such as "Japanese sweets from Tokyo."

[0497] Step 4:

[0498] The server selects the place to purchase the recommended souvenir items. It uses the Google Maps API to obtain the user's current location and search for the nearest store. The store's location is selected by calculating the distance between the user's current location and the destination based on the data obtained from Google Maps.

[0499] Step 5:

[0500] The server provides online purchasing options and generates links to online shops where the suggested souvenir items can be purchased in case the user is unable to purchase them locally. This is done by using the API of each online shop to search for the product ID and obtain the link to its purchase page.

[0501] Step 6:

[0502] The server collects reviews of recommended souvenir items and provides them to users. It retrieves ratings and comments from past users from a database such as MongoDB and displays them along with the analysis results. This allows users to confirm the reliability of the products.

[0503] Step 7:

[0504] The server generates reminders based on the anniversary information and notifies the user. It uses the Google Calendar API to retrieve the user's anniversary data and sets notifications when the date approaches. Notifications are sent as emails or in-app notifications.

[0505] Step 8:

[0506] The server prioritizes recommendations of local specialty products. Based on the analysis results, it extracts specialty product data related to the user's travel destination and adds them to the recommendation list with priority. This contributes to the spread of specialty products and the development of the local economy.

[0507] Step 9:

[0508] Users use a virtual reality device to explore virtual stores. They wear a head-mounted display and check recommended souvenir items in the virtual space. Users can control an avatar to visit stores and check detailed souvenir information and reviews in real time.

[0509] In this way, a system is constructed that realizes complex processing through the roles of the server, terminal, and user, and supports efficient and effective souvenir selection.

[0510] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0511] This invention is a system that allows users to select the best souvenirs for their travels. AI makes suggestions based on information such as budget, destination, and the recipient's preferences. It also has a function to adjust the suggestions by combining it with an emotion engine that recognizes the user's emotions. This system is specifically implemented as follows.

[0512] First, the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. The terminal provides an interface to send this information to the server. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets."

[0513] The server uses an AI model to suggest the best souvenir based on the received user data. This AI model selects the souvenir item that best suits the user's input criteria based on past data and trend information.

[0514] Furthermore, the server uses an emotion engine to recognize the user's emotions. It analyzes the user's facial expressions and tone of voice through emotion recognition devices (such as cameras and microphones) to understand their current emotional state. For example, if the user has a happy face, the server recognizes their emotional state as "happy."

[0515] The server adjusts the suggestions based on the user's emotional state as recognized by the emotion engine. For example, if the user is in a "happy" emotional state, the server will recommend souvenirs that will further enhance the user's joyful mood. In this way, suggestions that are tailored to the user's emotions will help the user select souvenirs that will provide greater satisfaction.

[0516] The server also monitors the user's emotional state in real time and updates the suggestions as needed. For example, if the user suddenly changes their mood or is not interested in a suggested souvenir, it can instantly suggest other options.

[0517] Furthermore, the server learns the user's past emotional data and reflects it in future souvenir suggestions, enabling more accurate suggestions based on the user's past emotional state and the type of souvenir they chose.

[0518] The server then selects a place to purchase the recommended souvenir based on the location information. Specifically, it searches for the nearest store that offers the recommended souvenir based on the user's current location information and provides the user with the location information of that store.

[0519] The server also provides the option of souvenirs that can be purchased online, allowing users to purchase souvenirs over the Internet even if they do not have time to purchase them locally.

[0520] Furthermore, the server collects and provides user-review information, which is information about the evaluations and experiences of past purchasers, to help users make purchasing decisions.

[0521] The server also generates reminders based on the user's anniversary information and notifies the user, allowing the user to select the perfect souvenir for a specific anniversary or event.

[0522] Finally, the server includes a means for preferentially recommending local specialties. By preferentially recommending local specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Tokyo," the server can recommend specialties unique to Tokyo, thereby contributing to the spread of local culture and specialties.

[0523] For example, if a user inputs "Kyoto" as their travel destination, a budget of "5,000 yen," and the other person's preference of "sake," and the emotion engine recognizes the emotion of "expectation," the system will suggest the most suitable sake based on past data and trends. The system will then provide the nearest store to the user's current location or a link to an online shop. It will also display reviews from past users and set reminders related to upcoming anniversaries. By prioritizing recommendations of sake that is particularly famous in Kyoto, the system also contributes to promoting local specialties.

[0524] In this way, the system of this invention not only uses AI to make appropriate suggestions based on the user's budget and preferences, but also uses an emotion engine to make suggestions that match the user's emotions, helping them choose souvenirs with greater satisfaction. Furthermore, by recommending local specialties, it can also contribute to revitalizing local economies.

[0525] The processing flow will be explained below.

[0526] Step 1:

[0527] The terminal provides the user with an interface to input budget, destination, and partner preferences. The user enters the information in the appropriate fields and clicks the submit button.

[0528] Step 2:

[0529] The terminal sends the information entered by the user, such as budget, travel destination, and partner preferences, to the server, which is then ready to receive the user's request.

[0530] Step 3:

[0531] The server uses an artificial intelligence model to suggest the best souvenir based on the received user data. This AI model analyzes past data and trend information to select the souvenir item that best suits the user's requirements.

[0532] Step 4:

[0533] The server uses an emotion engine to recognize the user's emotions. It analyzes the user's facial expressions and voice through the camera and microphone connected to the device to determine their current emotional state. For example, if the user is smiling, it will recognize that they are "happy."

[0534] Step 5:

[0535] The server adjusts the suggestions based on the user's emotional state as recognized by the emotion engine. For example, if the user is in a "happy" emotional state, the server will recommend souvenirs that will further enhance the user's joyful mood.

[0536] Step 6:

[0537] The server selects the place to purchase the suggested souvenir based on the user's current location information. Based on the user's current location information, it searches for the nearest store that offers the recommended souvenir and obtains the store's location information.

[0538] Step 7:

[0539] The server retrieves online shopping links for each item to provide online purchasing options for the suggested souvenirs, and if available, provides the link to the user.

[0540] Step 8:

[0541] The server collects word-of-mouth information about the proposed souvenirs, pulls out reviews and ratings left by past buyers from a database, and provides them to the user.

[0542] Step 9:

[0543] The server generates reminders based on the user's anniversary information, helping them select the appropriate souvenir for a specific anniversary or event.

[0544] Step 10:

[0545] The server prioritizes regional specialty products from among the recommended souvenirs. Based on data related to regional specialty products, the server prioritizes local products to support the revitalization of the local economy.

[0546] Step 11:

[0547] The server then sends all the results back to the device, including a list of the best souvenirs, where to buy, online options, reviews, reminders, and preferred recommendations for local specialties.

[0548] Step 12:

[0549] The terminal displays the information received from the server to the user, who then selects from the list of suitable souvenirs displayed on the terminal screen and obtains the desired product using the provided purchasing locations or online options.

[0550] As a specific example, if a user inputs "Kyoto" as their travel destination, a budget of "5,000 yen," and the recipient's preference of "sake," and the emotion engine recognizes the emotion of "expectation," the server will use an AI model to suggest the most suitable sake. The server will then provide the store closest to the user's current location, along with reviews. It will also provide an online purchase link. Furthermore, a reminder related to the next anniversary will be generated, with priority given to recommendations of local sake, a Kyoto specialty. Based on this information, users can select and purchase the perfect souvenir.

[0551] Example 2

[0552] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0553] Traditionally, choosing the right souvenirs for a trip has been challenging, especially when it comes to making optimal choices based on the user's budget and the recipient's preferences. Furthermore, there has been a lack of methods to improve satisfaction by adjusting recommendations based on the user's emotional state. Furthermore, there have been insufficient efforts to revitalize local economies through preferential recommendations of regional specialties. Therefore, there is a need for a system that collects user information, considers the user's emotional state, makes optimal recommendations, and prioritizes regional specialties.

[0554] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0555] In this invention, the server includes means for collecting information on a user's budget, travel destination, and partner preferences, means for executing an artificial intelligence model to suggest optimal products to the user based on the collected information, means for executing an emotion recognition engine to recognize the user's emotional state regarding the suggested products, means for adjusting the content of the suggestions based on the user's emotional state, means for selecting and providing a purchase location for the suggested products based on location information, means for providing an online purchase option for the suggested products, means for collecting and providing evaluation information on the suggested products to the user, means for generating a reminder based on anniversary information and notifying the user, and means for preferentially recommending regional specialties from among the suggested products. This makes it possible to provide highly satisfying suggestions that are in line with the user's emotional state and to revitalize local economies through preferential recommendations of regional specialties.

[0556] "User" refers to a person who uses the system to select souvenirs at a travel destination.

[0557] "Budget" refers to the upper limit of the amount of money that a user sets for purchasing souvenirs at a travel destination.

[0558] "Travel destination" refers to a place that a user visits during a trip.

[0559] "The recipient's tastes" refers to the preferences and interests of the person receiving the souvenir.

[0560] "Means for collecting information" refers to methods and devices for obtaining data about a user's budget, travel destinations, and partner preferences.

[0561] An "artificial intelligence model" refers to an algorithm or program that selects the most suitable product based on collected information.

[0562] An "emotion recognition engine" refers to a system that analyzes and recognizes a user's emotional state from facial expressions, tone of voice, etc.

[0563] The "means for adjusting the content of the proposal" refers to a method or device for changing the optimal product proposal based on the emotional state of the user obtained by the emotion recognition engine.

[0564] "Location information" refers to geographical data used to identify a user's current location.

[0565] "Means for selecting a purchasing location" refers to a method or device for identifying the optimal product purchasing location based on location information.

[0566] "Online Purchase Option" refers to an option for a User to purchase Products over the Internet.

[0567] "Evaluation Information" refers to feedback and reviews of products provided by past users.

[0568] "Reminder" refers to a function or message that notifies the user on special occasions or specific events.

[0569] "Regional specialty products" refer to products that are produced in a specific region and are representative of that region.

[0570] The present invention is a system that allows users to select the best souvenir for their travel destination, and is implemented through the following process. The process begins when the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. The terminal is equipped with an interface for collecting this information and sending it to a server. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to select a souvenir for someone who likes Japanese sweets."

[0571] The device sends this information to a server via the internet. The server then uses the information it receives to run an artificial intelligence (AI) model, which then suggests the best souvenir. This AI model uses past data and trend information to select the souvenir item that best suits the user's input criteria. For example, it suggests the most highly rated Japanese sweets available in Tokyo.

[0572] Furthermore, the server is equipped with an emotion recognition engine that analyzes the user's emotions through emotion recognition devices (cameras and microphones). The emotion recognition engine analyzes the user's facial expressions and tone of voice to determine their current emotional state. For example, if the user has a happy face, the emotional state is recognized as "happy."

[0573] The server has the ability to adjust the content of suggestions based on the user's emotional state as recognized by the emotion recognition engine. For example, if the user is in a "happy" emotional state, the server will recommend items that will further increase the user's joy. This can increase user satisfaction.

[0574] Next, the server selects the place to purchase the recommended product based on the user's current location information. For example, the server uses GPS data to confirm that the user is currently in "Shinjuku," searches for stores selling the recommended Japanese sweets in the Shinjuku area, and provides the user with their location information.

[0575] The server can also provide online purchasing options, allowing users to purchase souvenirs over the Internet if they don't have time to shop locally. Additionally, the server can provide reviews collected from past users, allowing users to see other people's ratings and feedback.

[0576] The server also includes a function to generate reminders based on anniversary information and notify users. For example, it can notify users that their wedding anniversary is approaching and suggest suitable souvenirs.

[0577] Finally, the server has a means to recommend regional specialties to the user. For example, if a user is looking for souvenirs in "Tokyo," the server will recommend regional specialties unique to Tokyo, such as "Tokyo Banana" and "Kaminariokoshi."

[0578] As a concrete example, let's consider a scenario in which a user inputs "Kyoto" as the travel destination, a budget of "5,000 yen," and the other person's preference of "sake," and the emotion engine recognizes the emotion of "expectation." The system uses an AI model to suggest highly rated sake in Kyoto and provides information on the nearest store to purchase it from the user's current location. At the same time, the system also provides links to online shops, reviews from past users, and reminders related to the next anniversary, and prioritizes recommendations of famous sake, a Kyoto specialty.

[0579] An example of a specific prompt for a generative AI model is, "Please suggest a souvenir for someone who is traveling to Kyoto, has a budget of 5,000 yen, and likes sake. The user is currently in an emotional state of expectation."

[0580] In this way, AI makes appropriate suggestions based on the user's budget and preferences, and the emotion engine makes suggestions that match the user's emotions, helping them choose souvenirs that will leave them satisfied. Recommending local specialties also contributes to the development of local economies.

[0581] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0582] Step 1: The user uses the terminal to input information such as travel destination, budget, partner preferences, etc. The input information is sent to the server through the interface.

[0583] Input: "Travel destination (e.g. Tokyo)", "Budget (e.g. 3,000 yen)", "Partner's preferences (e.g. Japanese sweets)"

[0584] Output: Request data sent from the terminal to the server

[0585] Step 2: The server receives the information sent from the device and inputs it into an artificial intelligence (AI) model, which then selects the best souvenir based on past data and trend information.

[0586] Input: User's "travel destination", "budget", and "preferences" data

[0587] Data processing / calculation: The AI ​​model analyzes this data and uses historical databases and trend algorithms to extract the most suitable products.

[0588] Output: Data suggesting the best souvenirs (e.g., highly rated Japanese sweets available in Tokyo)

[0589] Step 3: The server uses an emotion recognition engine to collect the user's emotion data from the emotion recognition device (camera or microphone) and recognize the user's current emotional state.

[0590] Input: User's facial expressions and tone of voice obtained from emotion recognition device

[0591] Data processing / calculation: An emotion recognition engine analyzes this data and classifies the emotional state as "happy," for example.

[0592] Output: Data on the user's emotional state (e.g., "happy")

[0593] Step 4: The server adjusts the suggestions based on the emotional state data. Appropriate suggestions are made based on the emotional state.

[0594] Input: optimal souvenir suggestion data, user emotional state data

[0595] Data processing / calculation: Filtering and adjusting the suggestions to reselect the souvenir that best suits the user's emotional state.

[0596] Output: Tailored souvenir suggestion data (e.g. Japanese sweets in special packaging)

[0597] Step 5: The server selects the recommended product purchasing location based on the user's current location information and provides the specific location information of the store where the product was purchased.

[0598] Input: User's current location information (GPS data), tailored souvenir suggestion data

[0599] Data processing / calculation: Search for the nearest store to your current location and identify its location information.

[0600] Output: Location information of the nearest store (e.g., a list of stores in Shinjuku)

[0601] Step 6: The server also provides an online purchase option, allowing users to purchase souvenirs over the Internet.

[0602] Input: Adjusted souvenir suggestion data

[0603] Data processing / calculation: Generate an online shop link and provide it as a purchasing option.

[0604] Output: Online purchase option link (e.g. Japanese sweets online shop URL)

[0605] Step 7: The server collects evaluation information about the proposed souvenir and provides it to the user. It also displays reviews from past users.

[0606] Input: Adjusted souvenir suggestion data

[0607] Data processing / calculation: Obtain and organize relevant word-of-mouth information from the evaluation database.

[0608] Output: User reviews (e.g., "This Japanese sweet was really delicious!")

[0609] Step 8: The server generates a reminder based on the anniversary information and notifies the user.

[0610] Input: User's anniversary information, tailored souvenir suggestion data

[0611] Data Processing / Calculation: Schedule reminder notifications when an anniversary is approaching.

[0612] Output: Reminder notification (e.g. "Let's prepare a souvenir for our anniversary!")

[0613] Step 9: The server recommends regional specialties from the proposed products with priority.

[0614] Input: Adjusted souvenir suggestion data

[0615] Data processing / calculation: Refer to the regional specialty product database and prioritize recommendations of products unique to that region.

[0616] Output: Recommendation data for local specialties (e.g., "Tokyo Banana" and "Kaminariokoshi")

[0617] (Application example 2)

[0618] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0619] With conventional technology, it was difficult to provide optimal recommendations for souvenirs when choosing them at a travel destination, taking into account the user's personal preferences and emotional state. This resulted in users choosing inappropriate souvenirs, which reduced user satisfaction. Furthermore, recommendations of local specialties were weak, and the promotion of local economies was insufficient. It is necessary to solve these issues, provide more useful information to users, and contribute to the development of local economies.

[0620] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0621] In this invention, the server includes means for collecting information on the user's budget, travel destination, and partner's preferences, emotion recognition means for recognizing the user's emotions, means for executing an artificial intelligence model to suggest optimal souvenirs to the user based on the collected information and the emotional state obtained by the emotion recognition means, means for selecting a place to purchase the suggested souvenirs from location information, means for providing online purchase options for the suggested souvenirs, means for collecting word-of-mouth information on the suggested souvenirs and providing it to the user, means for generating reminders based on anniversary information and notifying the user, and means for preferentially recommending regional specialties from among the suggested souvenirs. This makes it possible to suggest optimal souvenirs tailored to the user's emotional state and also to preferentially recommend regional specialties.

[0622] A "user budget" is a monetary limit that a user is willing to spend on a particular product or service.

[0623] A "travel destination" is a geographic location or destination that a user plans to visit.

[0624] "The recipient's preferences" refer to the things or tastes that the person receiving the souvenir is particularly interested in.

[0625] "Means of collecting information" refers to the interface and functions for obtaining the necessary data from the user.

[0626] "Emotion recognition means" refers to devices or algorithms that evaluate and identify a user's emotional state, such as facial expressions or voice.

[0627] An "artificial intelligence model" is a computer program that uses specific algorithms and statistical models to analyze data and suggest the best souvenirs for users.

[0628] The "means for selecting a place to purchase" refers to a function for identifying the most suitable place to purchase based on the user's current location information, etc.

[0629] "Means for providing online purchase options" refers to a function that provides links and information that allow users to purchase souvenirs over the Internet.

[0630] "Means for collecting and providing word-of-mouth information" refers to a function for collecting ratings and reviews from past purchasers and displaying that information to users.

[0631] "Means for generating and notifying reminders based on anniversary information" refers to a function that creates reminders for the user's anniversaries or specific events and notifies the user.

[0632] The "means for preferentially recommending local specialty products" is a function for preferentially recommending to the user specialty products produced in a specific region.

[0633] The present invention is a system for allowing users to select the best souvenirs at their travel destinations. The system includes the following components:

[0634] First, the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. For example, the user might input, "I'm traveling to Kyoto, my budget is 5,000 yen, and I want to choose a souvenir for someone who likes sake." The terminal provides an interface that sends the input information to the server.

[0635] Next, the server uses the received information to suggest the best souvenirs using an AI model. This AI model selects souvenir items that best fit the user's input criteria based on past data and trend information. Specifically, the AI ​​model analyzes the user's input criteria and suggests the best items from products specific to the travel destination.

[0636] Furthermore, the server uses emotion recognition means to recognize the user's emotional state. It analyzes the user's facial expressions and tone of voice through emotion recognition devices (such as cameras and microphones) to understand the user's current emotional state. For example, if the user has a happy face, the server recognizes the user's emotional state as "happy."

[0637] The server adjusts the suggestions based on the user's emotional state. For example, if the user is in a "happy" emotional state, it will recommend souvenirs that will further enhance the user's joyful mood. In this way, by making suggestions that are in line with the user's emotions, the server helps the user choose souvenirs that will give them greater satisfaction.

[0638] The server also searches for recommended souvenir purchasing locations based on the user's current location information. It provides the location information of the nearest store from the user's current location or a link to an online shop. This allows users to purchase souvenirs over the Internet even if they don't have time to buy them locally.

[0639] In addition, the server collects and provides user-review information, including information on the evaluations and experiences of past purchasers, to assist users in making purchasing decisions.

[0640] The server generates reminders based on the user's anniversary information and notifies the user, allowing the user to select the perfect souvenir for a specific anniversary or event.

[0641] Finally, the server includes a means for preferentially recommending regional specialties. By preferentially recommending regional specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Kyoto," the server can recommend Kyoto-specific specialties, thereby contributing to the spread of local culture and specialties.

[0642] Examples:

[0643] If the user inputs "Kyoto" as the travel destination, a budget of "5,000 yen," and the other person's preference of "sake," and the emotion of "expectation" is recognized from the camera image, the system will make specific suggestions such as the following.

[0644] Recommended souvenir: Kyoto's famous local sake

[0645] Where to buy: Select local stores

[0646] Online option: Online shop link for the product

[0647] Example prompt sentence:

[0648] The user has selected "Kyoto" as their travel destination, their budget is "5000 yen", and their partner's preference is "sake". The user's emotional state is "expectation". Please suggest the best sake souvenir. Also provide where to buy it and online options.

[0649] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0650] Step 1:

[0651] The user uses the terminal to input information such as the travel destination, budget, and the partner's preferences.

[0652] Input: Travel destination (e.g. Kyoto), budget (5,000 yen), partner's preference (sake)

[0653] Output: User input data

[0654] Specific operation: The user enters the required information through the device interface, and the data is saved in the device.

[0655] Step 2:

[0656] The terminal transmits the user input data to the server.

[0657] Input: User-entered data

[0658] Output: User data sent to the server

[0659] Specific operation: The terminal transmits the collected user input data to a server via the Internet.

[0660] Step 3:

[0661] Based on the user data received by the server, a generative AI model is used to suggest the best souvenir.

[0662] Input: User data sent to the server

[0663] Output: Perfect souvenir item

[0664] Specific operation: The server runs an AI model based on the received data and selects the souvenir that best suits the user's requirements.

[0665] Step 4:

[0666] The server uses emotion recognition means to recognize the emotional state of the user.

[0667] Input: User facial or voice data

[0668] Output: Emotional state (e.g., "happy," "expected")

[0669] How it works: The server analyzes data obtained from the camera and microphone and uses emotion recognition models to identify the user's emotional state.

[0670] Step 5:

[0671] The server adjusts the souvenir suggestions based on the emotional state.

[0672] Input: Best souvenir item, user's emotional state

[0673] Output: Tailored souvenir suggestions

[0674] Specific operation: The server selects souvenirs that match the user's emotional state and updates the recommendations.

[0675] Step 6:

[0676] The server selects the place to purchase the suggested souvenir based on the location information.

[0677] Input: Best souvenir item, user's current location

[0678] Output: Location of nearest store

[0679] Specific operation: The server obtains the user's current location information and searches for the nearest store that offers the best souvenirs.

[0680] Step 7:

[0681] The server provides an online purchase option for the suggested souvenirs.

[0682] Enter: Perfect souvenir item

[0683] Output: Online store link

[0684] What it does: The server searches a database on the Internet and generates links to purchase the suggested souvenirs online.

[0685] Step 8:

[0686] The server collects word-of-mouth information about the proposed souvenirs and provides it to the user.

[0687] Enter: Perfect souvenir item

[0688] Output: Reviews

[0689] Specific operation: The server collects reviews and ratings from past buyers and selects the data to provide to the user.

[0690] Step 9:

[0691] The server generates a reminder based on the anniversary information and notifies the user.

[0692] Input: User's anniversary information

[0693] Output: Reminder notification

[0694] Specific operation: The server generates reminders based on the user's anniversary information and sends notifications to the user at the specified time.

[0695] Step 10:

[0696] The server will prioritize recommendations of local specialties.

[0697] Input: Best souvenir items, local specialty information

[0698] Output: A list of recommended local specialties

[0699] Specific operation: The server prioritizes and recommends local specialties based on the user's input conditions and information on local specialties, and creates suggestions.

[0700] 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.

[0701] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0702] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0703] [Third embodiment]

[0704] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0705] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0706] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[0707] 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.

[0708] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0709] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0710] 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. 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.

[0711] 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.

[0712] 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 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.

[0713] 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.

[0714] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0715] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0716] This invention is a system that allows users to select the best souvenirs for their travels, and AI makes suggestions based on information such as budget, destination, and the recipient's preferences. This system is specifically implemented as follows.

[0717] First, the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. The terminal provides an interface to send this information to the server. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets."

[0718] The server uses an AI model to recommend the best souvenir based on the received user data. This AI model selects souvenir items that best fit the user's input criteria based on past data and trend information.

[0719] The server then selects a place to purchase the recommended souvenir based on the location information. Specifically, it searches for the nearest store that offers the recommended souvenir based on the user's current location information and provides the user with the location information of that store.

[0720] The server also provides the option of souvenirs that can be purchased online, allowing users to purchase souvenirs over the Internet even if they do not have time to purchase them locally.

[0721] Furthermore, the server collects and provides user-review information, which is information about the evaluations and experiences of past purchasers, to help users make purchasing decisions.

[0722] The server also generates reminders based on the user's anniversary information and notifies the user, allowing the user to select the perfect souvenir for a specific anniversary or event.

[0723] Finally, the server includes a means for preferentially recommending local specialties. By preferentially recommending local specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Tokyo," the server can recommend specialties unique to Tokyo, thereby contributing to the spread of local culture and specialties.

[0724] For example, if a user inputs "Kyoto" as their travel destination, a budget of "5,000 yen," and "sake" as their partner's preference, the system will suggest the best sake based on past data and trends. It will then suggest the nearest store to the user's current location or provide a link to an online shop. It will also display reviews from past users and set reminders related to upcoming anniversaries. It also contributes to promoting local specialties by prioritizing recommendations of sake that is particularly famous in Kyoto.

[0725] In this way, the system of this invention uses AI to make appropriate suggestions based on the user's budget and preferences, eliminating the hassle of choosing souvenirs and improving the travel experience. In addition, by recommending local specialties, it can contribute to revitalizing local economies.

[0726] The processing flow will be explained below.

[0727] Step 1:

[0728] The terminal provides the user with an interface to input budget, destination, and partner preferences. The user enters the information in the appropriate fields and clicks the submit button.

[0729] Step 2:

[0730] The terminal sends the information entered by the user, such as budget, travel destination, and partner preferences, to the server, which is then ready to receive the user's request.

[0731] Step 3:

[0732] The server uses an AI model to suggest the best souvenirs based on the received user data. The AI ​​model analyzes past data, trends, and the purchasing history of other users to generate a list of suggested souvenirs.

[0733] Step 4:

[0734] The server searches for a place to purchase each souvenir based on the created souvenir list, finds the nearest store based on the user's current location, and acquires its location information.

[0735] Step 5:

[0736] The server retrieves online shopping links for each item to provide online purchasing options for the suggested souvenirs, and if available, provides the link to the user.

[0737] Step 6:

[0738] The server collects word-of-mouth information about the proposed souvenirs, including reviews and ratings left by past buyers, and gathers data to provide useful information to users.

[0739] Step 7:

[0740] The server generates reminders based on the user's anniversary information, helping them select the appropriate souvenir for a specific anniversary or event.

[0741] Step 8:

[0742] The server prioritizes and recommends regional specialties from among the suggested souvenirs. Based on data related to regional specialties, it recommends local products to help revitalize the local economy.

[0743] Step 9:

[0744] The server then sends all the results back to the device, including a list of the best souvenirs, where to buy, online options, reviews, reminders, and preferred recommendations for local specialties.

[0745] Step 10:

[0746] The terminal displays the information received from the server to the user, who then selects from the list of suitable souvenirs displayed on the terminal screen and obtains the desired product using the provided purchasing locations or online options.

[0747] Example 1

[0748] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0749] When choosing souvenirs, users currently spend a lot of time and effort selecting the best one from a wide range of options. Furthermore, there are a lack of effective ways to purchase local specialties and to refer to word-of-mouth information. This makes it difficult for users to choose a souvenir that satisfies them. Furthermore, there is no system that prioritizes and recommends local specialties, which is a problem that does not contribute to the development of local economies.

[0750] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0751] In this invention, the server includes: means for collecting information on a user's budget, travel destination, and other party preferences; means for running a generative AI model to suggest optimal souvenirs to the user based on the collected information; means for selecting a purchase location for the suggested souvenir based on location information; means for providing online purchase options for the suggested souvenir; means for collecting and providing user reviews about the suggested souvenir; means for generating reminders based on anniversary information and notifying the user; means for preferentially recommending regional specialties from among the suggested souvenirs; means for selecting and providing information about the optimal purchase location based on the user's current location information; means for providing links to online purchases of the suggested souvenirs if they are available; and means for selecting souvenirs based on past trend information using the generative AI model. This allows users to easily select and purchase optimal souvenirs and refer to reviews, and further contributes to the development of local economies by recommending regional specialties. A "user" refers to an individual who uses a terminal to input information such as a travel destination, budget, and other party preferences.

[0752] A "terminal" is a device through which a user inputs information such as travel destination, budget, and the other person's preferences, and includes smartphones, PCs, tablets, etc.

[0753] "Server" refers to a central computer system that processes information received from users and suggests the most suitable souvenirs.

[0754] "Budget" refers to the range of amounts set by the user for purchasing souvenirs.

[0755] "Travel destination" indicates a place where the user is traveling and includes geographic information about the place.

[0756] "Recipient's preferences" is information input by the user, and includes elements related to the recipient's tastes and preferences.

[0757] A "generative AI model" is an artificial intelligence model used to suggest the best souvenirs based on information entered by the user.

[0758] "Online Purchase Option" refers to the means provided for users to purchase suggested souvenirs over the Internet.

[0759] "Word-of-mouth information" refers to information including ratings and reviews provided by users who have previously purchased a product.

[0760] "Reminder" refers to an alert or message provided to notify a user of a particular anniversary or event.

[0761] "Regional specialty products" refer to products that are produced in a particular region and are characteristic of that region.

[0762] "Location information" refers to information including geographical data indicating a user's current location or a specific point.

[0763] "Purchase location" refers to the physical store or online shop where the suggested souvenir can be purchased.

[0764] "Past trend information" refers to information based on market trends and data on popular products.

[0765] This invention relates to a system for selecting the perfect souvenir for a travel destination. Users use a terminal to input information such as their travel destination, budget, and the recipient's preferences. Based on the information received, a server suggests the perfect souvenir and provides information such as where to buy it, online purchasing options, and reviews. The system also provides reminders based on anniversary information and recommends local specialties.

[0766] First, the user uses a device (such as a smartphone or PC) to input information such as the travel destination, budget, and the recipient's preferences. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets." The necessary information is then sent from the device to the server.

[0767] Based on the received user data, the server uses a generative AI model, a TensorFlow neural network model implemented in Python, to suggest the best souvenir. This generative AI model selects the souvenir item that best suits the user's input criteria based on past data and trend information. For example, if a user inputs a prompt such as "Travel destination: Tokyo, Budget: 3,000 yen, Favorites: Japanese sweets," the model will select Japanese sweets for Tokyo based on past trend information.

[0768] Next, the server selects the recommended souvenir purchasing location based on the location information. Specifically, it uses a location information API to obtain the user's current location and searches the PostgreSQL database for related stores within a specific range based on those coordinates. As a result, information on the nearest store is provided to the user. For example, if the user is near Tokyo Station, information on nearby Japanese confectionery stores is provided.

[0769] The server also provides souvenir options that can be purchased online. It uses the Amazon API and Rakuten API to check whether the suggested souvenirs are available online, and if so, generates and provides a link. This allows users to purchase souvenirs over the Internet even if they don't have time to buy them locally.

[0770] The server also collects user reviews and provides them to users. Specifically, it uses Python's BeautifulSoup to scrape relevant user reviews from the web, formatting them, and sending them to users for viewing. For example, it displays ratings and reviews from past buyers of the suggested Japanese sweets.

[0771] The server also generates reminders based on the anniversary information and notifies the user. It references the anniversary database and uses Firebase Cloud Messaging to trigger reminder notifications for specific dates. For example, when a user's wedding anniversary is approaching, a notification is sent with a suggestion for the perfect souvenir.

[0772] In addition, the server prioritizes recommendations of local specialties. By referencing a database of local specialties, it selects and recommends specialties that correspond to the user's travel destination (for example, Japanese sweets from Tokyo), which contributes to the development of the local economy.

[0773] An example of a prompt is as follows:

[0774] "Destination: Tokyo, Budget: 3000 yen, Favorites: Japanese sweets"

[0775] "Travel destination: Kyoto, Budget: 5,000 yen, Favorites: Sake"

[0776] In this way, the system of this invention uses AI to make appropriate suggestions based on the user's budget and preferences, eliminating the hassle of choosing souvenirs and improving the travel experience. In addition, by recommending local specialties, it also contributes to revitalizing the local economy.

[0777] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0778] Step 1: Enter your information

[0779] The user uses a device to input information such as travel destination, budget, and the other person's preferences. Specifically, the user enters information such as "Travel destination: Kyoto, Budget: 5,000 yen, Other person's preference: Japanese sake" into a form displayed on the screen of their smartphone or PC, and clicks the send button. This causes the input information to be displayed on the device screen, and the device then sends this information to the server.

[0780] Step 2: Send data from the device to the server

[0781] The terminal sends the information entered by the user to the server. Specifically, the terminal generates an HTTP request and sends the input information to the server in JSON format. This request includes the travel destination, budget, and the other person's preferences. The input is the information "Travel destination: Kyoto, Budget: 5,000 yen, Other person's preference: Sake," and the output is the information received on the server side.

[0782] Step 3: Server selects the gift

[0783] The server uses a generative AI model to select the optimal souvenir based on the received user data. Specifically, the server calls a TensorFlow neural network model implemented in Python and inputs the received information as a prompt. The generative AI model uses an internal database and past trend information to select souvenir items that fit the input criteria. The input is information such as "Travel destination: Kyoto, Budget: 5,000 yen, Recipient's preference: Sake," and the output is a recommended sake item.

[0784] Step 4: Choose a place to buy

[0785] The server selects the recommended souvenir purchasing location based on location information. Specifically, the server obtains the user's current location using a location information API and searches the PostgreSQL database for nearby stores based on those coordinates. The server extracts information about related stores within a specific range and selects the nearest store. The input is the user's current location information, and the output is information about the nearest store where the souvenir can be purchased.

[0786] Step 5: Offer online purchasing options

[0787] The server also provides souvenir options that can be purchased online. Specifically, the server uses the Amazon API or Rakuten API to check whether the recommended souvenirs are available for purchase online. If so, it generates and provides a corresponding link. The input is the information about the recommended souvenir item, and the output is the link to the corresponding online shop.

[0788] Step 6: Collect and provide reviews

[0789] The server collects reviews about recommended souvenirs and provides them to users. Specifically, the server uses Python's BeautifulSoup to scrape relevant reviews from the web and format them in a user-viewable format. The input is the recommended souvenir item information, and the output is the reviews about that item.

[0790] Step 7: Set reminders and notifications

[0791] The server generates a reminder based on the anniversary information and notifies the user. Specifically, the server references the anniversary database and uses Firebase Cloud Messaging to send a reminder notification for a specific date. The input is the user's anniversary information, and the output is the reminder notification.

[0792] Step 8: Recommend local specialties

[0793] The server prioritizes regional specialty products from the recommended souvenirs. Specifically, the server references a regional specialty product database and prioritizes the specialty products that correspond to the user's travel destination. The input is the travel destination and specialty product data, and the output is the suggested regional specialty products.

[0794] (Application example 1)

[0795] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0796] Conventional systems make it difficult for users to select the perfect souvenir when visiting a particular location, making it difficult to improve the quality of their travel experience. Furthermore, virtual shopping experiences using virtual reality devices were not readily available, preventing users from enjoying a detailed remote shopping experience. Furthermore, there were insufficient means to effectively recommend local specialties and contribute to the development of the local economy.

[0797] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0798] In this invention, the server includes: means for collecting information on a user's budget, travel destination, and the recipient's preferences; means for running an artificial intelligence model to suggest optimal souvenirs to the user based on the collected information; means for selecting a place to purchase the suggested souvenirs based on location information; means for providing online purchasing options for the suggested souvenirs; means for collecting word-of-mouth information about the suggested souvenirs and providing it to the user; means for generating reminders based on anniversary information and notifying the user; means for preferentially recommending regional specialties from among the suggested souvenirs; and means for linking with a virtual reality device that allows the user to explore virtual stores and confirm the souvenirs they have selected. This allows users to enjoy a sophisticated shopping experience using virtual reality from their travel destination or at home, eliminating the need to select the optimal souvenir and contributing to the spread of regional specialties and the development of the local economy.

[0799] "User's budget" is the upper limit of the amount that a user sets for the products that he or she wishes to purchase.

[0800] "Travel destination" refers to a place or city that the user plans to visit.

[0801] "Preferences of the recipient" refers to the specific tastes and hobbies of the recipient to whom the user is giving a souvenir.

[0802] "Means for collecting information" refers to a method or device for obtaining the necessary information from the user.

[0803] An "artificial intelligence model" is an algorithm or system that learns from past data and trend information and makes optimal suggestions.

[0804] "Purchase location" refers to the geographic location or store where the user can actually purchase the recommended souvenir.

[0805] "Location Information" means data regarding a user's current geographic location.

[0806] An "online purchase option" is a choice that allows a user to purchase products over the Internet.

[0807] "Word-of-mouth information" is information about ratings and comments made by past users about products.

[0808] A "reminder" is a function or system that notifies users of specific dates, times, or anniversaries.

[0809] "Regional specialties" are products or foods that are produced in a particular region and are representative of that region.

[0810] A "virtual reality device" is a device that allows users to immerse themselves in a virtual space and experience it, and mainly includes head-mounted displays and VR goggles.

[0811] This invention provides a system that allows users to select the best souvenirs for their travels, with AI making suggestions based on information such as budget, destination, and the recipient's preferences, allowing users to efficiently select souvenirs.

[0812] First, the user uses a device to input information such as the travel destination, budget, and the recipient's preferences. The device provides an interface that sends this information to the server. For example, a user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets." This information is then sent to the server via a web browser or a dedicated application.

[0813] The server uses an artificial intelligence model to recommend the best souvenir based on the received user data. This artificial intelligence model is built using frameworks such as TensorFlow and PyTorch. The model learns from past data and trend information to select the souvenir item that best suits the user's input criteria. For example, "Japanese sweets from Tokyo" may be recommended.

[0814] Next, the server selects the place to purchase the recommended souvenir based on the location information. Specifically, it obtains the user's current location information using Google Maps API or similar, and searches for the nearest store that offers the recommended souvenir. The location information of that store is then provided to the user.

[0815] The server also provides the option of souvenirs available for purchase online, allowing users to purchase souvenirs over the Internet even if they don't have time to do so locally. Users can click on the provided link to access the online shop and complete the purchase.

[0816] Furthermore, the server collects and provides user-review information, which includes information on the evaluations and experiences of past purchasers. This information helps users confirm the reliability of the recommended souvenirs and assists them in making a purchasing decision.

[0817] The server also generates reminders based on the user's anniversary information and notifies the user. This function is often implemented using the Google Calendar API, and helps users choose the perfect souvenir for a particular anniversary or event.

[0818] Finally, the server includes a means for preferentially recommending local specialties. By preferentially recommending local specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Tokyo," the server can recommend specialties unique to Tokyo, thereby contributing to the spread of local culture and specialties.

[0819] Furthermore, this invention can be applied to virtual stores. By using a virtual reality device such as a head-mounted display or VR goggles, users can visit stores in a virtual space and check recommended souvenirs. Users can operate an avatar to explore the virtual store and experience the realistic shopping experience of the selected souvenir.

[0820] As a concrete example, consider the case where a user enters "Kyoto" as the travel destination, a budget of "5,000 yen," and "sake" as the recipient's preference. Based on this information, the server will recommend the most suitable sake based on past data and trend information. Furthermore, based on the user's current location, the server will provide the nearest store where the sake can be purchased and also provide a link to the online shop. Reviews will also be displayed, and a reminder related to the next anniversary will be set. Recommendations will also be prioritized for regional specialties, such as sake that is particularly famous in Kyoto.

[0821] Example prompt sentence:

[0822] Travel destination: Kyoto

[0823] Budget: 5,000 yen

[0824] Partner's preference: Sake

[0825] Current location: Tokyo

[0826] In this way, the system of this invention improves the travel experience while reducing the effort required for souvenir selection by making appropriate suggestions based on the user's budget and preferences using AI. In addition, by recommending local specialties, it can contribute to revitalizing the local economy.

[0827] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0828] Step 1:

[0829] The user uses a device to input information such as travel destination, budget, and the other person's preferences. The user provides information through an input form on the device, such as "Travel destination: Tokyo, budget: 3,000 yen, other person's preferences: Japanese sweets." This information is structured in JSON format or similar and sent to the server.

[0830] Step 2:

[0831] The server analyzes the information received from the user. To analyze the information, the server accesses a database and searches for past data and trend information. This process uses SQL queries and other methods to extract information based on the input travel destination, budget, and preferences. As a result of the analysis, a list of multiple potential souvenir items is generated.

[0832] Step 3:

[0833] The server runs an artificial intelligence model (using, for example, TensorFlow or PyTorch) based on the list of candidate items. The model learns from past user data and trend information and selects the souvenir item that best suits the input criteria. This process identifies recommended items such as "Japanese sweets from Tokyo."

[0834] Step 4:

[0835] The server selects the place to purchase the recommended souvenir items. It uses the Google Maps API to obtain the user's current location and search for the nearest store. The store's location is selected by calculating the distance between the user's current location and the destination based on the data obtained from Google Maps.

[0836] Step 5:

[0837] The server provides online purchasing options and generates links to online shops where the suggested souvenir items can be purchased in case the user is unable to purchase them locally. This is done by using the API of each online shop to search for the product ID and obtain the link to its purchase page.

[0838] Step 6:

[0839] The server collects reviews of recommended souvenir items and provides them to users. It retrieves ratings and comments from past users from a database such as MongoDB and displays them along with the analysis results. This allows users to confirm the reliability of the products.

[0840] Step 7:

[0841] The server generates reminders based on the anniversary information and notifies the user. It uses the Google Calendar API to retrieve the user's anniversary data and sets notifications when the date approaches. Notifications are sent as emails or in-app notifications.

[0842] Step 8:

[0843] The server prioritizes recommendations of local specialty products. Based on the analysis results, it extracts specialty product data related to the user's travel destination and adds them to the recommendation list with priority. This contributes to the spread of specialty products and the development of the local economy.

[0844] Step 9:

[0845] Users use a virtual reality device to explore virtual stores. They wear a head-mounted display and check recommended souvenir items in the virtual space. Users can control an avatar to visit stores and check detailed souvenir information and reviews in real time.

[0846] In this way, a system is constructed that realizes complex processing through the roles of the server, terminal, and user, and supports efficient and effective souvenir selection.

[0847] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0848] This invention is a system that allows users to select the best souvenirs for their travels. AI makes suggestions based on information such as budget, destination, and the recipient's preferences. It also has a function to adjust the suggestions by combining it with an emotion engine that recognizes the user's emotions. This system is specifically implemented as follows.

[0849] First, the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. The terminal provides an interface to send this information to the server. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets."

[0850] The server uses an AI model to suggest the best souvenir based on the received user data. This AI model selects the souvenir item that best suits the user's input criteria based on past data and trend information.

[0851] Furthermore, the server uses an emotion engine to recognize the user's emotions. It analyzes the user's facial expressions and tone of voice through emotion recognition devices (such as cameras and microphones) to understand their current emotional state. For example, if the user has a happy face, the server recognizes their emotional state as "happy."

[0852] The server adjusts the suggestions based on the user's emotional state as recognized by the emotion engine. For example, if the user is in a "happy" emotional state, the server will recommend souvenirs that will further enhance the user's joyful mood. In this way, suggestions that are tailored to the user's emotions will help the user select souvenirs that will provide greater satisfaction.

[0853] The server also monitors the user's emotional state in real time and updates the suggestions as needed. For example, if the user suddenly changes their mood or is not interested in a suggested souvenir, it can instantly suggest other options.

[0854] Furthermore, the server learns the user's past emotional data and reflects it in future souvenir suggestions, enabling more accurate suggestions based on the user's past emotional state and the type of souvenir they chose.

[0855] The server then selects a place to purchase the recommended souvenir based on the location information. Specifically, it searches for the nearest store that offers the recommended souvenir based on the user's current location information and provides the user with the location information of that store.

[0856] The server also provides the option of souvenirs that can be purchased online, allowing users to purchase souvenirs over the Internet even if they do not have time to purchase them locally.

[0857] Furthermore, the server collects and provides user-review information, which is information about the evaluations and experiences of past purchasers, to help users make purchasing decisions.

[0858] The server also generates reminders based on the user's anniversary information and notifies the user, allowing the user to select the perfect souvenir for a specific anniversary or event.

[0859] Finally, the server includes a means for preferentially recommending local specialties. By preferentially recommending local specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Tokyo," the server can recommend specialties unique to Tokyo, thereby contributing to the spread of local culture and specialties.

[0860] For example, if a user inputs "Kyoto" as their travel destination, a budget of "5,000 yen," and the other person's preference of "sake," and the emotion engine recognizes the emotion of "expectation," the system will suggest the most suitable sake based on past data and trends. The system will then provide the nearest store to the user's current location or a link to an online shop. It will also display reviews from past users and set reminders related to upcoming anniversaries. By prioritizing recommendations of sake that is particularly famous in Kyoto, the system also contributes to promoting local specialties.

[0861] In this way, the system of this invention not only uses AI to make appropriate suggestions based on the user's budget and preferences, but also uses an emotion engine to make suggestions that match the user's emotions, helping them choose souvenirs with greater satisfaction. Furthermore, by recommending local specialties, it can also contribute to revitalizing local economies.

[0862] The processing flow will be explained below.

[0863] Step 1:

[0864] The terminal provides the user with an interface to input budget, destination, and partner preferences. The user enters the information in the appropriate fields and clicks the submit button.

[0865] Step 2:

[0866] The terminal sends the information entered by the user, such as budget, travel destination, and partner preferences, to the server, which is then ready to receive the user's request.

[0867] Step 3:

[0868] The server uses an artificial intelligence model to suggest the best souvenir based on the received user data. This AI model analyzes past data and trend information to select the souvenir item that best suits the user's requirements.

[0869] Step 4:

[0870] The server uses an emotion engine to recognize the user's emotions. It analyzes the user's facial expressions and voice through the camera and microphone connected to the device to determine their current emotional state. For example, if the user is smiling, it will recognize that they are "happy."

[0871] Step 5:

[0872] The server adjusts the suggestions based on the user's emotional state as recognized by the emotion engine. For example, if the user is in a "happy" emotional state, the server will recommend souvenirs that will further enhance the user's joyful mood.

[0873] Step 6:

[0874] The server selects the place to purchase the suggested souvenir based on the user's current location information. Based on the user's current location information, it searches for the nearest store that offers the recommended souvenir and obtains the store's location information.

[0875] Step 7:

[0876] The server retrieves online shopping links for each item to provide online purchasing options for the suggested souvenirs, and if available, provides the link to the user.

[0877] Step 8:

[0878] The server collects word-of-mouth information about the proposed souvenirs, pulls out reviews and ratings left by past buyers from a database, and provides them to the user.

[0879] Step 9:

[0880] The server generates reminders based on the user's anniversary information, helping them select the appropriate souvenir for a specific anniversary or event.

[0881] Step 10:

[0882] The server prioritizes regional specialty products from among the recommended souvenirs. Based on data related to regional specialty products, the server prioritizes local products to support the revitalization of the local economy.

[0883] Step 11:

[0884] The server then sends all the results back to the device, including a list of the best souvenirs, where to buy, online options, reviews, reminders, and preferred recommendations for local specialties.

[0885] Step 12:

[0886] The terminal displays the information received from the server to the user, who then selects from the list of suitable souvenirs displayed on the terminal screen and obtains the desired product using the provided purchasing locations or online options.

[0887] As a specific example, if a user inputs "Kyoto" as their travel destination, a budget of "5,000 yen," and the recipient's preference of "sake," and the emotion engine recognizes the emotion of "expectation," the server will use an AI model to suggest the most suitable sake. The server will then provide the store closest to the user's current location, along with reviews. It will also provide an online purchase link. Furthermore, a reminder related to the next anniversary will be generated, with priority given to recommendations of local sake, a Kyoto specialty. Based on this information, users can select and purchase the perfect souvenir.

[0888] Example 2

[0889] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0890] Traditionally, choosing the right souvenirs for a trip has been challenging, especially when it comes to making optimal choices based on the user's budget and the recipient's preferences. Furthermore, there has been a lack of methods to improve satisfaction by adjusting recommendations based on the user's emotional state. Furthermore, there have been insufficient efforts to revitalize local economies through preferential recommendations of regional specialties. Therefore, there is a need for a system that collects user information, considers the user's emotional state, makes optimal recommendations, and prioritizes regional specialties.

[0891] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0892] In this invention, the server includes means for collecting information on a user's budget, travel destination, and partner preferences, means for executing an artificial intelligence model to suggest optimal products to the user based on the collected information, means for executing an emotion recognition engine to recognize the user's emotional state regarding the suggested products, means for adjusting the content of the suggestions based on the user's emotional state, means for selecting and providing a purchase location for the suggested products based on location information, means for providing an online purchase option for the suggested products, means for collecting and providing evaluation information on the suggested products to the user, means for generating a reminder based on anniversary information and notifying the user, and means for preferentially recommending regional specialties from among the suggested products. This makes it possible to provide highly satisfying suggestions that are in line with the user's emotional state and to revitalize local economies through preferential recommendations of regional specialties.

[0893] "User" refers to a person who uses the system to select souvenirs at a travel destination.

[0894] "Budget" refers to the upper limit of the amount of money that a user sets for purchasing souvenirs at a travel destination.

[0895] "Travel destination" refers to a place that a user visits during a trip.

[0896] "The recipient's tastes" refers to the preferences and interests of the person receiving the souvenir.

[0897] "Means for collecting information" refers to methods and devices for obtaining data about a user's budget, travel destinations, and partner preferences.

[0898] An "artificial intelligence model" refers to an algorithm or program that selects the most suitable product based on collected information.

[0899] An "emotion recognition engine" refers to a system that analyzes and recognizes a user's emotional state from facial expressions, tone of voice, etc.

[0900] The "means for adjusting the content of the proposal" refers to a method or device for changing the optimal product proposal based on the emotional state of the user obtained by the emotion recognition engine.

[0901] "Location information" refers to geographical data used to identify a user's current location.

[0902] "Means for selecting a purchasing location" refers to a method or device for identifying the optimal product purchasing location based on location information.

[0903] "Online Purchase Option" refers to an option for a User to purchase Products over the Internet.

[0904] "Evaluation Information" refers to feedback and reviews of products provided by past users.

[0905] "Reminder" refers to a function or message that notifies the user on special occasions or specific events.

[0906] "Regional specialty products" refer to products that are produced in a specific region and are representative of that region.

[0907] The present invention is a system that allows users to select the best souvenir for their travel destination, and is implemented through the following process. The process begins when the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. The terminal is equipped with an interface for collecting this information and sending it to a server. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to select a souvenir for someone who likes Japanese sweets."

[0908] The device sends this information to a server via the internet. The server then uses the information it receives to run an artificial intelligence (AI) model, which then suggests the best souvenir. This AI model uses past data and trend information to select the souvenir item that best suits the user's input criteria. For example, it suggests the most highly rated Japanese sweets available in Tokyo.

[0909] Furthermore, the server is equipped with an emotion recognition engine that analyzes the user's emotions through emotion recognition devices (cameras and microphones). The emotion recognition engine analyzes the user's facial expressions and tone of voice to determine their current emotional state. For example, if the user has a happy face, the emotional state is recognized as "happy."

[0910] The server has the ability to adjust the content of suggestions based on the user's emotional state as recognized by the emotion recognition engine. For example, if the user is in a "happy" emotional state, the server will recommend items that will further increase the user's joy. This can increase user satisfaction.

[0911] Next, the server selects the place to purchase the recommended product based on the user's current location information. For example, the server uses GPS data to confirm that the user is currently in "Shinjuku," searches for stores selling the recommended Japanese sweets in the Shinjuku area, and provides the user with their location information.

[0912] The server can also provide online purchasing options, allowing users to purchase souvenirs over the Internet if they don't have time to shop locally. Additionally, the server can provide reviews collected from past users, allowing users to see other people's ratings and feedback.

[0913] The server also includes a function to generate reminders based on anniversary information and notify users. For example, it can notify users that their wedding anniversary is approaching and suggest suitable souvenirs.

[0914] Finally, the server has a means to recommend regional specialties to the user. For example, if a user is looking for souvenirs in "Tokyo," the server will recommend regional specialties unique to Tokyo, such as "Tokyo Banana" and "Kaminariokoshi."

[0915] As a concrete example, let's consider a scenario in which a user inputs "Kyoto" as the travel destination, a budget of "5,000 yen," and the other person's preference of "sake," and the emotion engine recognizes the emotion of "expectation." The system uses an AI model to suggest highly rated sake in Kyoto and provides information on the nearest store to purchase it from the user's current location. At the same time, the system also provides links to online shops, reviews from past users, and reminders related to the next anniversary, and prioritizes recommendations of famous sake, a Kyoto specialty.

[0916] An example of a specific prompt for a generative AI model is, "Please suggest a souvenir for someone who is traveling to Kyoto, has a budget of 5,000 yen, and likes sake. The user is currently in an emotional state of expectation."

[0917] In this way, AI makes appropriate suggestions based on the user's budget and preferences, and the emotion engine makes suggestions that match the user's emotions, helping them choose souvenirs that will leave them satisfied. Recommending local specialties also contributes to the development of local economies.

[0918] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0919] Step 1: The user uses the terminal to input information such as travel destination, budget, partner preferences, etc. The input information is sent to the server through the interface.

[0920] Input: "Travel destination (e.g. Tokyo)", "Budget (e.g. 3,000 yen)", "Partner's preferences (e.g. Japanese sweets)"

[0921] Output: Request data sent from the terminal to the server

[0922] Step 2: The server receives the information sent from the device and inputs it into an artificial intelligence (AI) model, which then selects the best souvenir based on past data and trend information.

[0923] Input: User's "travel destination", "budget", and "preferences" data

[0924] Data processing / calculation: The AI ​​model analyzes this data and uses historical databases and trend algorithms to extract the most suitable products.

[0925] Output: Data suggesting the best souvenirs (e.g., highly rated Japanese sweets available in Tokyo)

[0926] Step 3: The server uses an emotion recognition engine to collect the user's emotion data from the emotion recognition device (camera or microphone) and recognize the user's current emotional state.

[0927] Input: User's facial expressions and tone of voice obtained from emotion recognition device

[0928] Data processing / calculation: An emotion recognition engine analyzes this data and classifies the emotional state as "happy," for example.

[0929] Output: Data on the user's emotional state (e.g., "happy")

[0930] Step 4: The server adjusts the suggestions based on the emotional state data. Appropriate suggestions are made based on the emotional state.

[0931] Input: optimal souvenir suggestion data, user emotional state data

[0932] Data processing / calculation: Filtering and adjusting the suggestions to reselect the souvenir that best suits the user's emotional state.

[0933] Output: Tailored souvenir suggestion data (e.g. Japanese sweets in special packaging)

[0934] Step 5: The server selects the recommended product purchasing location based on the user's current location information and provides the specific location information of the store where the product was purchased.

[0935] Input: User's current location information (GPS data), tailored souvenir suggestion data

[0936] Data processing / calculation: Search for the nearest store to your current location and identify its location information.

[0937] Output: Location information of the nearest store (e.g., a list of stores in Shinjuku)

[0938] Step 6: The server also provides an online purchase option, allowing users to purchase souvenirs over the Internet.

[0939] Input: Adjusted souvenir suggestion data

[0940] Data processing / calculation: Generate an online shop link and provide it as a purchasing option.

[0941] Output: Online purchase option link (e.g. Japanese sweets online shop URL)

[0942] Step 7: The server collects evaluation information about the proposed souvenir and provides it to the user. It also displays reviews from past users.

[0943] Input: Adjusted souvenir suggestion data

[0944] Data processing / calculation: Obtain and organize relevant word-of-mouth information from the evaluation database.

[0945] Output: User reviews (e.g., "This Japanese sweet was really delicious!")

[0946] Step 8: The server generates a reminder based on the anniversary information and notifies the user.

[0947] Input: User's anniversary information, tailored souvenir suggestion data

[0948] Data Processing / Calculation: Schedule reminder notifications when an anniversary is approaching.

[0949] Output: Reminder notification (e.g. "Let's prepare a souvenir for our anniversary!")

[0950] Step 9: The server recommends regional specialties from the proposed products with priority.

[0951] Input: Adjusted souvenir suggestion data

[0952] Data processing / calculation: Refer to the regional specialty product database and prioritize recommendations of products unique to that region.

[0953] Output: Recommendation data for local specialties (e.g., "Tokyo Banana" and "Kaminariokoshi")

[0954] (Application example 2)

[0955] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0956] With conventional technology, it was difficult to provide optimal recommendations for souvenirs when choosing them at a travel destination, taking into account the user's personal preferences and emotional state. This resulted in users choosing inappropriate souvenirs, which reduced user satisfaction. Furthermore, recommendations of local specialties were weak, and the promotion of local economies was insufficient. It is necessary to solve these issues, provide more useful information to users, and contribute to the development of local economies.

[0957] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0958] In this invention, the server includes means for collecting information on the user's budget, travel destination, and partner's preferences, emotion recognition means for recognizing the user's emotions, means for executing an artificial intelligence model to suggest optimal souvenirs to the user based on the collected information and the emotional state obtained by the emotion recognition means, means for selecting a place to purchase the suggested souvenirs from location information, means for providing online purchase options for the suggested souvenirs, means for collecting word-of-mouth information on the suggested souvenirs and providing it to the user, means for generating reminders based on anniversary information and notifying the user, and means for preferentially recommending regional specialties from among the suggested souvenirs. This makes it possible to suggest optimal souvenirs tailored to the user's emotional state and also to preferentially recommend regional specialties.

[0959] A "user budget" is a monetary limit that a user is willing to spend on a particular product or service.

[0960] A "travel destination" is a geographic location or destination that a user plans to visit.

[0961] "The recipient's preferences" refer to the things or tastes that the person receiving the souvenir is particularly interested in.

[0962] "Means of collecting information" refers to the interface and functions for obtaining the necessary data from the user.

[0963] "Emotion recognition means" refers to devices or algorithms that evaluate and identify a user's emotional state, such as facial expressions or voice.

[0964] An "artificial intelligence model" is a computer program that uses specific algorithms and statistical models to analyze data and suggest the best souvenirs for users.

[0965] The "means for selecting a place to purchase" refers to a function for identifying the most suitable place to purchase based on the user's current location information, etc.

[0966] "Means for providing online purchase options" refers to a function that provides links and information that allow users to purchase souvenirs over the Internet.

[0967] "Means for collecting and providing word-of-mouth information" refers to a function for collecting ratings and reviews from past purchasers and displaying that information to users.

[0968] "Means for generating and notifying reminders based on anniversary information" refers to a function that creates reminders for the user's anniversaries or specific events and notifies the user.

[0969] The "means for preferentially recommending local specialty products" is a function for preferentially recommending to the user specialty products produced in a specific region.

[0970] The present invention is a system for allowing users to select the best souvenirs at their travel destinations. The system includes the following components:

[0971] First, the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. For example, the user might input, "I'm traveling to Kyoto, my budget is 5,000 yen, and I want to choose a souvenir for someone who likes sake." The terminal provides an interface that sends the input information to the server.

[0972] Next, the server uses the received information to suggest the best souvenirs using an AI model. This AI model selects souvenir items that best fit the user's input criteria based on past data and trend information. Specifically, the AI ​​model analyzes the user's input criteria and suggests the best items from products specific to the travel destination.

[0973] Furthermore, the server uses emotion recognition means to recognize the user's emotional state. It analyzes the user's facial expressions and tone of voice through emotion recognition devices (such as cameras and microphones) to understand the user's current emotional state. For example, if the user has a happy face, the server recognizes the user's emotional state as "happy."

[0974] The server adjusts the suggestions based on the user's emotional state. For example, if the user is in a "happy" emotional state, it will recommend souvenirs that will further enhance the user's joyful mood. In this way, by making suggestions that are in line with the user's emotions, the server helps the user choose souvenirs that will give them greater satisfaction.

[0975] The server also searches for recommended souvenir purchasing locations based on the user's current location information. It provides the location information of the nearest store from the user's current location or a link to an online shop. This allows users to purchase souvenirs over the Internet even if they don't have time to buy them locally.

[0976] In addition, the server collects and provides user-review information, including information on the evaluations and experiences of past purchasers, to assist users in making purchasing decisions.

[0977] The server generates reminders based on the user's anniversary information and notifies the user, allowing the user to select the perfect souvenir for a specific anniversary or event.

[0978] Finally, the server includes a means for preferentially recommending regional specialties. By preferentially recommending regional specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Kyoto," the server can recommend Kyoto-specific specialties, thereby contributing to the spread of local culture and specialties.

[0979] Examples:

[0980] If the user inputs "Kyoto" as the travel destination, a budget of "5,000 yen," and the other person's preference of "sake," and the emotion of "expectation" is recognized from the camera image, the system will make specific suggestions such as the following.

[0981] Recommended souvenir: Kyoto's famous local sake

[0982] Where to buy: Select local stores

[0983] Online option: Online shop link for the product

[0984] Example prompt sentence:

[0985] The user has selected "Kyoto" as their travel destination, their budget is "5000 yen", and their partner's preference is "sake". The user's emotional state is "expectation". Please suggest the best sake souvenir. Also provide where to buy it and online options.

[0986] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0987] Step 1:

[0988] The user uses the terminal to input information such as the travel destination, budget, and the partner's preferences.

[0989] Input: Travel destination (e.g. Kyoto), budget (5,000 yen), partner's preference (sake)

[0990] Output: User input data

[0991] Specific operation: The user enters the required information through the device interface, and the data is saved in the device.

[0992] Step 2:

[0993] The terminal transmits the user input data to the server.

[0994] Input: User-entered data

[0995] Output: User data sent to the server

[0996] Specific operation: The terminal transmits the collected user input data to a server via the Internet.

[0997] Step 3:

[0998] Based on the user data received by the server, a generative AI model is used to suggest the best souvenir.

[0999] Input: User data sent to the server

[1000] Output: Perfect souvenir item

[1001] Specific operation: The server runs an AI model based on the received data and selects the souvenir that best suits the user's requirements.

[1002] Step 4:

[1003] The server uses emotion recognition means to recognize the emotional state of the user.

[1004] Input: User facial or voice data

[1005] Output: Emotional state (e.g., "happy," "expected")

[1006] How it works: The server analyzes data obtained from the camera and microphone and uses emotion recognition models to identify the user's emotional state.

[1007] Step 5:

[1008] The server adjusts the souvenir suggestions based on the emotional state.

[1009] Input: Best souvenir item, user's emotional state

[1010] Output: Tailored souvenir suggestions

[1011] Specific operation: The server selects souvenirs that match the user's emotional state and updates the recommendations.

[1012] Step 6:

[1013] The server selects the place to purchase the suggested souvenir based on the location information.

[1014] Input: Best souvenir item, user's current location

[1015] Output: Location of nearest store

[1016] Specific operation: The server obtains the user's current location information and searches for the nearest store that offers the best souvenirs.

[1017] Step 7:

[1018] The server provides an online purchase option for the suggested souvenirs.

[1019] Enter: Perfect souvenir item

[1020] Output: Online store link

[1021] What it does: The server searches a database on the Internet and generates links to purchase the suggested souvenirs online.

[1022] Step 8:

[1023] The server collects word-of-mouth information about the proposed souvenirs and provides it to the user.

[1024] Enter: Perfect souvenir item

[1025] Output: Reviews

[1026] Specific operation: The server collects reviews and ratings from past buyers and selects the data to provide to the user.

[1027] Step 9:

[1028] The server generates a reminder based on the anniversary information and notifies the user.

[1029] Input: User's anniversary information

[1030] Output: Reminder notification

[1031] Specific operation: The server generates reminders based on the user's anniversary information and sends notifications to the user at the specified time.

[1032] Step 10:

[1033] The server will prioritize recommendations of local specialties.

[1034] Input: Best souvenir items, local specialty information

[1035] Output: A list of recommended local specialties

[1036] Specific operation: The server prioritizes and recommends local specialties based on the user's input conditions and information on local specialties, and creates suggestions.

[1037] 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.

[1038] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1039] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1040] [Fourth embodiment]

[1041] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1042] 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.

[1043] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[1044] 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.

[1045] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1046] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1047] 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. 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.

[1048] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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.

[1049] 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.

[1050] 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 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.

[1051] 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.

[1052] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1053] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1054] This invention is a system that allows users to select the best souvenirs for their travels, and AI makes suggestions based on information such as budget, destination, and the recipient's preferences. This system is specifically implemented as follows.

[1055] First, the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. The terminal provides an interface to send this information to the server. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets."

[1056] The server uses an AI model to recommend the best souvenir based on the received user data. This AI model selects souvenir items that best fit the user's input criteria based on past data and trend information.

[1057] The server then selects a place to purchase the recommended souvenir based on the location information. Specifically, it searches for the nearest store that offers the recommended souvenir based on the user's current location information and provides the user with the location information of that store.

[1058] The server also provides the option of souvenirs that can be purchased online, allowing users to purchase souvenirs over the Internet even if they do not have time to purchase them locally.

[1059] Furthermore, the server collects and provides user-review information, which is information about the evaluations and experiences of past purchasers, to help users make purchasing decisions.

[1060] The server also generates reminders based on the user's anniversary information and notifies the user, allowing the user to select the perfect souvenir for a specific anniversary or event.

[1061] Finally, the server includes a means for preferentially recommending local specialties. By preferentially recommending local specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Tokyo," the server can recommend specialties unique to Tokyo, thereby contributing to the spread of local culture and specialties.

[1062] For example, if a user inputs "Kyoto" as their travel destination, a budget of "5,000 yen," and "sake" as their partner's preference, the system will suggest the best sake based on past data and trends. It will then suggest the nearest store to the user's current location or provide a link to an online shop. It will also display reviews from past users and set reminders related to upcoming anniversaries. It also contributes to promoting local specialties by prioritizing recommendations of sake that is particularly famous in Kyoto.

[1063] In this way, the system of this invention uses AI to make appropriate suggestions based on the user's budget and preferences, eliminating the hassle of choosing souvenirs and improving the travel experience. In addition, by recommending local specialties, it can contribute to revitalizing local economies.

[1064] The processing flow will be explained below.

[1065] Step 1:

[1066] The terminal provides the user with an interface to input budget, destination, and partner preferences. The user enters the information in the appropriate fields and clicks the submit button.

[1067] Step 2:

[1068] The terminal sends the information entered by the user, such as budget, travel destination, and partner preferences, to the server, which is then ready to receive the user's request.

[1069] Step 3:

[1070] The server uses an AI model to suggest the best souvenirs based on the received user data. The AI ​​model analyzes past data, trends, and the purchasing history of other users to generate a list of suggested souvenirs.

[1071] Step 4:

[1072] The server searches for a place to purchase each souvenir based on the created souvenir list, finds the nearest store based on the user's current location, and acquires its location information.

[1073] Step 5:

[1074] The server retrieves online shopping links for each item to provide online purchasing options for the suggested souvenirs, and if available, provides the link to the user.

[1075] Step 6:

[1076] The server collects word-of-mouth information about the proposed souvenirs, including reviews and ratings left by past buyers, and gathers data to provide useful information to users.

[1077] Step 7:

[1078] The server generates reminders based on the user's anniversary information, helping them select the appropriate souvenir for a specific anniversary or event.

[1079] Step 8:

[1080] The server prioritizes and recommends regional specialties from among the suggested souvenirs. Based on data related to regional specialties, it recommends local products to help revitalize the local economy.

[1081] Step 9:

[1082] The server then sends all the results back to the device, including a list of the best souvenirs, where to buy, online options, reviews, reminders, and preferred recommendations for local specialties.

[1083] Step 10:

[1084] The terminal displays the information received from the server to the user, who then selects from the list of suitable souvenirs displayed on the terminal screen and obtains the desired product using the provided purchasing locations or online options.

[1085] Example 1

[1086] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1087] When choosing souvenirs, users currently spend a lot of time and effort selecting the best one from a wide range of options. Furthermore, there are a lack of effective ways to purchase local specialties and to refer to word-of-mouth information. This makes it difficult for users to choose a souvenir that satisfies them. Furthermore, there is no system that prioritizes and recommends local specialties, which is a problem that does not contribute to the development of local economies.

[1088] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1089] In this invention, the server includes: means for collecting information on a user's budget, travel destination, and other party preferences; means for running a generative AI model to suggest optimal souvenirs to the user based on the collected information; means for selecting a purchase location for the suggested souvenir based on location information; means for providing online purchase options for the suggested souvenir; means for collecting and providing user reviews about the suggested souvenir; means for generating reminders based on anniversary information and notifying the user; means for preferentially recommending regional specialties from among the suggested souvenirs; means for selecting and providing information about the optimal purchase location based on the user's current location information; means for providing links to online purchases of the suggested souvenirs if they are available; and means for selecting souvenirs based on past trend information using the generative AI model. This allows users to easily select and purchase optimal souvenirs and refer to reviews, and further contributes to the development of local economies by recommending regional specialties. A "user" refers to an individual who uses a terminal to input information such as a travel destination, budget, and other party preferences.

[1090] A "terminal" is a device through which a user inputs information such as travel destination, budget, and the other person's preferences, and includes smartphones, PCs, tablets, etc.

[1091] "Server" refers to a central computer system that processes information received from users and suggests the most suitable souvenirs.

[1092] "Budget" refers to the range of amounts set by the user for purchasing souvenirs.

[1093] "Travel destination" indicates a place where the user is traveling and includes geographic information about the place.

[1094] "Recipient's preferences" is information input by the user, and includes elements related to the recipient's tastes and preferences.

[1095] A "generative AI model" is an artificial intelligence model used to suggest the best souvenirs based on information entered by the user.

[1096] "Online Purchase Option" refers to the means provided for users to purchase suggested souvenirs over the Internet.

[1097] "Word-of-mouth information" refers to information including ratings and reviews provided by users who have previously purchased a product.

[1098] "Reminder" refers to an alert or message provided to notify a user of a particular anniversary or event.

[1099] "Regional specialty products" refer to products that are produced in a particular region and are characteristic of that region.

[1100] "Location information" refers to information including geographical data indicating a user's current location or a specific point.

[1101] "Purchase location" refers to the physical store or online shop where the suggested souvenir can be purchased.

[1102] "Past trend information" refers to information based on market trends and data on popular products.

[1103] This invention relates to a system for selecting the perfect souvenir for a travel destination. Users use a terminal to input information such as their travel destination, budget, and the recipient's preferences. Based on the information received, a server suggests the perfect souvenir and provides information such as where to buy it, online purchasing options, and reviews. The system also provides reminders based on anniversary information and recommends local specialties.

[1104] First, the user uses a device (such as a smartphone or PC) to input information such as the travel destination, budget, and the recipient's preferences. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets." The necessary information is then sent from the device to the server.

[1105] Based on the received user data, the server uses a generative AI model, a TensorFlow neural network model implemented in Python, to suggest the best souvenir. This generative AI model selects the souvenir item that best suits the user's input criteria based on past data and trend information. For example, if a user inputs a prompt such as "Travel destination: Tokyo, Budget: 3,000 yen, Favorites: Japanese sweets," the model will select Japanese sweets for Tokyo based on past trend information.

[1106] Next, the server selects the recommended souvenir purchasing location based on the location information. Specifically, it uses a location information API to obtain the user's current location and searches the PostgreSQL database for related stores within a specific range based on those coordinates. As a result, information on the nearest store is provided to the user. For example, if the user is near Tokyo Station, information on nearby Japanese confectionery stores is provided.

[1107] The server also provides souvenir options that can be purchased online. It uses the Amazon API and Rakuten API to check whether the suggested souvenirs are available online, and if so, generates and provides a link. This allows users to purchase souvenirs over the Internet even if they don't have time to buy them locally.

[1108] The server also collects user reviews and provides them to users. Specifically, it uses Python's BeautifulSoup to scrape relevant user reviews from the web, formatting them, and sending them to users for viewing. For example, it displays ratings and reviews from past buyers of the suggested Japanese sweets.

[1109] The server also generates reminders based on the anniversary information and notifies the user. It references the anniversary database and uses Firebase Cloud Messaging to trigger reminder notifications for specific dates. For example, when a user's wedding anniversary is approaching, a notification is sent with a suggestion for the perfect souvenir.

[1110] In addition, the server prioritizes recommendations of local specialties. By referencing a database of local specialties, it selects and recommends specialties that correspond to the user's travel destination (for example, Japanese sweets from Tokyo), which contributes to the development of the local economy.

[1111] An example of a prompt is as follows:

[1112] "Destination: Tokyo, Budget: 3000 yen, Favorites: Japanese sweets"

[1113] "Travel destination: Kyoto, Budget: 5,000 yen, Favorites: Sake"

[1114] In this way, the system of this invention uses AI to make appropriate suggestions based on the user's budget and preferences, eliminating the hassle of choosing souvenirs and improving the travel experience. In addition, by recommending local specialties, it also contributes to revitalizing the local economy.

[1115] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1116] Step 1: Enter your information

[1117] The user uses a device to input information such as travel destination, budget, and the other person's preferences. Specifically, the user enters information such as "Travel destination: Kyoto, Budget: 5,000 yen, Other person's preference: Japanese sake" into a form displayed on the screen of their smartphone or PC, and clicks the send button. This causes the input information to be displayed on the device screen, and the device then sends this information to the server.

[1118] Step 2: Send data from the device to the server

[1119] The terminal sends the information entered by the user to the server. Specifically, the terminal generates an HTTP request and sends the input information to the server in JSON format. This request includes the travel destination, budget, and the other person's preferences. The input is the information "Travel destination: Kyoto, Budget: 5,000 yen, Other person's preference: Sake," and the output is the information received on the server side.

[1120] Step 3: Server selects the gift

[1121] The server uses a generative AI model to select the optimal souvenir based on the received user data. Specifically, the server calls a TensorFlow neural network model implemented in Python and inputs the received information as a prompt. The generative AI model uses an internal database and past trend information to select souvenir items that fit the input criteria. The input is information such as "Travel destination: Kyoto, Budget: 5,000 yen, Recipient's preference: Sake," and the output is a recommended sake item.

[1122] Step 4: Choose a place to buy

[1123] The server selects the recommended souvenir purchasing location based on location information. Specifically, the server obtains the user's current location using a location information API and searches the PostgreSQL database for nearby stores based on those coordinates. The server extracts information about related stores within a specific range and selects the nearest store. The input is the user's current location information, and the output is information about the nearest store where the souvenir can be purchased.

[1124] Step 5: Offer online purchasing options

[1125] The server also provides souvenir options that can be purchased online. Specifically, the server uses the Amazon API or Rakuten API to check whether the recommended souvenirs are available for purchase online. If so, it generates and provides a corresponding link. The input is the information about the recommended souvenir item, and the output is the link to the corresponding online shop.

[1126] Step 6: Collect and provide reviews

[1127] The server collects reviews about recommended souvenirs and provides them to users. Specifically, the server uses Python's BeautifulSoup to scrape relevant reviews from the web and format them in a user-viewable format. The input is the recommended souvenir item information, and the output is the reviews about that item.

[1128] Step 7: Set reminders and notifications

[1129] The server generates a reminder based on the anniversary information and notifies the user. Specifically, the server references the anniversary database and uses Firebase Cloud Messaging to send a reminder notification for a specific date. The input is the user's anniversary information, and the output is the reminder notification.

[1130] Step 8: Recommend local specialties

[1131] The server prioritizes regional specialty products from the recommended souvenirs. Specifically, the server references a regional specialty product database and prioritizes the specialty products that correspond to the user's travel destination. The input is the travel destination and specialty product data, and the output is the suggested regional specialty products.

[1132] (Application example 1)

[1133] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1134] Conventional systems make it difficult for users to select the perfect souvenir when visiting a particular location, making it difficult to improve the quality of their travel experience. Furthermore, virtual shopping experiences using virtual reality devices were not readily available, preventing users from enjoying a detailed remote shopping experience. Furthermore, there were insufficient means to effectively recommend local specialties and contribute to the development of the local economy.

[1135] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1136] In this invention, the server includes: means for collecting information on a user's budget, travel destination, and the recipient's preferences; means for running an artificial intelligence model to suggest optimal souvenirs to the user based on the collected information; means for selecting a place to purchase the suggested souvenirs based on location information; means for providing online purchasing options for the suggested souvenirs; means for collecting word-of-mouth information about the suggested souvenirs and providing it to the user; means for generating reminders based on anniversary information and notifying the user; means for preferentially recommending regional specialties from among the suggested souvenirs; and means for linking with a virtual reality device that allows the user to explore virtual stores and confirm the souvenirs they have selected. This allows users to enjoy a sophisticated shopping experience using virtual reality from their travel destination or at home, eliminating the need to select the optimal souvenir and contributing to the spread of regional specialties and the development of the local economy.

[1137] "User's budget" is the upper limit of the amount that a user sets for the products that he or she wishes to purchase.

[1138] "Travel destination" refers to a place or city that the user plans to visit.

[1139] "Preferences of the recipient" refers to the specific tastes and hobbies of the recipient to whom the user is giving a souvenir.

[1140] "Means for collecting information" refers to a method or device for obtaining the necessary information from the user.

[1141] An "artificial intelligence model" is an algorithm or system that learns from past data and trend information and makes optimal suggestions.

[1142] "Purchase location" refers to the geographic location or store where the user can actually purchase the recommended souvenir.

[1143] "Location Information" means data regarding a user's current geographic location.

[1144] An "online purchase option" is a choice that allows a user to purchase products over the Internet.

[1145] "Word-of-mouth information" is information about ratings and comments made by past users about products.

[1146] A "reminder" is a function or system that notifies users of specific dates, times, or anniversaries.

[1147] "Regional specialties" are products or foods that are produced in a particular region and are representative of that region.

[1148] A "virtual reality device" is a device that allows users to immerse themselves in a virtual space and experience it, and mainly includes head-mounted displays and VR goggles.

[1149] This invention provides a system that allows users to select the best souvenirs for their travels, with AI making suggestions based on information such as budget, destination, and the recipient's preferences, allowing users to efficiently select souvenirs.

[1150] First, the user uses a device to input information such as the travel destination, budget, and the recipient's preferences. The device provides an interface that sends this information to the server. For example, a user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets." This information is then sent to the server via a web browser or a dedicated application.

[1151] The server uses an artificial intelligence model to recommend the best souvenir based on the received user data. This artificial intelligence model is built using frameworks such as TensorFlow and PyTorch. The model learns from past data and trend information to select the souvenir item that best suits the user's input criteria. For example, "Japanese sweets from Tokyo" may be recommended.

[1152] Next, the server selects the place to purchase the recommended souvenir based on the location information. Specifically, it obtains the user's current location information using Google Maps API or similar, and searches for the nearest store that offers the recommended souvenir. The location information of that store is then provided to the user.

[1153] The server also provides the option of souvenirs available for purchase online, allowing users to purchase souvenirs over the Internet even if they don't have time to do so locally. Users can click on the provided link to access the online shop and complete the purchase.

[1154] Furthermore, the server collects and provides user-review information, which includes information on the evaluations and experiences of past purchasers. This information helps users confirm the reliability of the recommended souvenirs and assists them in making a purchasing decision.

[1155] The server also generates reminders based on the user's anniversary information and notifies the user. This function is often implemented using the Google Calendar API, and helps users choose the perfect souvenir for a particular anniversary or event.

[1156] Finally, the server includes a means for preferentially recommending local specialties. By preferentially recommending local specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Tokyo," the server can recommend specialties unique to Tokyo, thereby contributing to the spread of local culture and specialties.

[1157] Furthermore, this invention can be applied to virtual stores. By using a virtual reality device such as a head-mounted display or VR goggles, users can visit stores in a virtual space and check recommended souvenirs. Users can operate an avatar to explore the virtual store and experience the realistic shopping experience of the selected souvenir.

[1158] As a concrete example, consider the case where a user enters "Kyoto" as the travel destination, a budget of "5,000 yen," and "sake" as the recipient's preference. Based on this information, the server will recommend the most suitable sake based on past data and trend information. Furthermore, based on the user's current location, the server will provide the nearest store where the sake can be purchased and also provide a link to the online shop. Reviews will also be displayed, and a reminder related to the next anniversary will be set. Recommendations will also be prioritized for regional specialties, such as sake that is particularly famous in Kyoto.

[1159] Example prompt sentence:

[1160] Travel destination: Kyoto

[1161] Budget: 5,000 yen

[1162] Partner's preference: Sake

[1163] Current location: Tokyo

[1164] In this way, the system of this invention improves the travel experience while reducing the effort required for souvenir selection by making appropriate suggestions based on the user's budget and preferences using AI. In addition, by recommending local specialties, it can contribute to revitalizing the local economy.

[1165] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1166] Step 1:

[1167] The user uses a device to input information such as travel destination, budget, and the other person's preferences. The user provides information through an input form on the device, such as "Travel destination: Tokyo, budget: 3,000 yen, other person's preferences: Japanese sweets." This information is structured in JSON format or similar and sent to the server.

[1168] Step 2:

[1169] The server analyzes the information received from the user. To analyze the information, the server accesses a database and searches for past data and trend information. This process uses SQL queries and other methods to extract information based on the input travel destination, budget, and preferences. As a result of the analysis, a list of multiple potential souvenir items is generated.

[1170] Step 3:

[1171] The server runs an artificial intelligence model (using, for example, TensorFlow or PyTorch) based on the list of candidate items. The model learns from past user data and trend information and selects the souvenir item that best suits the input criteria. This process identifies recommended items such as "Japanese sweets from Tokyo."

[1172] Step 4:

[1173] The server selects the place to purchase the recommended souvenir items. It uses the Google Maps API to obtain the user's current location and search for the nearest store. The store's location is selected by calculating the distance between the user's current location and the destination based on the data obtained from Google Maps.

[1174] Step 5:

[1175] The server provides online purchasing options and generates links to online shops where the suggested souvenir items can be purchased in case the user is unable to purchase them locally. This is done by using the API of each online shop to search for the product ID and obtain the link to its purchase page.

[1176] Step 6:

[1177] The server collects reviews of recommended souvenir items and provides them to users. It retrieves ratings and comments from past users from a database such as MongoDB and displays them along with the analysis results. This allows users to confirm the reliability of the products.

[1178] Step 7:

[1179] The server generates reminders based on the anniversary information and notifies the user. It uses the Google Calendar API to retrieve the user's anniversary data and sets notifications when the date approaches. Notifications are sent as emails or in-app notifications.

[1180] Step 8:

[1181] The server prioritizes recommendations of local specialty products. Based on the analysis results, it extracts specialty product data related to the user's travel destination and adds them to the recommendation list with priority. This contributes to the spread of specialty products and the development of the local economy.

[1182] Step 9:

[1183] Users use a virtual reality device to explore virtual stores. They wear a head-mounted display and check recommended souvenir items in the virtual space. Users can control an avatar to visit stores and check detailed souvenir information and reviews in real time.

[1184] In this way, a system is constructed that realizes complex processing through the roles of the server, terminal, and user, and supports efficient and effective souvenir selection.

[1185] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1186] This invention is a system that allows users to select the best souvenirs for their travels. AI makes suggestions based on information such as budget, destination, and the recipient's preferences. It also has a function to adjust the suggestions by combining it with an emotion engine that recognizes the user's emotions. This system is specifically implemented as follows.

[1187] First, the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. The terminal provides an interface to send this information to the server. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to choose a souvenir for someone who likes Japanese sweets."

[1188] The server uses an AI model to suggest the best souvenir based on the received user data. This AI model selects the souvenir item that best suits the user's input criteria based on past data and trend information.

[1189] Furthermore, the server uses an emotion engine to recognize the user's emotions. It analyzes the user's facial expressions and tone of voice through emotion recognition devices (such as cameras and microphones) to understand their current emotional state. For example, if the user has a happy face, the server recognizes their emotional state as "happy."

[1190] The server adjusts the suggestions based on the user's emotional state as recognized by the emotion engine. For example, if the user is in a "happy" emotional state, the server will recommend souvenirs that will further enhance the user's joyful mood. In this way, suggestions that are tailored to the user's emotions will help the user select souvenirs that will provide greater satisfaction.

[1191] The server also monitors the user's emotional state in real time and updates the suggestions as needed. For example, if the user suddenly changes their mood or is not interested in a suggested souvenir, it can instantly suggest other options.

[1192] Furthermore, the server learns the user's past emotional data and reflects it in future souvenir suggestions, enabling more accurate suggestions based on the user's past emotional state and the type of souvenir they chose.

[1193] The server then selects a place to purchase the recommended souvenir based on the location information. Specifically, it searches for the nearest store that offers the recommended souvenir based on the user's current location information and provides the user with the location information of that store.

[1194] The server also provides the option of souvenirs that can be purchased online, allowing users to purchase souvenirs over the Internet even if they do not have time to purchase them locally.

[1195] Furthermore, the server collects and provides user-review information, which is information about the evaluations and experiences of past purchasers, to help users make purchasing decisions.

[1196] The server also generates reminders based on the user's anniversary information and notifies the user, allowing the user to select the perfect souvenir for a specific anniversary or event.

[1197] Finally, the server includes a means for preferentially recommending local specialties. By preferentially recommending local specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Tokyo," the server can recommend specialties unique to Tokyo, thereby contributing to the spread of local culture and specialties.

[1198] For example, if a user inputs "Kyoto" as their travel destination, a budget of "5,000 yen," and the other person's preference of "sake," and the emotion engine recognizes the emotion of "expectation," the system will suggest the most suitable sake based on past data and trends. The system will then provide the nearest store to the user's current location or a link to an online shop. It will also display reviews from past users and set reminders related to upcoming anniversaries. By prioritizing recommendations of sake that is particularly famous in Kyoto, the system also contributes to promoting local specialties.

[1199] In this way, the system of this invention not only uses AI to make appropriate suggestions based on the user's budget and preferences, but also uses an emotion engine to make suggestions that match the user's emotions, helping them choose souvenirs with greater satisfaction. Furthermore, by recommending local specialties, it can also contribute to revitalizing local economies.

[1200] The processing flow will be explained below.

[1201] Step 1:

[1202] The terminal provides the user with an interface to input budget, destination, and partner preferences. The user enters the information in the appropriate fields and clicks the submit button.

[1203] Step 2:

[1204] The terminal sends the information entered by the user, such as budget, travel destination, and partner preferences, to the server, which is then ready to receive the user's request.

[1205] Step 3:

[1206] The server uses an artificial intelligence model to suggest the best souvenir based on the received user data. This AI model analyzes past data and trend information to select the souvenir item that best suits the user's requirements.

[1207] Step 4:

[1208] The server uses an emotion engine to recognize the user's emotions. It analyzes the user's facial expressions and voice through the camera and microphone connected to the device to determine their current emotional state. For example, if the user is smiling, it will recognize that they are "happy."

[1209] Step 5:

[1210] The server adjusts the suggestions based on the user's emotional state as recognized by the emotion engine. For example, if the user is in a "happy" emotional state, the server will recommend souvenirs that will further enhance the user's joyful mood.

[1211] Step 6:

[1212] The server selects the place to purchase the suggested souvenir based on the user's current location information. Based on the user's current location information, it searches for the nearest store that offers the recommended souvenir and obtains the store's location information.

[1213] Step 7:

[1214] The server retrieves online shopping links for each item to provide online purchasing options for the suggested souvenirs, and if available, provides the link to the user.

[1215] Step 8:

[1216] The server collects word-of-mouth information about the proposed souvenirs, pulls out reviews and ratings left by past buyers from a database, and provides them to the user.

[1217] Step 9:

[1218] The server generates reminders based on the user's anniversary information, helping them select the appropriate souvenir for a specific anniversary or event.

[1219] Step 10:

[1220] The server prioritizes regional specialty products from among the recommended souvenirs. Based on data related to regional specialty products, the server prioritizes local products to support the revitalization of the local economy.

[1221] Step 11:

[1222] The server then sends all the results back to the device, including a list of the best souvenirs, where to buy, online options, reviews, reminders, and preferred recommendations for local specialties.

[1223] Step 12:

[1224] The terminal displays the information received from the server to the user, who then selects from the list of suitable souvenirs displayed on the terminal screen and obtains the desired product using the provided purchasing locations or online options.

[1225] As a specific example, if a user inputs "Kyoto" as their travel destination, a budget of "5,000 yen," and the recipient's preference of "sake," and the emotion engine recognizes the emotion of "expectation," the server will use an AI model to suggest the most suitable sake. The server will then provide the store closest to the user's current location, along with reviews. It will also provide an online purchase link. Furthermore, a reminder related to the next anniversary will be generated, with priority given to recommendations of local sake, a Kyoto specialty. Based on this information, users can select and purchase the perfect souvenir.

[1226] Example 2

[1227] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1228] Traditionally, choosing the right souvenirs for a trip has been challenging, especially when it comes to making optimal choices based on the user's budget and the recipient's preferences. Furthermore, there has been a lack of methods to improve satisfaction by adjusting recommendations based on the user's emotional state. Furthermore, there have been insufficient efforts to revitalize local economies through preferential recommendations of regional specialties. Therefore, there is a need for a system that collects user information, considers the user's emotional state, makes optimal recommendations, and prioritizes regional specialties.

[1229] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1230] In this invention, the server includes means for collecting information on a user's budget, travel destination, and partner preferences, means for executing an artificial intelligence model to suggest optimal products to the user based on the collected information, means for executing an emotion recognition engine to recognize the user's emotional state regarding the suggested products, means for adjusting the content of the suggestions based on the user's emotional state, means for selecting and providing a purchase location for the suggested products based on location information, means for providing an online purchase option for the suggested products, means for collecting and providing evaluation information on the suggested products to the user, means for generating a reminder based on anniversary information and notifying the user, and means for preferentially recommending regional specialties from among the suggested products. This makes it possible to provide highly satisfying suggestions that are in line with the user's emotional state and to revitalize local economies through preferential recommendations of regional specialties.

[1231] "User" refers to a person who uses the system to select souvenirs at a travel destination.

[1232] "Budget" refers to the upper limit of the amount of money that a user sets for purchasing souvenirs at a travel destination.

[1233] "Travel destination" refers to a place that a user visits during a trip.

[1234] "The recipient's tastes" refers to the preferences and interests of the person receiving the souvenir.

[1235] "Means for collecting information" refers to methods and devices for obtaining data about a user's budget, travel destinations, and partner preferences.

[1236] An "artificial intelligence model" refers to an algorithm or program that selects the most suitable product based on collected information.

[1237] An "emotion recognition engine" refers to a system that analyzes and recognizes a user's emotional state from facial expressions, tone of voice, etc.

[1238] The "means for adjusting the content of the proposal" refers to a method or device for changing the optimal product proposal based on the emotional state of the user obtained by the emotion recognition engine.

[1239] "Location information" refers to geographical data used to identify a user's current location.

[1240] "Means for selecting a purchasing location" refers to a method or device for identifying the optimal product purchasing location based on location information.

[1241] "Online Purchase Option" refers to an option for a User to purchase Products over the Internet.

[1242] "Evaluation Information" refers to feedback and reviews of products provided by past users.

[1243] "Reminder" refers to a function or message that notifies the user on special occasions or specific events.

[1244] "Regional specialty products" refer to products that are produced in a specific region and are representative of that region.

[1245] The present invention is a system that allows users to select the best souvenir for their travel destination, and is implemented through the following process. The process begins when the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. The terminal is equipped with an interface for collecting this information and sending it to a server. For example, the user might input, "I'm traveling to Tokyo, my budget is 3,000 yen, and I want to select a souvenir for someone who likes Japanese sweets."

[1246] The device sends this information to a server via the internet. The server then uses the information it receives to run an artificial intelligence (AI) model, which then suggests the best souvenir. This AI model uses past data and trend information to select the souvenir item that best suits the user's input criteria. For example, it suggests the most highly rated Japanese sweets available in Tokyo.

[1247] Furthermore, the server is equipped with an emotion recognition engine that analyzes the user's emotions through emotion recognition devices (cameras and microphones). The emotion recognition engine analyzes the user's facial expressions and tone of voice to determine their current emotional state. For example, if the user has a happy face, the emotional state is recognized as "happy."

[1248] The server has the ability to adjust the content of suggestions based on the user's emotional state as recognized by the emotion recognition engine. For example, if the user is in a "happy" emotional state, the server will recommend items that will further increase the user's joy. This can increase user satisfaction.

[1249] Next, the server selects the place to purchase the recommended product based on the user's current location information. For example, the server uses GPS data to confirm that the user is currently in "Shinjuku," searches for stores selling the recommended Japanese sweets in the Shinjuku area, and provides the user with their location information.

[1250] The server can also provide online purchasing options, allowing users to purchase souvenirs over the Internet if they don't have time to shop locally. Additionally, the server can provide reviews collected from past users, allowing users to see other people's ratings and feedback.

[1251] The server also includes a function to generate reminders based on anniversary information and notify users. For example, it can notify users that their wedding anniversary is approaching and suggest suitable souvenirs.

[1252] Finally, the server has a means to recommend regional specialties to the user. For example, if a user is looking for souvenirs in "Tokyo," the server will recommend regional specialties unique to Tokyo, such as "Tokyo Banana" and "Kaminariokoshi."

[1253] As a concrete example, let's consider a scenario in which a user inputs "Kyoto" as the travel destination, a budget of "5,000 yen," and the other person's preference of "sake," and the emotion engine recognizes the emotion of "expectation." The system uses an AI model to suggest highly rated sake in Kyoto and provides information on the nearest store to purchase it from the user's current location. At the same time, the system also provides links to online shops, reviews from past users, and reminders related to the next anniversary, and prioritizes recommendations of famous sake, a Kyoto specialty.

[1254] An example of a specific prompt for a generative AI model is, "Please suggest a souvenir for someone who is traveling to Kyoto, has a budget of 5,000 yen, and likes sake. The user is currently in an emotional state of expectation."

[1255] In this way, AI makes appropriate suggestions based on the user's budget and preferences, and the emotion engine makes suggestions that match the user's emotions, helping them choose souvenirs that will leave them satisfied. Recommending local specialties also contributes to the development of local economies.

[1256] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1257] Step 1: The user uses the terminal to input information such as travel destination, budget, partner preferences, etc. The input information is sent to the server through the interface.

[1258] Input: "Travel destination (e.g. Tokyo)", "Budget (e.g. 3,000 yen)", "Partner's preferences (e.g. Japanese sweets)"

[1259] Output: Request data sent from the terminal to the server

[1260] Step 2: The server receives the information sent from the device and inputs it into an artificial intelligence (AI) model, which then selects the best souvenir based on past data and trend information.

[1261] Input: User's "travel destination", "budget", and "preferences" data

[1262] Data processing / calculation: The AI ​​model analyzes this data and uses historical databases and trend algorithms to extract the most suitable products.

[1263] Output: Data suggesting the best souvenirs (e.g., highly rated Japanese sweets available in Tokyo)

[1264] Step 3: The server uses an emotion recognition engine to collect the user's emotion data from the emotion recognition device (camera or microphone) and recognize the user's current emotional state.

[1265] Input: User's facial expressions and tone of voice obtained from emotion recognition device

[1266] Data processing / calculation: An emotion recognition engine analyzes this data and classifies the emotional state as "happy," for example.

[1267] Output: Data on the user's emotional state (e.g., "happy")

[1268] Step 4: The server adjusts the suggestions based on the emotional state data. Appropriate suggestions are made based on the emotional state.

[1269] Input: optimal souvenir suggestion data, user emotional state data

[1270] Data processing / calculation: Filtering and adjusting the suggestions to reselect the souvenir that best suits the user's emotional state.

[1271] Output: Tailored souvenir suggestion data (e.g. Japanese sweets in special packaging)

[1272] Step 5: The server selects the recommended product purchasing location based on the user's current location information and provides the specific location information of the store where the product was purchased.

[1273] Input: User's current location information (GPS data), tailored souvenir suggestion data

[1274] Data processing / calculation: Search for the nearest store to your current location and identify its location information.

[1275] Output: Location information of the nearest store (e.g., a list of stores in Shinjuku)

[1276] Step 6: The server also provides an online purchase option, allowing users to purchase souvenirs over the Internet.

[1277] Input: Adjusted souvenir suggestion data

[1278] Data processing / calculation: Generate an online shop link and provide it as a purchasing option.

[1279] Output: Online purchase option link (e.g. Japanese sweets online shop URL)

[1280] Step 7: The server collects evaluation information about the proposed souvenir and provides it to the user. It also displays reviews from past users.

[1281] Input: Adjusted souvenir suggestion data

[1282] Data processing / calculation: Obtain and organize relevant word-of-mouth information from the evaluation database.

[1283] Output: User reviews (e.g., "This Japanese sweet was really delicious!")

[1284] Step 8: The server generates a reminder based on the anniversary information and notifies the user.

[1285] Input: User's anniversary information, tailored souvenir suggestion data

[1286] Data Processing / Calculation: Schedule reminder notifications when an anniversary is approaching.

[1287] Output: Reminder notification (e.g. "Let's prepare a souvenir for our anniversary!")

[1288] Step 9: The server recommends regional specialties from the proposed products with priority.

[1289] Input: Adjusted souvenir suggestion data

[1290] Data processing / calculation: Refer to the regional specialty product database and prioritize recommendations of products unique to that region.

[1291] Output: Recommendation data for local specialties (e.g., "Tokyo Banana" and "Kaminariokoshi")

[1292] (Application example 2)

[1293] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1294] With conventional technology, it was difficult to provide optimal recommendations for souvenirs when choosing them at a travel destination, taking into account the user's personal preferences and emotional state. This resulted in users choosing inappropriate souvenirs, which reduced user satisfaction. Furthermore, recommendations of local specialties were weak, and the promotion of local economies was insufficient. It is necessary to solve these issues, provide more useful information to users, and contribute to the development of local economies.

[1295] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1296] In this invention, the server includes means for collecting information on the user's budget, travel destination, and partner's preferences, emotion recognition means for recognizing the user's emotions, means for executing an artificial intelligence model to suggest optimal souvenirs to the user based on the collected information and the emotional state obtained by the emotion recognition means, means for selecting a place to purchase the suggested souvenirs from location information, means for providing online purchase options for the suggested souvenirs, means for collecting word-of-mouth information on the suggested souvenirs and providing it to the user, means for generating reminders based on anniversary information and notifying the user, and means for preferentially recommending regional specialties from among the suggested souvenirs. This makes it possible to suggest optimal souvenirs tailored to the user's emotional state and also to preferentially recommend regional specialties.

[1297] A "user budget" is a monetary limit that a user is willing to spend on a particular product or service.

[1298] A "travel destination" is a geographic location or destination that a user plans to visit.

[1299] "The recipient's preferences" refer to the things or tastes that the person receiving the souvenir is particularly interested in.

[1300] "Means of collecting information" refers to the interface and functions for obtaining the necessary data from the user.

[1301] "Emotion recognition means" refers to devices or algorithms that evaluate and identify a user's emotional state, such as facial expressions or voice.

[1302] An "artificial intelligence model" is a computer program that uses specific algorithms and statistical models to analyze data and suggest the best souvenirs for users.

[1303] The "means for selecting a place to purchase" refers to a function for identifying the most suitable place to purchase based on the user's current location information, etc.

[1304] "Means for providing online purchase options" refers to a function that provides links and information that allow users to purchase souvenirs over the Internet.

[1305] "Means for collecting and providing word-of-mouth information" refers to a function for collecting ratings and reviews from past purchasers and displaying that information to users.

[1306] "Means for generating and notifying reminders based on anniversary information" refers to a function that creates reminders for the user's anniversaries or specific events and notifies the user.

[1307] The "means for preferentially recommending local specialty products" is a function for preferentially recommending to the user specialty products produced in a specific region.

[1308] The present invention is a system for allowing users to select the best souvenirs at their travel destinations. The system includes the following components:

[1309] First, the user uses a terminal to input information such as the travel destination, budget, and the recipient's preferences. For example, the user might input, "I'm traveling to Kyoto, my budget is 5,000 yen, and I want to choose a souvenir for someone who likes sake." The terminal provides an interface that sends the input information to the server.

[1310] Next, the server uses the received information to suggest the best souvenirs using an AI model. This AI model selects souvenir items that best fit the user's input criteria based on past data and trend information. Specifically, the AI ​​model analyzes the user's input criteria and suggests the best items from products specific to the travel destination.

[1311] Furthermore, the server uses emotion recognition means to recognize the user's emotional state. It analyzes the user's facial expressions and tone of voice through emotion recognition devices (such as cameras and microphones) to understand the user's current emotional state. For example, if the user has a happy face, the server recognizes the user's emotional state as "happy."

[1312] The server adjusts the suggestions based on the user's emotional state. For example, if the user is in a "happy" emotional state, it will recommend souvenirs that will further enhance the user's joyful mood. In this way, by making suggestions that are in line with the user's emotions, the server helps the user choose souvenirs that will give them greater satisfaction.

[1313] The server also searches for recommended souvenir purchasing locations based on the user's current location information. It provides the location information of the nearest store from the user's current location or a link to an online shop. This allows users to purchase souvenirs over the Internet even if they don't have time to buy them locally.

[1314] In addition, the server collects and provides user-review information, including information on the evaluations and experiences of past purchasers, to assist users in making purchasing decisions.

[1315] The server generates reminders based on the user's anniversary information and notifies the user, allowing the user to select the perfect souvenir for a specific anniversary or event.

[1316] Finally, the server includes a means for preferentially recommending regional specialties. By preferentially recommending regional specialties to the user, it is possible to contribute to the development of the local economy. For example, if a user is looking for souvenirs in "Kyoto," the server can recommend Kyoto-specific specialties, thereby contributing to the spread of local culture and specialties.

[1317] Examples:

[1318] If the user inputs "Kyoto" as the travel destination, a budget of "5,000 yen," and the other person's preference of "sake," and the emotion of "expectation" is recognized from the camera image, the system will make specific suggestions such as the following.

[1319] Recommended souvenir: Kyoto's famous local sake

[1320] Where to buy: Select local stores

[1321] Online option: Online shop link for the product

[1322] Example prompt sentence:

[1323] The user has selected "Kyoto" as their travel destination, their budget is "5000 yen", and their partner's preference is "sake". The user's emotional state is "expectation". Please suggest the best sake souvenir. Also provide where to buy it and online options.

[1324] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1325] Step 1:

[1326] The user uses the terminal to input information such as the travel destination, budget, and the partner's preferences.

[1327] Input: Travel destination (e.g. Kyoto), budget (5,000 yen), partner's preference (sake)

[1328] Output: User input data

[1329] Specific operation: The user enters the required information through the device interface, and the data is saved in the device.

[1330] Step 2:

[1331] The terminal transmits the user input data to the server.

[1332] Input: User-entered data

[1333] Output: User data sent to the server

[1334] Specific operation: The terminal transmits the collected user input data to a server via the Internet.

[1335] Step 3:

[1336] Based on the user data received by the server, a generative AI model is used to suggest the best souvenir.

[1337] Input: User data sent to the server

[1338] Output: Perfect souvenir item

[1339] Specific operation: The server runs an AI model based on the received data and selects the souvenir that best suits the user's requirements.

[1340] Step 4:

[1341] The server uses emotion recognition means to recognize the emotional state of the user.

[1342] Input: User facial or voice data

[1343] Output: Emotional state (e.g., "happy," "expected")

[1344] How it works: The server analyzes data obtained from the camera and microphone and uses emotion recognition models to identify the user's emotional state.

[1345] Step 5:

[1346] The server adjusts the souvenir suggestions based on the emotional state.

[1347] Input: Best souvenir item, user's emotional state

[1348] Output: Tailored souvenir suggestions

[1349] Specific operation: The server selects souvenirs that match the user's emotional state and updates the recommendations.

[1350] Step 6:

[1351] The server selects the place to purchase the suggested souvenir based on the location information.

[1352] Input: Best souvenir item, user's current location

[1353] Output: Location of nearest store

[1354] Specific operation: The server obtains the user's current location information and searches for the nearest store that offers the best souvenirs.

[1355] Step 7:

[1356] The server provides an online purchase option for the suggested souvenirs.

[1357] Enter: Perfect souvenir item

[1358] Output: Online store link

[1359] What it does: The server searches a database on the Internet and generates links to purchase the suggested souvenirs online.

[1360] Step 8:

[1361] The server collects word-of-mouth information about the proposed souvenirs and provides it to the user.

[1362] Enter: Perfect souvenir item

[1363] Output: Reviews

[1364] Specific operation: The server collects reviews and ratings from past buyers and selects the data to provide to the user.

[1365] Step 9:

[1366] The server generates a reminder based on the anniversary information and notifies the user.

[1367] Input: User's anniversary information

[1368] Output: Reminder notification

[1369] Specific operation: The server generates reminders based on the user's anniversary information and sends notifications to the user at the specified time.

[1370] Step 10:

[1371] The server will prioritize recommendations of local specialties.

[1372] Input: Best souvenir items, local specialty information

[1373] Output: A list of recommended local specialties

[1374] Specific operation: The server prioritizes and recommends local specialties based on the user's input conditions and information on local specialties, and creates suggestions.

[1375] 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.

[1376] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1377] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1378] 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.

[1379] FIG. 9 is a diagram illustrating 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 actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect 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.

[1380] 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.

[1381] 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).

[1382] 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 indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, motorcycles, and other devices, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1383] 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."

[1384] 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.

[1385] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1386] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1387] 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.

[1388] 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.

[1389] 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.

[1390] The hardware resource for executing a specific process can be any of the following processors: An example of a processor 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. Another example of a processor is 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.

[1391] The hardware resource that executes the specific processing 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 processing may be a single processor.

[1392] 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.

[1393] 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.

[1394] 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.

[1395] 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.

[1396] The following is further disclosed regarding the above embodiment.

[1397] (Claim 1)

[1398] a means of collecting information about the user's budget, travel destination, and partner preferences;

[1399] means for executing an artificial intelligence model to suggest the most suitable souvenir to the user based on the collected information;

[1400] A means for selecting a place to purchase the suggested souvenir from location information;

[1401] means of providing online purchasing options for the proposed souvenirs;

[1402] A means for collecting and providing user reviews of the proposed souvenirs;

[1403] A means for generating a reminder based on the anniversary information and notifying the user of the reminder;

[1404] A method to prioritize and recommend local specialties from among the suggested souvenirs,

[1405] A system including:

[1406] (Claim 2)

[1407] 2. The system according to claim 1, wherein the system selects the most suitable place to purchase based on the user's current location information.

[1408] (Claim 3)

[1409] 2. The system according to claim 1, which collects information on local specialties and recommends souvenirs on a preferential basis based on that information.

[1410] "Example 1" (Claim 1)

[1411] a means of collecting information about the user's budget, travel destination, and partner preferences;

[1412] A means for executing a generative AI model to suggest optimal souvenirs to the user based on the collected information; and

[1413] A means for selecting a place to purchase the suggested souvenir from location information;

[1414] means of providing online purchasing options for the proposed souvenirs;

[1415] A means for collecting and providing user reviews of the proposed souvenirs;

[1416] A means for generating a reminder based on the anniversary information and notifying the user of the reminder;

[1417] A method to prioritize and recommend local specialties from among the suggested souvenirs,

[1418] A system including:

[1419] (Claim 2)

[1420] The system of claim 1, further comprising: means for selecting the optimal place to purchase souvenirs based on the user's current location information and providing that information; means for providing a link to the suggested souvenirs if they are available for purchase online; and means for selecting souvenirs based on a generative AI model and taking into account past trend information.

[1421] (Claim 3)

[1422] 2. The system according to claim 1, further comprising means for collecting information on local specialty products and, based on the information, preferentially recommending souvenirs to promote regional economic development.

[1423] In this way, we added distinctive features to the system to flesh out the claims.

[1424] "Application Example 1"

[1425] (Claim 1)

[1426] a means of collecting information about the user's budget, travel destination, and partner preferences;

[1427] means for executing an artificial intelligence model to suggest the most suitable souvenir to the user based on the collected information;

[1428] A means for selecting a place to purchase the suggested souvenir from location information;

[1429] means of providing online purchasing options for the proposed souvenirs;

[1430] A means for collecting and providing user reviews of the proposed souvenirs;

[1431] A means for generating a reminder based on the anniversary information and notifying the user of the reminder;

[1432] A method to prioritize and recommend local specialties from among the suggested souvenirs,

[1433] means for linking with a virtual reality device that allows the user to view the selected souvenir while exploring the virtual store;

[1434] A system including:

[1435] (Claim 2)

[1436] 2. The system according to claim 1, wherein the system selects the most suitable place to purchase based on the user's current location information.

[1437] (Claim 3)

[1438] 2. The system according to claim 1, which collects information on local specialties and recommends souvenirs on a preferential basis based on that information.

[1439] "Example 2: Combining Emotion Engines"

[1440] (Claim 1)

[1441] a means of collecting information about the user's budget, travel destination, and partner preferences;

[1442] means for executing an artificial intelligence model to recommend optimal products to the user based on the collected information;

[1443] means for implementing an emotion recognition engine to recognize the user's emotional state with respect to the proposed product;

[1444] means for adjusting the suggestions based on the user's emotional state;

[1445] A means for selecting and providing a place to purchase the suggested product based on location information;

[1446] means for providing online purchasing options for the proposed products;

[1447] A means for collecting evaluation information regarding the proposed product and providing it to the user;

[1448] A means for generating a reminder based on the anniversary information and notifying the user of the reminder;

[1449] A method to prioritize and recommend local specialties from among the proposed products;

[1450] A system including:

[1451] (Claim 2)

[1452] 2. The system according to claim 1, wherein the system selects the most suitable place to purchase based on the user's current location information.

[1453] (Claim 3)

[1454] 2. The system according to claim 1, which collects information on local specialty products and recommends products preferentially based on that information.

[1455] "Application example 2 when combining emotion engines"

[1456] (Claim 1)

[1457] a means of collecting information about the user's budget, travel destination, and partner preferences;

[1458] emotion recognition means for recognizing an emotion of a user;

[1459] means for executing an artificial intelligence model to suggest the most suitable souvenir to the user based on the collected information and the emotional state obtained by the emotion recognition means;

[1460] A means for selecting a place to purchase the suggested souvenir from location information;

[1461] means of providing online purchasing options for the proposed souvenirs;

[1462] A means for collecting and providing user reviews of the proposed souvenirs;

[1463] A means for generating a reminder based on the anniversary information and notifying the user of the reminder;

[1464] A method to prioritize and recommend local specialties from among the suggested souvenirs,

[1465] A system including:

[1466] (Claim 2)

[1467] 10. The system of claim 1, further comprising means for adjusting souvenir suggestions based on the user's emotional state.

[1468] (Claim 3)

[1469] 2. The system according to claim 1, wherein the system selects the most suitable place to purchase based on the user's current location information. [Explanation of symbols]

[1470] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means of collecting information about the user's budget, travel destination, and partner preferences; means for executing an artificial intelligence model to suggest the most suitable souvenir to the user based on the collected information; A means for selecting a place to purchase the suggested souvenir from location information; means of providing online purchasing options for the proposed souvenirs; A means for collecting and providing user reviews of the proposed souvenirs; A means for generating a reminder based on the anniversary information and notifying the user of the reminder; A method to prioritize and recommend local specialties from among the suggested souvenirs, A system including:

2. The system according to claim 1, wherein the system selects the most suitable place to purchase based on the user's current location information.

3. 2. The system according to claim 1, wherein information on local specialty products is collected and souvenirs are preferentially recommended based on the information.

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