system

Abstract

The system according to the embodiment aims to provide a consistent service from suggesting gifts to revitalizing local industries based on the user's needs and preferences. [Solution] The system according to the embodiment comprises a suggestion unit, a selection unit, a management unit, a reduction unit, and an activation unit. The suggestion unit suggests gift ideas based on the user's needs and preferences. The selection unit selects appropriate gifts from among those suggested by the suggestion unit. The management unit manages costs and schedules for the gifts selected by the selection unit. The reduction unit reduces the burden associated with purchasing and delivering gifts managed by the management unit. The activation unit aims to revitalize local industries through the purchase and delivery of gifts whose costs have been reduced by the reduction unit.

Description

[Technical Field]

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

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

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

[0004] Conventional technology has faced challenges in that it is difficult to consistently suggest and select gifts based on users' needs and preferences, manage costs, manage schedules, reduce the burden of purchasing and delivery, and even revitalize local industries.

[0005] The system according to the embodiment aims to provide a consistent service from suggesting gifts to revitalizing local industries based on the user's needs and preferences. [Means for solving the problem]

[0006] The system according to the embodiment includes a suggestion unit, a selection unit, a management unit, a reduction unit, and an activation unit. The suggestion unit suggests gift ideas based on the user's needs and preferences. The selection unit selects appropriate gifts from among those suggested by the suggestion unit. The management unit manages costs and schedules for the gifts selected by the selection unit. The reduction unit reduces the burden associated with purchasing and delivering gifts managed by the management unit. The activation unit aims to revitalize local industries through the purchase and delivery of gifts whose costs have been reduced by the reduction unit. [Effects of the Invention]

[0007] The system according to the embodiment can consistently provide services ranging from suggesting gifts to revitalizing local industries based on the user's needs and preferences. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) A gift communication system according to an embodiment of the present invention uses AI to connect people. This gift communication system proposes gift ideas based on a user's needs and preferences, selects personalized gifts, manages costs and schedules, reduces the burden of gift purchasing and delivery, and revitalizes local industries. For example, AI proposes gift ideas based on a user's needs and preferences. If a user is looking for a gift for a friend's birthday, AI suggests optimal gift ideas based on the friend's hobbies and interests. This proposal is made by analyzing the user's past purchase history and social media posts. Next, a personalized gift is selected. AI selects the most suitable gift for the user from the proposed gifts and provides personalized message and wrapping options. For example, the user can add a special message or customize the gift with original wrapping. Furthermore, cost and schedule management are performed. AI optimizes the costs of gift purchase and delivery, providing the optimal gift within the user's budget. It also manages gift delivery schedules to ensure delivery on the specified date and time. For example, if a user requests a gift be delivered to a friend for their birthday, AI adjusts the delivery schedule to match that date and time. It also reduces the burden of purchasing and delivering gifts. AI eliminates the hassle of selecting gifts for users, allowing them to easily purchase online. Furthermore, by linking with delivery companies, it is possible to track the delivery status of gifts in real time, allowing users to wait for their gifts with peace of mind. Finally, it aims to revitalize local industries. AI suggests local specialties and handmade gifts, contributing to the promotion of local industries. For example, suggesting local crafts and agricultural products as gifts can revitalize the local economy. In this way, a gift communication system using AI will create a system that makes buyers, recipients, and makers happy.This allows the gift communication system to suggest gift ideas based on users' needs and preferences, select personalized gifts, manage costs and schedules, reduce the burden of purchasing and delivering gifts, and revitalize local industries.

[0029] A gift communication system according to an embodiment includes a suggestion unit, a selection unit, a management unit, a reduction unit, and an activation unit. The suggestion unit suggests gift ideas based on a user's needs and preferences. For example, the suggestion unit analyzes the user's past purchase history and social media posts to suggest optimal gift ideas. For example, if a user is looking for a gift for a friend's birthday, the suggestion unit can suggest optimal gift ideas based on the friend's hobbies and interests. The selection unit selects an optimal gift from among the gifts suggested by the suggestion unit. For example, the selection unit provides personalized message and wrapping options. For example, the selection unit can add a special message or provide original wrapping to a gift selected by the user. The management unit optimizes costs associated with purchasing and delivering gifts to provide optimal gifts within a user's budget. For example, the management unit can optimize costs associated with purchasing and delivering gifts to provide optimal gifts within a user's budget. The management unit also manages gift delivery schedules to ensure gifts are delivered on the specified date and time. For example, if a user specifies, "I want to deliver a gift to a friend on their birthday," the management unit can adjust the delivery schedule to match that date and time. The reduction unit reduces the burden associated with purchasing and delivering gifts. For example, the reduction unit eliminates the need for a user to select a gift, allowing the user to easily purchase the gift online. For example, the reduction unit can track the delivery status of the gift in real time by coordinating with a delivery company. This allows the user to wait for the gift to arrive with peace of mind. The revitalization unit contributes to the promotion of local industries by suggesting local specialties and handmade gifts. For example, the revitalization unit can revitalize the local economy by suggesting local crafts and agricultural products as gifts. As a result, the gift communication system according to the embodiment can suggest gift ideas based on the user's needs and preferences, select personalized gifts, manage costs and schedules, reduce the burden associated with purchasing and delivering gifts, and revitalize local industries.

[0030] The suggestion unit can analyze the user's past purchase history and social media posts to suggest suitable gift ideas. The suggestion unit can, for example, analyze the user's past purchase history to suggest optimal gift ideas. The suggestion unit can also, for example, analyze the user's social media posts to suggest optimal gift ideas. The suggestion unit can, for example, analyze the types of products the user has purchased in the past and the frequency of purchases to suggest optimal gift ideas. The suggestion unit can, for example, analyze the user's social media posts to suggest optimal gift ideas based on the content and frequency of the posts, the number of likes and comments, etc. In this way, the suggestion unit can suggest more personalized gift ideas by analyzing the user's past purchase history and social media posts.

[0031] The selection unit may provide personalized messages and wrapping options. For example, the selection unit may add a special message to a gift selected by a user. For example, the selection unit may provide original wrapping for a gift selected by a user. For example, the selection unit may provide a message tailored to a user's name or a specific event. For example, the selection unit may select wrapping options such as color, design, and material. In this way, the selection unit may provide personalized messages and wrapping options, allowing the user to select a more special gift.

[0032] The management unit appropriately manages costs for purchasing and delivering gifts, and is able to provide an appropriate gift within the user's budget. The management unit, for example, optimizes the purchase cost of gifts, and is able to provide an optimal gift within the user's budget. The management unit can also optimize delivery costs, and is able to provide an optimal gift within the user's budget. The management unit can also optimize both purchase and delivery costs, and is able to provide an optimal gift within the user's budget. The management unit appropriately manages costs, for example, by using a budget setting method and a cost tracking method. In this way, the management unit can optimize costs, and is able to provide an optimal gift within the user's budget.

[0033] The management unit manages the delivery schedule for the gift and can reliably deliver the gift at the specified date and time. The management unit, for example, adjusts the delivery schedule to match the date and time specified by the user. The management unit, for example, works with a delivery company to reliably deliver the gift at the specified date and time. The management unit, for example, manages the delivery schedule in real time and can reliably deliver the gift at the specified date and time. The management unit manages the delivery schedule, for example, by using a method for setting delivery dates and times and tracking progress. In this way, the management unit manages the delivery schedule and can reliably deliver the gift at the specified date and time.

[0034] The reduction unit can eliminate the effort required for a user to select a gift and enable easy online purchases. For example, the reduction unit can eliminate the effort required for a user to select a gift and enable easy online purchases. For example, the reduction unit can track the delivery status of a gift in real time by cooperating with a delivery company. For example, the reduction unit notifies the user of the delivery status so that the user can wait for the arrival of the gift with peace of mind. For example, the reduction unit can reduce the effort required for online purchases by simplifying online purchases or automating the selection process. In this way, the reduction unit can eliminate the effort required for a user to select a gift and enable easy online purchases.

[0035] The reduction unit can track the delivery status of the gift in real time by cooperating with the delivery company. The reduction unit, for example, tracks the delivery status of the gift in real time by cooperating with the delivery company. The reduction unit can track the delivery status of the gift in real time by using a tracking system, for example. The reduction unit can update delivery status data in real time and notify the user. The reduction unit tracks the delivery status in real time by using, for example, the type of tracking system and the frequency of data updates. In this way, the reduction unit tracks the delivery status in real time, allowing the user to wait for the arrival of the gift with peace of mind.

[0036] The revitalization department can contribute to the promotion of local industries by suggesting local specialty products and handmade gifts. The revitalization department can, for example, suggest local specialty products and promote local industries. The revitalization department can, for example, suggest local handmade products and promote local industries. The revitalization department can, for example, suggest gifts related to local events and promote local industries. The revitalization department can, for example, suggest local specialty products and handmade crafts. The revitalization department can, for example, contribute to the promotion of local industries by suggesting local specialty products and handmade gifts. In this way, the revitalization department can contribute to the promotion of local industries by suggesting local specialty products and handmade gifts.

[0037] The suggestion unit can analyze the user's past purchase history and social media posts to suggest gift ideas tailored to specific events or seasons. For example, the suggestion unit can suggest the perfect gift for this year's Christmas by referring to gifts the user purchased for Christmas in the past. For example, the suggestion unit can analyze posts related to Valentine's Day from the user's social media posts to suggest the perfect gift for Valentine's Day. For example, the suggestion unit can suggest the perfect gift for this year's Mother's Day by referring to gifts given on Mother's Day from the user's past purchase history. For example, the suggestion unit analyzes the user's past purchase history and social media posts to suggest gift ideas tailored to specific events or seasons. As a result, the suggestion unit can suggest more appropriate gifts by suggesting gift ideas tailored to specific events or seasons.

[0038] The suggestion unit can suggest gift ideas according to the relationships between the user's family and friends, taking into account the relationships between the family and friends. For example, the suggestion unit can suggest a gift that matches the hobbies of a best friend as a gift the user gives to the best friend. For example, the suggestion unit can suggest a gift that the whole family can enjoy as a gift the user gives to their family. For example, the suggestion unit can suggest a practical gift that can be used at work as a gift the user gives to a colleague. For example, the suggestion unit analyzes the relationships between the family and friends of the user in order to suggest gift ideas according to the relationships, taking into account the relationships between the family and friends. As a result, the suggestion unit can suggest more appropriate gifts by suggesting gift ideas according to the relationships.

[0039] The suggestion unit can suggest region-specific gift ideas by taking into account the user's geographical location information. For example, if the user lives in Hokkaido, the suggestion unit can suggest Hokkaido's specialties. For example, if the user lives in Kyoto, the suggestion unit can suggest Kyoto's traditional crafts. For example, if the user lives in Okinawa, the suggestion unit can suggest Okinawa's specialties. For example, the suggestion unit analyzes the user's geographical location information to suggest region-specific gift ideas by taking into account the geographical location information. This allows the suggestion unit to suggest more appropriate gifts by suggesting region-specific gift ideas.

[0040] The suggestion unit can analyze the user's social media activity and suggest gift ideas based on trends. For example, the suggestion unit can suggest trending products that the user is talking about on social media. For example, the suggestion unit can suggest gifts introduced by influencers that the user follows. For example, the suggestion unit can suggest gifts that are popular in online communities in which the user participates. For example, the suggestion unit analyzes the user's social media activity to analyze the social media activity and suggest gift ideas based on trends. This allows the suggestion unit to suggest more appropriate gifts by suggesting gift ideas based on trends.

[0041] The selection unit can analyze the user's past gift selection history and select the optimal selection method. For example, the selection unit can analyze trends in gifts selected by the user in the past and suggest similar gifts. For example, the selection unit can suggest highly rated gifts based on ratings of gifts selected by the user in the past. For example, the selection unit can suggest gifts in the same price range based on the price range of gifts selected by the user in the past. For example, the selection unit analyzes the user's past gift selection history to analyze the gift selection history and select the optimal selection method. In this way, the selection unit can select a more appropriate gift by analyzing the past gift selection history.

[0042] When selecting a gift, the selection unit can perform filtering based on the user's current living situation and areas of interest. For example, if the user has started a new hobby, the selection unit can suggest gifts related to the hobby. For example, if the user has moved, the selection unit can suggest gifts that are suitable for the new residence. For example, if the user has started a new job, the selection unit can suggest gifts related to the job. For example, the selection unit analyzes the user's current living situation and areas of interest to perform filtering based on the user's current living situation and areas of interest. As a result, the selection unit can select a more appropriate gift by filtering based on the user's current living situation and areas of interest.

[0043] The selection unit can prioritize region-specific gifts by taking into account the user's geographical location information. For example, if the user lives in Hokkaido, the selection unit can prioritize Hokkaido's specialty products. For example, if the user lives in Kyoto, the selection unit can prioritize Kyoto's traditional crafts. For example, if the user lives in Okinawa, the selection unit can prioritize Okinawa's specialty products. For example, the selection unit analyzes the user's geographical location information to prioritize region-specific gifts by taking into account the geographical location information. As a result, the selection unit can select a more appropriate gift by prioritized region-specific gifts.

[0044] The selection unit can analyze the user's social media activity and select a relevant gift. For example, the selection unit can select trending products that the user is talking about on social media. For example, the selection unit can select gifts introduced by influencers that the user follows. For example, the selection unit can select gifts that are popular in online communities in which the user participates. For example, the selection unit analyzes the user's social media activity to analyze the social media activity and select a relevant gift. In this way, the selection unit can select a more appropriate gift by analyzing the social media activity.

[0045] The management unit can optimize costs for purchasing and delivering gifts to provide an optimal gift within the user's budget. The management unit, for example, can optimize the cost of purchasing gifts to provide an optimal gift within the user's budget. The management unit, for example, can optimize the delivery cost to provide an optimal gift within the user's budget. The management unit, for example, can optimize both the costs of purchasing and delivery to provide an optimal gift within the user's budget. The management unit optimizes costs, for example, by using a budget setting or a cost tracking method. In this way, the management unit can optimize costs to provide an optimal gift within the user's budget.

[0046] The management unit manages the delivery schedule for the gift and can reliably deliver the gift at the specified date and time. The management unit, for example, adjusts the delivery schedule to match the date and time specified by the user. The management unit, for example, works with a delivery company to reliably deliver the gift at the specified date and time. The management unit, for example, manages the delivery schedule in real time and can reliably deliver the gift at the specified date and time. The management unit manages the delivery schedule, for example, by using a method for setting delivery dates and times and tracking progress. In this way, the management unit manages the delivery schedule and can reliably deliver the gift at the specified date and time.

[0047] The management unit can optimize the delivery schedule by taking into account the geographical location information of the user. For example, if the user lives in Hokkaido, the management unit can optimize the delivery schedule within Hokkaido. For example, if the user lives in Kyoto, the management unit can optimize the delivery schedule within Kyoto. For example, if the user lives in Okinawa, the management unit can optimize the delivery schedule within Okinawa. For example, the management unit analyzes the geographical location information of the user to optimize the delivery schedule by taking into account the geographical location information. This allows the management unit to perform more appropriate management by optimizing the delivery schedule by taking into account the geographical location information.

[0048] The management unit can analyze the user's social media activity and perform related cost management and schedule management. For example, the management unit can perform cost management based on events that the user is talking about on social media. For example, the management unit can perform schedule management based on events of influencers that the user follows. For example, the management unit can manage costs and schedules based on events of online communities in which the user participates. For example, the management unit analyzes the user's social media activity to analyze the social media activity and perform related cost management and schedule management. This allows the management unit to perform more appropriate management by analyzing the social media activity.

[0049] The reduction unit can analyze the user's past gift purchase history and select the optimal reduction method. For example, the reduction unit can analyze trends in gifts purchased by the user in the past and suggest similar gifts. For example, the reduction unit can suggest highly rated gifts based on ratings of gifts purchased by the user in the past. For example, the reduction unit can suggest gifts in the same price range based on the price range of gifts purchased by the user in the past. For example, the reduction unit analyzes the user's past gift purchase history to analyze the gift purchase history and select the optimal reduction method. In this way, the reduction unit can select a more appropriate reduction method by analyzing the past gift purchase history.

[0050] The reduction unit can reduce the burden of purchasing and delivering gifts, making it easier to purchase online. For example, the reduction unit can eliminate the effort of selecting a gift, making it easier to purchase online. For example, the reduction unit can track the delivery status of the gift in real time by cooperating with a delivery company. For example, the reduction unit notifies the user of the delivery status so that the user can wait for the arrival of the gift with peace of mind. For example, the reduction unit simplifies online purchases and automates the selection process to reduce the burden. In this way, the reduction unit can reduce the burden of purchasing and delivering gifts, making it easier to purchase online.

[0051] The reduction unit can optimize cooperation with delivery companies by taking into account the geographical location information of the user. For example, if the user lives in Hokkaido, the reduction unit can optimize cooperation with delivery companies in Hokkaido. For example, if the user lives in Kyoto, the reduction unit can optimize cooperation with delivery companies in Kyoto. For example, if the user lives in Okinawa, the reduction unit can optimize cooperation with delivery companies in Okinawa. For example, the reduction unit analyzes the geographical location information of the user to optimize cooperation with delivery companies by taking into account the geographical location information. As a result, the reduction unit can perform more appropriate reduction by optimizing cooperation with delivery companies by taking into account the geographical location information.

[0052] The reduction unit can analyze the user's social media activity and suggest related burden reduction methods. For example, the reduction unit can prioritize suggesting trending products that the user is talking about on social media. For example, the reduction unit can prioritize suggesting gifts introduced by influencers that the user follows. For example, the reduction unit can prioritize suggesting gifts that are popular in online communities in which the user participates. For example, the reduction unit analyzes the user's social media activity to analyze the social media activity and suggest related burden reduction methods. In this way, the reduction unit can suggest more appropriate burden reduction methods by analyzing the social media activity.

[0053] The revitalization department can contribute to the promotion of local industries by suggesting local specialty products and handmade gifts. The revitalization department can, for example, suggest local specialty products and promote local industries. The revitalization department can, for example, suggest local handmade products and promote local industries. The revitalization department can, for example, suggest gifts related to local events and promote local industries. The revitalization department can, for example, suggest local specialty products and handmade crafts. The revitalization department can, for example, contribute to the promotion of local industries by suggesting local specialty products and handmade gifts. In this way, the revitalization department can contribute to the promotion of local industries by suggesting local specialty products and handmade gifts.

[0054] The revitalization department can analyze regional economic data and select the optimal revitalization method. For example, the revitalization department can analyze regional economic data and select a method to promote sales of local specialty products. For example, the revitalization department can analyze regional economic data and select a method to promote sales of handmade products. For example, the revitalization department can analyze regional economic data and select a method to promote sales of event-related gifts. For example, the revitalization department analyzes regional economic data to select the optimal revitalization method. In this way, the revitalization department can select a more appropriate revitalization method by analyzing regional economic data.

[0055] The activation unit can prioritize region-specific gifts by taking into account the user's geographical location information. For example, if the user lives in Hokkaido, the activation unit can prioritize Hokkaido's specialties. For example, if the user lives in Kyoto, the activation unit can prioritize Kyoto's traditional crafts. For example, if the user lives in Okinawa, the activation unit can prioritize Okinawa's specialties. For example, the activation unit analyzes the user's geographical location information to prioritize region-specific gifts by taking into account the geographical location information. As a result, the activation unit can provide more appropriate gifts by taking into account the geographical location information to suggest region-specific gifts.

[0056] The activation unit can analyze the user's social media activity and suggest methods for revitalizing related local industries. For example, the activation unit can suggest local specialties that the user is talking about on social media. For example, the activation unit can suggest local handmade products introduced by influencers that the user follows. For example, the activation unit can suggest gifts related to local events that are popular in online communities in which the user participates. For example, the activation unit analyzes the user's social media activity to analyze the social media activity and suggest methods for revitalizing related local industries. In this way, the activation unit can suggest more appropriate methods for revitalizing local industries by analyzing the social media activity.

[0057] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0058] The suggestion unit can suggest region-specific gift ideas by taking into account the user's geographical location information. For example, if the user lives in Hokkaido, Hokkaido's specialties can be suggested. If the user lives in Kyoto, Kyoto's traditional crafts can be suggested. If the user lives in Okinawa, Okinawa's specialties can be suggested. In order to suggest region-specific gift ideas by taking into account the geographical location information, the suggestion unit analyzes the user's geographical location information. This allows the suggestion unit to suggest more appropriate gifts by suggesting region-specific gift ideas.

[0059] The selection unit can analyze the user's past gift selection history and select the optimal selection method. For example, it can analyze the trends in gifts the user has selected in the past and suggest similar gifts. It can suggest highly rated gifts based on the ratings of gifts the user has selected in the past. It can suggest gifts in the same price range based on the price range of gifts the user has selected in the past. In order to analyze the gift selection history and select the optimal selection method, the selection unit analyzes the user's past gift selection history. This allows the selection unit to select a more appropriate gift by analyzing the past gift selection history.

[0060] The management unit can analyze the user's social media activity and perform related cost management and schedule management. For example, cost management can be performed according to events that the user is talking about on social media. Schedule management can be performed according to events of influencers that the user follows. Cost and schedule management can be performed according to events of online communities in which the user participates. The management unit analyzes the user's social media activity to perform related cost management and schedule management. This allows the management unit to perform more appropriate management by analyzing social media activity.

[0061] The mitigation unit can analyze the user's past gift purchase history and select the optimal mitigation method. For example, it can analyze trends in gifts purchased by the user in the past and suggest similar gifts. It can suggest highly rated gifts based on ratings of gifts purchased by the user in the past. It can suggest gifts in the same price range based on the price range of gifts purchased by the user in the past. In order to analyze the gift purchase history and select the optimal mitigation method, the user's past gift purchase history is analyzed. As a result, the mitigation unit can select a more appropriate mitigation method by analyzing the past gift purchase history.

[0062] The revitalization department can analyze regional economic data and select the most appropriate revitalization method. For example, it can analyze regional economic data and select a method to promote sales of local specialties. It can analyze regional economic data and select a method to promote sales of handmade products. It can analyze regional economic data and select a method to promote sales of event-related gifts. In order to analyze economic data and select the most appropriate revitalization method, the revitalization department can thereby analyze regional economic data and select a more appropriate revitalization method.

[0063] The processing flow of the first embodiment will be briefly explained below.

[0064] Step 1: The suggestion unit suggests gift ideas based on the user's needs and preferences. For example, the suggestion unit analyzes the user's past purchase history and social media posts to suggest optimal gift ideas. If a user is looking for a gift for a friend's birthday, the unit can suggest optimal gift ideas based on the friend's hobbies and interests. Step 2: The selection unit selects the best gift from the gifts suggested by the suggestion unit. The selection unit may provide options such as personalized messages and gift wrapping. The user can add a special message or custom gift wrapping to the gift they have selected. Step 3: The management department optimizes the costs of purchasing and delivering gifts, providing the best gift within the user's budget. The management department manages the gift delivery schedule and ensures that the gift is delivered on the specified date and time. For example, if a user specifies that they want to deliver a gift on their friend's birthday, the delivery schedule can be adjusted to match that date and time. Step 4: The mitigation unit reduces the burden of purchasing and delivering gifts. For example, the mitigation unit can eliminate the user's effort in selecting a gift and allow them to easily purchase it online. By linking with delivery companies, the delivery status of the gift can be tracked in real time, allowing the user to wait for the gift to arrive with peace of mind. Step 5: The Revitalization Department will propose local specialties and handmade gifts to contribute to the promotion of local industries. For example, proposing local crafts and agricultural products as gifts can revitalize the local economy.

[0065] (Example 2) A gift communication system according to an embodiment of the present invention uses AI to connect people. This gift communication system proposes gift ideas based on a user's needs and preferences, selects personalized gifts, manages costs and schedules, reduces the burden of gift purchasing and delivery, and revitalizes local industries. For example, AI proposes gift ideas based on a user's needs and preferences. If a user is looking for a gift for a friend's birthday, AI suggests optimal gift ideas based on the friend's hobbies and interests. This proposal is made by analyzing the user's past purchase history and social media posts. Next, a personalized gift is selected. AI selects the most suitable gift for the user from the proposed gifts and provides personalized message and wrapping options. For example, the user can add a special message or customize the gift with original wrapping. Furthermore, cost and schedule management are performed. AI optimizes the costs of gift purchase and delivery, providing the optimal gift within the user's budget. It also manages gift delivery schedules to ensure delivery on the specified date and time. For example, if a user requests a gift be delivered to a friend for their birthday, AI adjusts the delivery schedule to match that date and time. It also reduces the burden of purchasing and delivering gifts. AI eliminates the hassle of selecting gifts for users, allowing them to easily purchase online. Furthermore, by linking with delivery companies, it is possible to track the delivery status of gifts in real time, allowing users to wait for their gifts with peace of mind. Finally, it aims to revitalize local industries. AI suggests local specialties and handmade gifts, contributing to the promotion of local industries. For example, suggesting local crafts and agricultural products as gifts can revitalize the local economy. In this way, a gift communication system using AI will create a system that makes buyers, recipients, and makers happy.This allows the gift communication system to suggest gift ideas based on users' needs and preferences, select personalized gifts, manage costs and schedules, reduce the burden of purchasing and delivering gifts, and revitalize local industries.

[0066] A gift communication system according to an embodiment includes a suggestion unit, a selection unit, a management unit, a reduction unit, and an activation unit. The suggestion unit suggests gift ideas based on a user's needs and preferences. For example, the suggestion unit analyzes the user's past purchase history and social media posts to suggest optimal gift ideas. For example, if a user is looking for a gift for a friend's birthday, the suggestion unit can suggest optimal gift ideas based on the friend's hobbies and interests. The selection unit selects an optimal gift from among the gifts suggested by the suggestion unit. For example, the selection unit provides personalized message and wrapping options. For example, the selection unit can add a special message or provide original wrapping to a gift selected by the user. The management unit optimizes costs associated with purchasing and delivering gifts to provide optimal gifts within a user's budget. For example, the management unit can optimize costs associated with purchasing and delivering gifts to provide optimal gifts within a user's budget. The management unit also manages gift delivery schedules to ensure gifts are delivered on the specified date and time. For example, if a user specifies, "I want to deliver a gift to a friend on their birthday," the management unit can adjust the delivery schedule to match that date and time. The reduction unit reduces the burden associated with purchasing and delivering gifts. For example, the reduction unit eliminates the need for a user to select a gift, allowing the user to easily purchase the gift online. For example, the reduction unit can track the delivery status of the gift in real time by coordinating with a delivery company. This allows the user to wait for the gift to arrive with peace of mind. The revitalization unit contributes to the promotion of local industries by suggesting local specialties and handmade gifts. For example, the revitalization unit can revitalize the local economy by suggesting local crafts and agricultural products as gifts. As a result, the gift communication system according to the embodiment can suggest gift ideas based on the user's needs and preferences, select personalized gifts, manage costs and schedules, reduce the burden associated with purchasing and delivering gifts, and revitalize local industries.

[0067] The suggestion unit can analyze the user's past purchase history and social media posts to suggest suitable gift ideas. The suggestion unit can, for example, analyze the user's past purchase history to suggest optimal gift ideas. The suggestion unit can also, for example, analyze the user's social media posts to suggest optimal gift ideas. The suggestion unit can, for example, analyze the types of products the user has purchased in the past and the frequency of purchases to suggest optimal gift ideas. The suggestion unit can, for example, analyze the user's social media posts to suggest optimal gift ideas based on the content and frequency of the posts, the number of likes and comments, etc. In this way, the suggestion unit can suggest more personalized gift ideas by analyzing the user's past purchase history and social media posts.

[0068] The selection unit may provide personalized messages and wrapping options. For example, the selection unit may add a special message to a gift selected by a user. For example, the selection unit may provide original wrapping for a gift selected by a user. For example, the selection unit may provide a message tailored to a user's name or a specific event. For example, the selection unit may select wrapping options such as color, design, and material. In this way, the selection unit may provide personalized messages and wrapping options, allowing the user to select a more special gift.

[0069] The management unit appropriately manages costs for purchasing and delivering gifts, and is able to provide an appropriate gift within the user's budget. The management unit, for example, optimizes the purchase cost of gifts, and is able to provide an optimal gift within the user's budget. The management unit can also optimize delivery costs, and is able to provide an optimal gift within the user's budget. The management unit can also optimize both purchase and delivery costs, and is able to provide an optimal gift within the user's budget. The management unit appropriately manages costs, for example, by using a budget setting method and a cost tracking method. In this way, the management unit can optimize costs, and is able to provide an optimal gift within the user's budget.

[0070] The management unit manages the delivery schedule for the gift and can reliably deliver the gift at the specified date and time. The management unit, for example, adjusts the delivery schedule to match the date and time specified by the user. The management unit, for example, works with a delivery company to reliably deliver the gift at the specified date and time. The management unit, for example, manages the delivery schedule in real time and can reliably deliver the gift at the specified date and time. The management unit manages the delivery schedule, for example, by using a method for setting delivery dates and times and tracking progress. In this way, the management unit manages the delivery schedule and can reliably deliver the gift at the specified date and time.

[0071] The reduction unit can eliminate the effort required for a user to select a gift and enable easy online purchases. For example, the reduction unit can eliminate the effort required for a user to select a gift and enable easy online purchases. For example, the reduction unit can track the delivery status of a gift in real time by cooperating with a delivery company. For example, the reduction unit notifies the user of the delivery status so that the user can wait for the arrival of the gift with peace of mind. For example, the reduction unit can reduce the effort required for online purchases by simplifying online purchases or automating the selection process. In this way, the reduction unit can eliminate the effort required for a user to select a gift and enable easy online purchases.

[0072] The reduction unit can track the delivery status of the gift in real time by cooperating with the delivery company. The reduction unit, for example, tracks the delivery status of the gift in real time by cooperating with the delivery company. The reduction unit can track the delivery status of the gift in real time by using a tracking system, for example. The reduction unit can update delivery status data in real time and notify the user. The reduction unit tracks the delivery status in real time by using, for example, the type of tracking system and the frequency of data updates. In this way, the reduction unit tracks the delivery status in real time, allowing the user to wait for the arrival of the gift with peace of mind.

[0073] The revitalization department can contribute to the promotion of local industries by suggesting local specialty products and handmade gifts. The revitalization department can, for example, suggest local specialty products and promote local industries. The revitalization department can, for example, suggest local handmade products and promote local industries. The revitalization department can, for example, suggest gifts related to local events and promote local industries. The revitalization department can, for example, suggest local specialty products and handmade crafts. The revitalization department can, for example, contribute to the promotion of local industries by suggesting local specialty products and handmade gifts. In this way, the revitalization department can contribute to the promotion of local industries by suggesting local specialty products and handmade gifts.

[0074] The suggestion unit can estimate the user's emotions and suggest gift ideas based on the estimated user's emotions. For example, if the user wants to express gratitude, the suggestion unit can suggest a gift accompanied by a thank-you message. For example, if the user wants to express congratulations, the suggestion unit can suggest a gift accompanied by a congratulatory message. For example, if the user wants to express comfort, the suggestion unit can suggest a gift accompanied by a comforting message. The suggestion unit can estimate the user's emotions using, for example, an emotion estimation algorithm and suggest gift ideas based on the emotions. Emotion estimation is performed using, for example, techniques such as facial expression recognition, voice analysis, and text analysis. As a result, the suggestion unit can suggest more appropriate gifts by suggesting gift ideas based on the user's emotions.

[0075] The suggestion unit can analyze the user's past purchase history and social media posts to suggest gift ideas tailored to specific events or seasons. For example, the suggestion unit can suggest the perfect gift for this year's Christmas by referring to gifts the user purchased for Christmas in the past. For example, the suggestion unit can analyze posts related to Valentine's Day from the user's social media posts to suggest the perfect gift for Valentine's Day. For example, the suggestion unit can suggest the perfect gift for this year's Mother's Day by referring to gifts given on Mother's Day from the user's past purchase history. For example, the suggestion unit analyzes the user's past purchase history and social media posts to suggest gift ideas tailored to specific events or seasons. As a result, the suggestion unit can suggest more appropriate gifts by suggesting gift ideas tailored to specific events or seasons.

[0076] The suggestion unit can suggest gift ideas according to the relationships between the user's family and friends, taking into account the relationships between the family and friends. For example, the suggestion unit can suggest a gift that matches the hobbies of a best friend as a gift the user gives to the best friend. For example, the suggestion unit can suggest a gift that the whole family can enjoy as a gift the user gives to their family. For example, the suggestion unit can suggest a practical gift that can be used at work as a gift the user gives to a colleague. For example, the suggestion unit analyzes the relationships between the family and friends of the user in order to suggest gift ideas according to the relationships, taking into account the relationships between the family and friends. As a result, the suggestion unit can suggest more appropriate gifts by suggesting gift ideas according to the relationships.

[0077] The suggestion unit can estimate the user's emotions and determine the priority of gifts to be suggested based on the estimated user's emotions. For example, if the user feels a strong sense of gratitude, the suggestion unit can preferentially suggest gifts that express gratitude. For example, if the user feels a strong sense of celebration, the suggestion unit can preferentially suggest gifts that express celebratory feelings. For example, if the user feels a strong sense of comfort, the suggestion unit can preferentially suggest gifts that express comfort. The suggestion unit can estimate the user's emotions using, for example, an emotion estimation algorithm and determine the priority of gifts to be suggested based on the emotions. Emotion estimation is performed using, for example, techniques such as facial expression recognition, voice analysis, and text analysis. As a result, the suggestion unit can suggest more appropriate gifts by determining the priority of gifts based on the user's emotions.

[0078] The suggestion unit can suggest region-specific gift ideas by taking into account the user's geographical location information. For example, if the user lives in Hokkaido, the suggestion unit can suggest Hokkaido's specialties. For example, if the user lives in Kyoto, the suggestion unit can suggest Kyoto's traditional crafts. For example, if the user lives in Okinawa, the suggestion unit can suggest Okinawa's specialties. For example, the suggestion unit analyzes the user's geographical location information to suggest region-specific gift ideas by taking into account the geographical location information. This allows the suggestion unit to suggest more appropriate gifts by suggesting region-specific gift ideas.

[0079] The suggestion unit can analyze the user's social media activity and suggest gift ideas based on trends. For example, the suggestion unit can suggest trending products that the user is talking about on social media. For example, the suggestion unit can suggest gifts introduced by influencers that the user follows. For example, the suggestion unit can suggest gifts that are popular in online communities in which the user participates. For example, the suggestion unit analyzes the user's social media activity to analyze the social media activity and suggest gift ideas based on trends. This allows the suggestion unit to suggest more appropriate gifts by suggesting gift ideas based on trends.

[0080] The selection unit may estimate a user's emotion and provide personalized messages and wrapping options based on the estimated user's emotion. For example, if a user wants to express gratitude, the selection unit may suggest wrapping with a thank-you message. For example, if a user wants to express congratulations, the selection unit may suggest wrapping with a congratulatory message. For example, if a user wants to express comfort, the selection unit may suggest wrapping with a comforting message. The selection unit may estimate a user's emotion using, for example, an emotion estimation algorithm, and provide personalized messages and wrapping options based on the emotion. Emotion estimation may be performed using techniques such as facial expression recognition, voice analysis, and text analysis. This allows the selection unit to select a more special gift by providing personalized messages and wrapping options based on the user's emotion.

[0081] The selection unit can analyze the user's past gift selection history and select the optimal selection method. For example, the selection unit can analyze trends in gifts selected by the user in the past and suggest similar gifts. For example, the selection unit can suggest highly rated gifts based on ratings of gifts selected by the user in the past. For example, the selection unit can suggest gifts in the same price range based on the price range of gifts selected by the user in the past. For example, the selection unit analyzes the user's past gift selection history to analyze the gift selection history and select the optimal selection method. In this way, the selection unit can select a more appropriate gift by analyzing the past gift selection history.

[0082] When selecting a gift, the selection unit can perform filtering based on the user's current living situation and areas of interest. For example, if the user has started a new hobby, the selection unit can suggest gifts related to the hobby. For example, if the user has moved, the selection unit can suggest gifts that are suitable for the new residence. For example, if the user has started a new job, the selection unit can suggest gifts related to the job. For example, the selection unit analyzes the user's current living situation and areas of interest to perform filtering based on the user's current living situation and areas of interest. As a result, the selection unit can select a more appropriate gift by filtering based on the user's current living situation and areas of interest.

[0083] The selection unit can estimate the user's emotions and determine the priority of gifts to be selected based on the estimated user's emotions. For example, if the user feels a strong sense of gratitude, the selection unit can preferentially select gifts that express gratitude. For example, if the user feels a strong sense of celebration, the selection unit can preferentially select gifts that express celebratory feelings. For example, if the user feels a strong sense of comfort, the selection unit can preferentially select gifts that express comfort. The selection unit can estimate the user's emotions using, for example, an emotion estimation algorithm and determine the priority of gifts to be selected based on the emotions. Emotion estimation is performed using, for example, techniques such as facial expression recognition, voice analysis, and text analysis. As a result, the selection unit can select more appropriate gifts by determining the priority of gifts based on the user's emotions.

[0084] The selection unit can prioritize region-specific gifts by taking into account the user's geographical location information. For example, if the user lives in Hokkaido, the selection unit can prioritize Hokkaido's specialty products. For example, if the user lives in Kyoto, the selection unit can prioritize Kyoto's traditional crafts. For example, if the user lives in Okinawa, the selection unit can prioritize Okinawa's specialty products. For example, the selection unit analyzes the user's geographical location information to prioritize region-specific gifts by taking into account the geographical location information. As a result, the selection unit can select a more appropriate gift by prioritized region-specific gifts.

[0085] The selection unit can analyze the user's social media activity and select a relevant gift. For example, the selection unit can select trending products that the user is talking about on social media. For example, the selection unit can select gifts introduced by influencers that the user follows. For example, the selection unit can select gifts that are popular in online communities in which the user participates. For example, the selection unit analyzes the user's social media activity to analyze the social media activity and select a relevant gift. In this way, the selection unit can select a more appropriate gift by analyzing the social media activity.

[0086] The management unit can estimate the user's emotions and perform cost management and schedule management based on the estimated user emotions. For example, if the user is concerned about the budget, the management unit can optimize costs and provide a gift within the budget. For example, if the user is in a hurry, the management unit can adjust the schedule and deliver the gift quickly. For example, if the user is relaxed, the management unit can deliver the gift with ample time to spare. The management unit can estimate the user's emotions using, for example, an emotion estimation algorithm, and perform cost management and schedule management based on the emotions. Emotion estimation is performed using, for example, technologies such as facial expression recognition, voice analysis, and text analysis. This allows the management unit to perform more appropriate cost management and schedule management based on the user's emotions.

[0087] The management unit can optimize costs for purchasing and delivering gifts to provide an optimal gift within the user's budget. The management unit, for example, can optimize the cost of purchasing gifts to provide an optimal gift within the user's budget. The management unit, for example, can optimize the delivery cost to provide an optimal gift within the user's budget. The management unit, for example, can optimize both the costs of purchasing and delivery to provide an optimal gift within the user's budget. The management unit optimizes costs, for example, by using a budget setting or a cost tracking method. In this way, the management unit can optimize costs to provide an optimal gift within the user's budget.

[0088] The management unit manages the delivery schedule for the gift and can reliably deliver the gift at the specified date and time. The management unit, for example, adjusts the delivery schedule to match the date and time specified by the user. The management unit, for example, works with a delivery company to reliably deliver the gift at the specified date and time. The management unit, for example, manages the delivery schedule in real time and can reliably deliver the gift at the specified date and time. The management unit manages the delivery schedule, for example, by using a method for setting delivery dates and times and tracking progress. In this way, the management unit manages the delivery schedule and can reliably deliver the gift at the specified date and time.

[0089] The management unit can estimate the user's emotions and determine the priority of cost management based on the estimated user emotions. For example, when the user is concerned about the budget, the management unit can prioritize cost management. For example, when the user is in a hurry, the management unit can prioritize schedule management. For example, when the user is relaxed, the management unit can balance cost and schedule. For example, the management unit can estimate the user's emotions using an emotion estimation algorithm and determine the priority of cost management based on the emotions. Emotion estimation is performed using technologies such as facial expression recognition, voice analysis, and text analysis. This allows the management unit to perform more appropriate management by determining the priority of cost management based on the user's emotions.

[0090] The management unit can optimize the delivery schedule by taking into account the geographical location information of the user. For example, if the user lives in Hokkaido, the management unit can optimize the delivery schedule within Hokkaido. For example, if the user lives in Kyoto, the management unit can optimize the delivery schedule within Kyoto. For example, if the user lives in Okinawa, the management unit can optimize the delivery schedule within Okinawa. For example, the management unit analyzes the geographical location information of the user to optimize the delivery schedule by taking into account the geographical location information. This allows the management unit to perform more appropriate management by optimizing the delivery schedule by taking into account the geographical location information.

[0091] The management unit can analyze the user's social media activity and perform related cost management and schedule management. For example, the management unit can perform cost management based on events that the user is talking about on social media. For example, the management unit can perform schedule management based on events of influencers that the user follows. For example, the management unit can manage costs and schedules based on events of online communities in which the user participates. For example, the management unit analyzes the user's social media activity to analyze the social media activity and perform related cost management and schedule management. This allows the management unit to perform more appropriate management by analyzing the social media activity.

[0092] The reduction unit can estimate a user's emotions and reduce the effort required for selecting and purchasing a gift based on the estimated user's emotions. For example, when the user is feeling stressed, the reduction unit can provide a simple interface and minimize the selection procedure. For example, when the user is relaxed, the reduction unit can provide detailed selection options and suggest a customizable selection method. For example, when the user is in a hurry, the reduction unit can prioritize voice input to enable the user to quickly select a gift. The reduction unit can estimate a user's emotions using, for example, an emotion estimation algorithm and reduce the effort required for selecting and purchasing a gift based on the emotion. Emotion estimation is performed using technologies such as facial expression recognition, voice analysis, and text analysis. As a result, the reduction unit can reduce the effort required for selecting and purchasing a gift based on the user's emotions, thereby providing a more appropriate gift.

[0093] The reduction unit can analyze the user's past gift purchase history and select the optimal reduction method. For example, the reduction unit can analyze trends in gifts purchased by the user in the past and suggest similar gifts. For example, the reduction unit can suggest highly rated gifts based on ratings of gifts purchased by the user in the past. For example, the reduction unit can suggest gifts in the same price range based on the price range of gifts purchased by the user in the past. For example, the reduction unit analyzes the user's past gift purchase history to analyze the gift purchase history and select the optimal reduction method. In this way, the reduction unit can select a more appropriate reduction method by analyzing the past gift purchase history.

[0094] The reduction unit can reduce the burden of purchasing and delivering gifts, making it easier to purchase online. For example, the reduction unit can eliminate the effort of selecting a gift, making it easier to purchase online. For example, the reduction unit can track the delivery status of the gift in real time by cooperating with a delivery company. For example, the reduction unit notifies the user of the delivery status so that the user can wait for the arrival of the gift with peace of mind. For example, the reduction unit simplifies online purchases and automates the selection process to reduce the burden. In this way, the reduction unit can reduce the burden of purchasing and delivering gifts, making it easier to purchase online.

[0095] The reduction unit can estimate the user's emotions and determine the priority of the burden to be reduced based on the estimated user emotions. For example, if the user is feeling stressed, the reduction unit can prioritize simplifying the selection procedure. For example, if the user is relaxed, the reduction unit can prioritize providing detailed selection options. For example, if the user is in a hurry, the reduction unit can prioritize quick selection and purchase. For example, the reduction unit can estimate the user's emotions using an emotion estimation algorithm and determine the priority of the burden to be reduced based on the emotions. Emotion estimation is performed using technologies such as facial expression recognition, voice analysis, and text analysis. This allows the reduction unit to perform more appropriate reduction by determining the priority of the burden to be reduced based on the user's emotions.

[0096] The reduction unit can optimize cooperation with delivery companies by taking into account the geographical location information of the user. For example, if the user lives in Hokkaido, the reduction unit can optimize cooperation with delivery companies in Hokkaido. For example, if the user lives in Kyoto, the reduction unit can optimize cooperation with delivery companies in Kyoto. For example, if the user lives in Okinawa, the reduction unit can optimize cooperation with delivery companies in Okinawa. For example, the reduction unit analyzes the geographical location information of the user to optimize cooperation with delivery companies by taking into account the geographical location information. As a result, the reduction unit can perform more appropriate reduction by optimizing cooperation with delivery companies by taking into account the geographical location information.

[0097] The reduction unit can analyze the user's social media activity and suggest related burden reduction methods. For example, the reduction unit can prioritize suggesting trending products that the user is talking about on social media. For example, the reduction unit can prioritize suggesting gifts introduced by influencers that the user follows. For example, the reduction unit can prioritize suggesting gifts that are popular in online communities in which the user participates. For example, the reduction unit analyzes the user's social media activity to analyze the social media activity and suggest related burden reduction methods. In this way, the reduction unit can suggest more appropriate burden reduction methods by analyzing the social media activity.

[0098] The activation unit can estimate the user's emotions and suggest gifts that will revitalize local industries based on the estimated user emotions. For example, if the user is interested in local specialty products, the activation unit can suggest those specialty products. For example, if the user is interested in local handmade products, the activation unit can suggest those handmade products. For example, if the user is interested in a local event, the activation unit can suggest gifts related to the event. For example, the activation unit can estimate the user's emotions using an emotion estimation algorithm and suggest gifts that will revitalize local industries based on the emotions. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and text analysis. As a result, the activation unit can provide more appropriate gifts by suggesting gifts that will revitalize local industries based on the user's emotions.

[0099] The revitalization department can contribute to the promotion of local industries by suggesting local specialty products and handmade gifts. The revitalization department can, for example, suggest local specialty products and promote local industries. The revitalization department can, for example, suggest local handmade products and promote local industries. The revitalization department can, for example, suggest gifts related to local events and promote local industries. The revitalization department can, for example, suggest local specialty products and handmade crafts. The revitalization department can, for example, contribute to the promotion of local industries by suggesting local specialty products and handmade gifts. In this way, the revitalization department can contribute to the promotion of local industries by suggesting local specialty products and handmade gifts.

[0100] The revitalization department can analyze regional economic data and select the optimal revitalization method. For example, the revitalization department can analyze regional economic data and select a method to promote sales of local specialty products. For example, the revitalization department can analyze regional economic data and select a method to promote sales of handmade products. For example, the revitalization department can analyze regional economic data and select a method to promote sales of event-related gifts. For example, the revitalization department analyzes regional economic data to select the optimal revitalization method. In this way, the revitalization department can select a more appropriate revitalization method by analyzing regional economic data.

[0101] The activation unit can estimate the user's emotions and determine the priority of local industries to be activated based on the estimated user emotions. For example, if the user has a strong interest in a particular region, the activation unit can prioritize activating industries in that region. For example, if the user has a strong interest in a particular local specialty, the activation unit can prioritize activating that local specialty. For example, if the user has a strong interest in a particular event, the activation unit can prioritize activating industries related to the event. For example, the activation unit can estimate the user's emotions using an emotion estimation algorithm and determine the priority of local industries to be activated based on the emotions. Emotion estimation is performed using technologies such as facial expression recognition, voice analysis, and text analysis. This allows the activation unit to prioritize local industries based on the user's emotions, thereby enabling more appropriate activation.

[0102] The activation unit can prioritize region-specific gifts by taking into account the user's geographical location information. For example, if the user lives in Hokkaido, the activation unit can prioritize Hokkaido's specialties. For example, if the user lives in Kyoto, the activation unit can prioritize Kyoto's traditional crafts. For example, if the user lives in Okinawa, the activation unit can prioritize Okinawa's specialties. For example, the activation unit analyzes the user's geographical location information to prioritize region-specific gifts by taking into account the geographical location information. As a result, the activation unit can provide more appropriate gifts by taking into account the geographical location information to suggest region-specific gifts.

[0103] The activation unit can analyze the user's social media activity and suggest methods for revitalizing related local industries. For example, the activation unit can suggest local specialties that the user is talking about on social media. For example, the activation unit can suggest local handmade products introduced by influencers that the user follows. For example, the activation unit can suggest gifts related to local events that are popular in online communities in which the user participates. For example, the activation unit analyzes the user's social media activity to analyze the social media activity and suggest methods for revitalizing related local industries. In this way, the activation unit can suggest more appropriate methods for revitalizing local industries by analyzing the social media activity. === Hard Collateral 1-1 === Each of the multiple elements, including the suggestion unit, selection unit, management unit, reduction unit, and activation unit, is implemented, for example, by at least one of the smart device 14 and the data processing device 12. For example, the suggestion unit is implemented by the control unit 46A of the smart device 14 and analyzes the user's past purchase history and social media posts to suggest gift ideas. The selection unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and selects the most suitable gift from the suggested gifts and provides personalized message and wrapping options. The management unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and optimizes the costs associated with purchasing and delivering gifts and manages delivery schedules. The reduction unit is implemented, for example, by the control unit 46A of the smart device 14 and eliminates the user's effort in selecting gifts, allowing them to easily purchase them online. The activation unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and suggests local specialties and handmade gifts. === Hard Collateral 1-2 === Each of the multiple elements, including the suggestion unit, selection unit, management unit, reduction unit, and activation unit, is implemented, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the suggestion unit is implemented by the control unit 46A of the smart glasses 214 and analyzes the user's past purchase history and social media posts to suggest gift ideas. The selection unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and selects the most suitable gift from the suggested gifts and provides personalized message and wrapping options. The management unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and optimizes the costs associated with purchasing and delivering gifts and manages delivery schedules. The reduction unit is implemented, for example, by the control unit 46A of the smart glasses 214 and saves the user the trouble of selecting a gift, allowing them to easily purchase gifts online. The activation unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and suggests local specialties and handmade gifts. === Hard Collateral 1-3 === Each of the multiple elements, including the suggestion unit, selection unit, management unit, reduction unit, and activation unit, is implemented, for example, by at least one of the headset terminal 314 and the data processing device 12. For example, the suggestion unit is implemented by the control unit 46A of the headset terminal 314 and analyzes the user's past purchase history and social media posts to suggest gift ideas. The selection unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and selects the most suitable gift from the suggested gifts and provides personalized message and wrapping options. The management unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and optimizes the costs associated with purchasing and delivering gifts and manages delivery schedules. The reduction unit is implemented, for example, by the control unit 46A of the headset terminal 314 and saves the user the trouble of selecting a gift, allowing them to easily purchase gifts online. The activation unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and suggests local specialties and handmade gifts. === Hard Collateral 1-4 === Each of the multiple elements, including the suggestion unit, selection unit, management unit, reduction unit, and activation unit, is implemented, for example, by at least one of the robot 414 and the data processing device 12. For example, the suggestion unit is implemented by the control unit 46A of the robot 414 and analyzes the user's past purchase history and social media posts to suggest gift ideas. The selection unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and selects the most suitable gift from the suggested gifts and provides personalized message and wrapping options. The management unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and optimizes the costs associated with purchasing and delivering gifts and manages delivery schedules. The reduction unit is implemented, for example, by the control unit 46A of the robot 414 and saves the user the trouble of selecting a gift, allowing them to easily purchase it online. The activation unit is implemented, for example, by the specific processing unit 290 of the data processing device 12 and suggests local specialties and handmade gifts.

[0104] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0105] The suggestion unit can estimate the user's emotions and suggest gift ideas based on the estimated user's emotions. For example, if the user wants to express gratitude, a gift accompanied by a thank-you message can be suggested. If the user wants to express congratulations, a gift accompanied by a congratulatory message can be suggested. If the user wants to express comfort, a gift accompanied by a comforting message can be suggested. An emotion estimation algorithm is used to estimate the user's emotions and suggest gift ideas based on the emotions. Emotion estimation is performed using techniques such as facial expression recognition, voice analysis, and text analysis. This allows the suggestion unit to suggest more appropriate gifts by suggesting gift ideas based on the user's emotions.

[0106] The selection unit can estimate the user's emotions and provide personalized messages and wrapping options based on the estimated user's emotions. For example, if the user wants to express gratitude, wrapping with a thank-you message can be suggested. If the user wants to express congratulations, wrapping with a congratulatory message can be suggested. If the user wants to express comfort, wrapping with a comforting message can be suggested. An emotion estimation algorithm is used to estimate the user's emotions and provide personalized messages and wrapping options based on the emotions. Emotion estimation is performed using techniques such as facial expression recognition, voice analysis, and text analysis. This allows the selection unit to select a more special gift by providing personalized messages and wrapping options based on the user's emotions.

[0107] The management unit can estimate the user's emotions and perform cost management and schedule management based on the estimated user emotions. For example, if the user is concerned about the budget, costs can be optimized to provide a gift within the budget. If the user is in a hurry, the schedule can be adjusted to deliver the gift quickly. If the user is relaxed, the gift can be delivered with ample time to spare. An emotion estimation algorithm is used to estimate the user's emotions and perform cost management and schedule management based on the emotions. Emotion estimation is performed using technologies such as facial expression recognition, voice analysis, and text analysis. This allows the management unit to perform more appropriate cost management and schedule management by managing the user's emotions.

[0108] The mitigation unit can estimate a user's emotions and reduce the effort required for selecting and purchasing a gift based on the estimated user's emotions. For example, if the user is feeling stressed, a simple interface can be provided to minimize the selection steps. If the user is relaxed, detailed selection options can be provided and a customizable selection method can be suggested. If the user is in a hurry, voice input can be prioritized to enable quick gift selection. The emotion estimation algorithm is used to estimate a user's emotions and reduce the effort required for selecting and purchasing a gift based on the emotions. Emotion estimation is performed using technologies such as facial expression recognition, voice analysis, and text analysis. As a result, the mitigation unit can provide a more appropriate gift by reducing the effort required for selecting and purchasing a gift based on the user's emotions.

[0109] The activation unit can estimate the user's emotions and suggest gifts that will revitalize local industries based on the estimated user emotions. For example, if the user is interested in local specialty products, those specialty products can be suggested. If the user is interested in local handmade products, those handmade products can be suggested. If the user is interested in local events, gifts related to those events can be suggested. The activation unit uses an emotion estimation algorithm to estimate the user's emotions and suggests gifts that will revitalize local industries based on those emotions. Emotion estimation is performed using technologies such as facial expression recognition, voice analysis, and text analysis. As a result, the activation unit can provide more appropriate gifts by suggesting gifts that will revitalize local industries based on the user's emotions.

[0110] The suggestion unit can suggest region-specific gift ideas by taking into account the user's geographical location information. For example, if the user lives in Hokkaido, Hokkaido's specialties can be suggested. If the user lives in Kyoto, Kyoto's traditional crafts can be suggested. If the user lives in Okinawa, Okinawa's specialties can be suggested. In order to suggest region-specific gift ideas by taking into account the geographical location information, the suggestion unit analyzes the user's geographical location information. This allows the suggestion unit to suggest more appropriate gifts by suggesting region-specific gift ideas.

[0111] The selection unit can analyze the user's past gift selection history and select the optimal selection method. For example, it can analyze the trends in gifts the user has selected in the past and suggest similar gifts. It can suggest highly rated gifts based on the ratings of gifts the user has selected in the past. It can suggest gifts in the same price range based on the price range of gifts the user has selected in the past. In order to analyze the gift selection history and select the optimal selection method, the selection unit analyzes the user's past gift selection history. This allows the selection unit to select a more appropriate gift by analyzing the past gift selection history.

[0112] The management unit can analyze the user's social media activity and perform related cost management and schedule management. For example, cost management can be performed according to events that the user is talking about on social media. Schedule management can be performed according to events of influencers that the user follows. Cost and schedule management can be performed according to events of online communities in which the user participates. The management unit analyzes the user's social media activity to perform related cost management and schedule management. This allows the management unit to perform more appropriate management by analyzing social media activity.

[0113] The mitigation unit can analyze the user's past gift purchase history and select the optimal mitigation method. For example, it can analyze trends in gifts purchased by the user in the past and suggest similar gifts. It can suggest highly rated gifts based on ratings of gifts purchased by the user in the past. It can suggest gifts in the same price range based on the price range of gifts purchased by the user in the past. In order to analyze the gift purchase history and select the optimal mitigation method, the user's past gift purchase history is analyzed. As a result, the mitigation unit can select a more appropriate mitigation method by analyzing the past gift purchase history.

[0114] The revitalization department can analyze regional economic data and select the most appropriate revitalization method. For example, it can analyze regional economic data and select a method to promote sales of local specialties. It can analyze regional economic data and select a method to promote sales of handmade products. It can analyze regional economic data and select a method to promote sales of event-related gifts. In order to analyze economic data and select the most appropriate revitalization method, the revitalization department can thereby analyze regional economic data and select a more appropriate revitalization method.

[0115] The processing flow of the second embodiment will be briefly explained below.

[0116] Step 1: The suggestion unit suggests gift ideas based on the user's needs and preferences. For example, the suggestion unit analyzes the user's past purchase history and social media posts to suggest optimal gift ideas. If a user is looking for a gift for a friend's birthday, the unit can suggest optimal gift ideas based on the friend's hobbies and interests. Step 2: The selection unit selects the most suitable gift from the gifts suggested by the suggestion unit. The selection unit may provide options such as personalized messages and gift wrapping. The user can add a special message or original gift wrapping to the gift they have selected. Step 3: The management department optimizes the costs of purchasing and delivering gifts, providing the best gift within the user's budget. The management department manages the gift delivery schedule and ensures that the gift is delivered on the specified date and time. For example, if a user specifies that they want to deliver a gift on their friend's birthday, the delivery schedule can be adjusted to match that date and time. Step 4: The mitigation unit reduces the burden of purchasing and delivering gifts. For example, the mitigation unit can eliminate the user's effort in selecting a gift and allow them to easily purchase it online. By linking with delivery companies, the delivery status of the gift can be tracked in real time, allowing the user to wait for the gift to arrive with peace of mind. Step 5: The Revitalization Department will propose local specialties and handmade gifts to contribute to the promotion of local industries. For example, proposing local crafts and agricultural products as gifts can revitalize the local economy.

[0117] 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.

[0118] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of the generative AI include a neural network (NN) and a neural network (NN). The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, image data, etc. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and may perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-mentioned parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. The processing performed by an AI including the generative AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI including the generative AI.

[0119] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

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

[0121] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0122] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0123] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0124] The 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.

[0125] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0126] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0127] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0128] Fig. 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.

[0129] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0130] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0131] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0132] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0133] The specific processing unit 290 transmits the result of the specific processing to the 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.

[0134] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0135] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

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

[0137] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0138] 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.

[0139] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0140] The 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.

[0141] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0142] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0143] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0144] 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.

[0145] 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.

[0146] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0147] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0148] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0149] 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.

[0150] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0151] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0152] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0153] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0154] 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.

[0155] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0156] 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.

[0157] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0158] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0159] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0160] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0161] 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.

[0162] 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.

[0163] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0164] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0165] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0166] 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.

[0167] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0168] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0169] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0170] 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.

[0171] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0172] 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.

[0173] 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).

[0174] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0175] 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."

[0176] 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.

[0177] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0178] 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.

[0179] 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.

[0180] 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.

[0181] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0182] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0183] 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.

[0184] 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.

[0185] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0186] 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.

[0187] 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.

[0188] [Explanation of symbols]

[0189] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A system comprising: a proposal unit that proposes gift ideas based on a user's needs and preferences; a selection unit that selects appropriate gifts from among those proposed by the proposal unit; a management unit that performs cost management and schedule management for the gifts selected by the selection unit; a reduction unit that reduces the burden of purchasing and delivering gifts managed by the management unit; and an activation unit that aims to revitalize local industries through the purchase and delivery of gifts reduced by the reduction unit.

2. The system according to claim 1, wherein the suggestion unit analyzes the user's past purchase history and social media posts to suggest appropriate gift ideas.

3. The selection unit Offer personalized messages and gift wrapping options 2. The system of claim 1.

4. 2. The system according to claim 1, wherein the management unit appropriately manages costs for purchasing and delivering gifts, and provides appropriate gifts within the user's budget.

5. The management unit Manage gift delivery schedules and ensure delivery on time 2. The system of claim 1.

6. The lightening portion is Eliminate the hassle of choosing gifts and make buying online easier 2. The system of claim 1.

7. The lightening portion is Integrate with delivery companies to track your gift delivery in real time 2. The system of claim 1.

8. The activation unit is Providing local specialties and handmade gifts, contributing to the promotion of local industries 2. The system of claim 1.

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