system

Abstract

An object of the system according to the embodiment is to propose a personal computer configuration optimal for the needs of a user without expert knowledge.SOLUTION: A system according to an embodiment includes a needs collection unit, an analysis unit, a proposal unit, a customization unit, and an estimation unit. The needs collection unit collects needs of a user. The analysis unit analyzes the needs collected by the need collection unit. The proposal unit proposes an optimum PC configuration based on the need analyzed by the analysis unit. The customizing section provides customization options based on the personal computer configuration proposed by the proposing section. The estimating unit calculates an estimated amount based on the customization option provided by the customizing unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology requires specialized knowledge for users to select the PC configuration that best suits their needs, which can be a barrier to purchasing.

[0005] The system according to the embodiment aims to propose a PC configuration that is optimal for the user's needs, even if the user does not have specialized knowledge. [Means for solving the problem]

[0006] The system according to the embodiment includes a needs collection unit, an analysis unit, a proposal unit, a customization unit, and an estimation unit. The needs collection unit collects user needs. The analysis unit analyzes the needs collected by the needs collection unit. The proposal unit proposes an optimal PC configuration based on the needs analyzed by the analysis unit. The customization unit provides customization options based on the PC configuration proposed by the proposal unit. The estimation unit calculates an estimated cost based on the customization options provided by the customization unit. [Effects of the Invention]

[0007] The system according to the embodiment can propose a PC configuration that is optimal for the user's needs, even if the user does not have specialized knowledge. [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) The BTO PC purchase support system according to an embodiment of the present invention is a system in which a generation AI provides appropriate advice and suggestions so that users can easily select and purchase a PC that meets their needs. As a result, the BTO PC purchase support system allows users to easily select and purchase a PC that meets their needs even without specialized knowledge.

[0029] A BTO PC purchase support system according to an embodiment includes a needs collection unit, an analysis unit, a proposal unit, a customization unit, and an estimate unit. The needs collection unit collects user needs. For example, a user may input requests such as "I want a PC for gaming" or "I need a high-performance PC for work." The analysis unit analyzes the collected needs. For example, a generation AI analyzes the user's input information and understands the needs. The proposal unit proposes an optimal PC configuration based on the analyzed needs. For example, a user looking for a PC for gaming may be suggested a configuration equipped with a high-performance graphics card and large memory capacity. The customization unit provides customization options based on the proposed PC configuration. For example, if a user wants to increase storage capacity or use a specific brand of parts, the generation AI presents corresponding customization options. The estimate unit calculates an estimated price based on the provided customization options. For example, the estimate after customization may be automatically calculated and presented to the user. This allows users to easily select and purchase a PC that meets their needs, even without specialized knowledge.

[0030] The needs gathering unit can analyze the user's past purchase history and usage history to predict future needs. The needs gathering unit, for example, analyzes the user's past purchase history to predict future needs. For example, the needs gathering unit predicts the next required PC specifications based on the specifications and purpose of use of PCs purchased in the past. The needs gathering unit also analyzes the user's past usage history to predict future needs. For example, the needs gathering unit predicts the next required PC specifications based on data on software and applications used in the past. The needs gathering unit also analyzes the user's past purchase history and usage history to predict future needs. For example, the needs gathering unit predicts the next required PC specifications based on the frequency and duration of use of PCs purchased in the past. This makes it possible to predict the user's future needs and make more appropriate suggestions.

[0031] The needs gathering unit can make more personalized suggestions by taking into account the user's lifestyle and hobbies and preferences. The needs gathering unit, for example, takes into account the user's lifestyle, and the generation AI makes personalized suggestions. For example, if the user likes the outdoors, the generation AI will suggest a lightweight computer that is easy to carry. The needs gathering unit also takes into account the user's hobbies and preferences, and the generation AI will make personalized suggestions. For example, if the user's hobby is music production, the generation AI will suggest a computer with a high-performance audio interface. The needs gathering unit also takes into account the user's lifestyle and hobbies and preferences, and the generation AI will make personalized suggestions. For example, if the user's hobby is photography, the generation AI will suggest a computer with a large capacity storage device. This makes it possible to make suggestions that meet the individual needs of the user.

[0032] The needs gathering unit can collect a wider variety of information using voice input or image input. For example, the needs gathering unit allows the user to input their needs using voice input, and the generation AI analyzes the voice data. For example, if a user voice-inputs, "I want a PC for gaming," the voice data is analyzed to understand their needs. The needs gathering unit also allows the user to input their needs using image input, and the generation AI analyzes the image data. For example, if a user uploads an image of the PC they want, the image data is analyzed to understand their needs. The needs gathering unit also allows the user to input their needs using voice input or image input, and the generation AI analyzes the data. For example, if a user voice-inputs, "I need a high-performance PC for work," and uploads an image of the PC they want, the data is analyzed to understand their needs. This makes it possible to collect a wider variety of information using voice and images.

[0033] The needs gathering unit can compare the needs of users of different age groups and regions, and analyze the region-specific needs. For example, the needs gathering unit compares the needs of users of different age groups, and the generation AI analyzes the region-specific needs. For example, the needs of young users and elderly users are compared, and the region-specific needs of each are understood. The needs gathering unit also compares the needs of users of different regions, and the generation AI analyzes the region-specific needs. For example, the needs of users in urban areas and rural areas are compared, and the region-specific needs of each are understood. The needs gathering unit also compares the needs of users of different age groups and regions, and the generation AI analyzes the region-specific needs. For example, the needs of young urban users and elderly rural users are compared, and the region-specific needs of each are understood. This makes it possible to analyze region-specific needs and make more appropriate suggestions.

[0034] The suggestion unit can reflect the latest technological trends and market trends in the proposed PC configuration. For example, the suggestion unit reflects the latest technological trends in the PC configuration proposed by the generation AI. For example, it may propose a configuration equipped with the latest graphics cards and processors. The suggestion unit also reflects market trends in the proposed PC configuration. For example, it may propose a configuration using currently popular parts and brands. The suggestion unit also reflects the latest technological trends and market trends in the PC configuration proposed by the generation AI. For example, it may propose a configuration using parts that incorporate the latest technology or parts that are in high demand in the current market. This makes it possible to make proposals that reflect the latest technological trends and market trends.

[0035] The proposal unit can generate multiple configuration proposals based on the user's needs and compare the advantages and disadvantages of each. For example, the proposal unit uses a generation AI to generate multiple PC configuration proposals based on the user's needs and compare the advantages and disadvantages of each. For example, a performance-oriented configuration is compared with a cost-oriented configuration. The proposal unit also uses a generation AI to generate multiple PC configuration proposals based on the user's needs and compare the advantages and disadvantages of each. For example, a configuration equipped with a high-performance graphics card is compared with a configuration equipped with large-capacity storage. The proposal unit also uses a generation AI to generate multiple PC configuration proposals based on the user's needs and compare the advantages and disadvantages of each. For example, a configuration incorporating the latest technology is compared with a configuration offering excellent cost performance. This allows the proposal unit to compare multiple configuration proposals and make the optimal proposal.

[0036] The suggestion unit can propose computer configurations according to different uses. For example, the generation AI in the suggestion unit proposes computer configurations according to different uses. For example, it proposes a configuration equipped with a high-performance graphics card and large-capacity memory for a computer used for design. The suggestion unit also proposes computer configurations according to different uses. For example, it proposes a configuration equipped with a high-speed processor and large-capacity storage for a computer used for programming. The suggestion unit also proposes computer configurations according to different uses. For example, it proposes a configuration equipped with a high-performance audio interface and a large-screen display for a computer used for entertainment. This makes it possible to propose optimal configurations according to different uses.

[0037] The suggestion unit can add an option to use eco-friendly parts or recyclable materials to the proposed computer configuration. For example, the suggestion unit adds an option to use eco-friendly parts to the computer configuration proposed by the generation AI. For example, it suggests a low-power processor or parts made from recyclable materials. The suggestion unit also adds an option to use recyclable materials to the proposed computer configuration. For example, it suggests parts made from recycled plastic or recycled aluminum. The suggestion unit also adds an option to use eco-friendly parts or recyclable materials to the computer configuration proposed by the generation AI. For example, it suggests parts that have undergone an environmentally friendly manufacturing process. This makes it possible to make environmentally friendly suggestions.

[0038] The customization unit can dynamically adjust the options of customization options according to the user's budget and intended use. For example, the customization unit dynamically adjusts the options of customization options according to the user's budget. For example, the customization unit selects optimal parts within the budget set by the user and presents customization options. The customization unit also dynamically adjusts the options of customization options according to the user's intended use. For example, if the user wants a PC for gaming, the customization unit presents options equipped with a high-performance graphics card and large-capacity memory. The customization unit also dynamically adjusts the options of customization options according to the user's budget and intended use. For example, if the user wants a high-performance PC for work, the customization unit presents options equipped with a high-speed processor and large-capacity storage. This enables customization according to the user's budget and intended use.

[0039] The customization unit can propose a discount to the estimated price after customization, taking into consideration the user's ability to pay and past purchase history. The customization unit, for example, proposes a discount to the estimated price after customization, taking into consideration the user's ability to pay. For example, the customization unit applies an optimal discount within the budget set by the user and presents the estimated price. The customization unit also proposes a discount to the estimated price after customization, taking into consideration the user's past purchase history. For example, a repeat customer discount is applied to a user who has purchased parts of the same brand in the past. The customization unit also proposes a discount to the estimated price after customization, taking into consideration the user's ability to pay and past purchase history. For example, if the user has purchased an expensive computer in the past, a special discount is applied. This makes it possible to propose a discount based on the user's ability to pay and past purchase history.

[0040] The customization unit can provide a function that allows a user to add parts and accessories that the user has designed himself to the customization options. The customization unit, for example, provides a function that allows a user to add parts that the user has designed himself to the customization options. For example, it provides an option to incorporate a case or keyboard that the user has designed into the personal computer. The customization unit also provides a function that allows a user to add accessories that the user has designed himself to the customization options. For example, it provides an option to attach stickers or decals that the user has designed to the personal computer. The customization unit also provides a function that allows a user to add parts and accessories that the user has designed himself to the customization options. For example, it provides an option to incorporate a custom fan or LED light that the user has designed into the personal computer. This enables customization that allows a user to add parts and accessories that the user has designed himself to the customization options.

[0041] The estimating unit can accommodate different currencies and payment methods for the estimated amount to accommodate international users. The estimating unit, for example, accommodates different currencies for the estimated amount to accommodate international users. For example, the estimated amount is displayed in a currency selected by the user. The estimating unit also accommodates different payment methods for the estimated amount to accommodate international users. For example, payment methods such as credit card, electronic money, and bank transfer can be selected. The estimating unit also accommodates different currencies and payment methods for the estimated amount to accommodate international users. For example, the estimated amount is displayed in the currency and payment method selected by the user to allow the payment procedure to proceed smoothly. This makes it possible to provide an estimate that accommodates international users.

[0042] The purchase procedure unit can provide a personalized guide for each step of the purchase procedure based on the user's past purchase history and preferences. The purchase procedure unit, for example, provides a personalized guide for each step of the purchase procedure based on the user's past purchase history. For example, the purchase procedure unit suggests the optimal procedure based on the specifications and intended use of computers purchased in the past. The purchase procedure unit also provides a personalized guide for each step of the purchase procedure based on the user's preferences. For example, the purchase procedure unit suggests the optimal procedure based on the user's preferred brands and parts. The purchase procedure unit also provides a personalized guide for each step of the purchase procedure based on the user's past purchase history and preferences. For example, the purchase procedure unit suggests the optimal procedure based on the frequency of use and intended use of computers purchased in the past. In this way, a personalized guide can be provided based on the user's past purchase history and preferences.

[0043] The purchase checkout unit can provide a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. The purchase checkout unit, for example, provides a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, if the user has a question during the checkout, the generation AI will respond in real time. The purchase checkout unit also provides a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, if the user asks about the progress of the checkout, the generation AI will provide a detailed explanation. The purchase checkout unit also provides a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, if the user asks about payment methods, the generation AI will provide appropriate advice. This makes it possible to provide a chatbot function that instantly answers any questions or concerns the user may have.

[0044] The purchase procedure unit can introduce a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. The purchase procedure unit, for example, introduces a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, the user gives instructions for the procedure by voice, and the generation AI proceeds with the procedure in accordance with those instructions. The purchase procedure unit also introduces a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, the user asks a question by voice, and the generation AI responds by voice. The purchase procedure unit also introduces a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, the user selects a payment method by voice, and the generation AI proceeds with the procedure in accordance with that selection. In this way, a voice assistant can be provided that allows the user to proceed with the procedure by voice.

[0045] The purchase checkout unit can provide multilingual support for purchase checkout support that corresponds to different languages ​​and cultures. The purchase checkout unit, for example, provides multilingual support for purchase checkout support that corresponds to different languages. For example, a procedure guide is displayed in a language selected by the user, and the generation AI provides support in that language. The purchase checkout unit also provides multilingual support for purchase checkout support that corresponds to different cultures. For example, appropriate procedure methods and advice are provided based on the culture selected by the user. The purchase checkout unit also provides multilingual support for purchase checkout support that corresponds to different languages ​​and cultures. For example, procedure guides and support are customized based on the language and culture selected by the user. This makes it possible to provide multilingual support for purchase checkout support that corresponds to different languages ​​and cultures.

[0046] The support department can provide personalized guides for post-purchase support that take into account the user's past trouble history and usage status. For example, the support department provides personalized guides for post-purchase support that take into account the user's past trouble history. For example, optimal support is provided based on solutions to problems that have occurred in the past. The support department also provides personalized guides that take into account the user's usage status. For example, support is provided for software and applications that the user uses frequently. The support department also provides personalized guides for post-purchase support that take into account the user's past trouble history and usage status. For example, support is provided for solutions to problems that have occurred in the past and for frequently used functions. This makes it possible to provide personalized guides based on the user's past trouble history and usage status.

[0047] The support department can provide a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, for post-purchase support, the support department provides a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, if a user asks a question about initial setup, the generation AI answers in real time. The support department also provides a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, if a user asks a question about troubleshooting, the generation AI provides a detailed solution. The support department also provides a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, if a user asks a question about upgrading, the generation AI provides appropriate advice. This makes it possible to provide a chatbot function that instantly answers the user's questions and concerns.

[0048] The support department can introduce video tutorials and online seminars for post-purchase support to allow users to understand visually. For example, the support department can introduce video tutorials for post-purchase support to allow users to understand visually. For example, videos can be used to explain initial setup and troubleshooting procedures. The support department can also introduce online seminars for post-purchase support to allow users to understand visually. For example, seminars can be held on PC maintenance and upgrades. The support department can also introduce video tutorials and online seminars for post-purchase support to allow users to understand visually. For example, videos can be used to explain how to use specific software or applications. This makes it possible to provide video tutorials and online seminars that allow users to understand visually.

[0049] The support department can provide multilingual support that corresponds to different languages ​​and cultures for post-purchase support. For example, the support department provides multilingual support that corresponds to different languages ​​for post-purchase support. For example, a support guide is displayed in a language selected by the user, and the generation AI provides support in that language. The support department also provides multilingual support that corresponds to different cultures. For example, appropriate support methods and advice are provided based on the culture selected by the user. The support department also provides multilingual support that corresponds to different languages ​​and cultures for post-purchase support. For example, a support guide and support are customized based on the language and culture selected by the user. This makes it possible to provide multilingual support that corresponds to different languages ​​and cultures.

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

[0051] The needs collection unit collects user needs. For example, a user can input requests such as "I want a PC for gaming" or "I need a high-performance PC for work." The analysis unit analyzes the collected needs. For example, a generation AI analyzes the user's input information and understands the needs. The proposal unit proposes the optimal PC configuration based on the analyzed needs. For example, a user looking for a PC for gaming might be suggested a configuration with a high-performance graphics card and large memory capacity. The customization unit provides customization options based on the proposed PC configuration. For example, if a user wants to increase storage capacity or use a specific brand of parts, the generation AI presents corresponding customization options. The estimation unit calculates an estimated price based on the provided customization options. For example, it automatically calculates the estimated price after customization and presents it to the user. This allows the PC BTO purchase support system to easily select and purchase a PC that meets their needs, even without specialized knowledge.

[0052] The needs gathering unit can analyze a user's past purchase history and usage history to predict future needs. For example, the unit analyzes a user's past purchase history to predict future needs. For example, the unit predicts the next required PC specifications based on the specifications and purpose of use of previously purchased PCs. The needs gathering unit also analyzes a user's past usage history to predict future needs. For example, the unit predicts the next required PC specifications based on data on software and applications used in the past. The needs gathering unit also analyzes a user's past purchase history and usage history to predict future needs. For example, the unit predicts the next required PC specifications based on the frequency and duration of use of previously purchased PCs. This makes it possible to predict the user's future needs and make more appropriate suggestions.

[0053] The needs gathering unit can make more personalized suggestions by taking into account the user's lifestyle and hobbies and preferences. For example, the generation AI makes personalized suggestions by taking into account the user's lifestyle. For example, if the user likes the outdoors, it will suggest a lightweight computer that is easy to carry. The needs gathering unit also takes into account the user's hobbies and preferences, and the generation AI makes personalized suggestions. For example, if the user's hobby is music production, it will suggest a computer with a high-performance audio interface. The needs gathering unit also takes into account the user's lifestyle and hobbies and preferences, and the generation AI makes personalized suggestions. For example, if the user's hobby is photography, it will suggest a computer with a large capacity storage device. This makes it possible to make suggestions that meet the individual needs of the user.

[0054] The needs gathering unit can collect a wider variety of information using voice and image input. For example, the user can input their needs using voice input, and the generation AI analyzes the voice data. For example, if a user inputs "I want a PC for gaming" by voice, the voice data is analyzed to understand their needs. The needs gathering unit can also allow the user to input their needs using image input, and the generation AI analyzes the image data. For example, if a user uploads an image of the PC they want, the image data is analyzed to understand their needs. The needs gathering unit can also allow the user to input their needs using voice or image input, and the generation AI analyzes the data. For example, if a user inputs "I need a high-performance PC for work" by voice and uploads an image of the PC they want, the data is analyzed to understand their needs. This makes it possible to collect a wider variety of information using voice and images.

[0055] The needs gathering unit can compare the needs of users of different age groups and regions, and analyze the region-specific needs. For example, the needs of users of different age groups are compared, and the generation AI analyzes the region-specific needs. For example, the needs of young users and elderly users are compared, and the region-specific needs of each are understood. The needs gathering unit also compares the needs of users of different regions, and the generation AI analyzes the region-specific needs. For example, the needs of users in urban areas and rural areas are compared, and the region-specific needs of each are understood. The needs gathering unit also compares the needs of users of different age groups and regions, and the generation AI analyzes the region-specific needs. For example, the needs of young urban users and elderly rural users are compared, and the region-specific needs of each are understood. This makes it possible to analyze region-specific needs and make more appropriate proposals.

[0056] The proposal unit can reflect the latest technological trends and market trends in the proposed PC configuration. For example, the proposal unit can reflect the latest technological trends in the PC configuration proposed by the generation AI. For example, it can propose a configuration equipped with the latest graphics cards and processors. The proposal unit can also reflect market trends in the proposed PC configuration. For example, it can propose a configuration using currently popular parts and brands. The proposal unit can also reflect the latest technological trends and market trends in the PC configuration proposed by the generation AI. For example, it can propose a configuration using parts that incorporate the latest technology or parts that are in high demand in the current market. This makes it possible to make proposals that reflect the latest technological trends and market trends.

[0057] The proposal unit can generate multiple configuration proposals based on the user's needs and compare the advantages and disadvantages of each. For example, the generation AI generates multiple PC configuration proposals based on the user's needs and compares the advantages and disadvantages of each. For example, a performance-oriented configuration is compared with a cost-oriented configuration. The proposal unit also generates multiple PC configuration proposals based on the user's needs and compares the advantages and disadvantages of each. For example, a configuration equipped with a high-performance graphics card is compared with a configuration equipped with large-capacity storage. The proposal unit also generates multiple PC configuration proposals based on the user's needs and compares the advantages and disadvantages of each. For example, a configuration incorporating the latest technology is compared with a configuration offering excellent cost performance. This allows the proposal unit to compare multiple configuration proposals and make the optimal proposal.

[0058] The suggestion unit can propose computer configurations for different uses. For example, the generation AI proposes computer configurations for different uses. For example, it proposes a configuration equipped with a high-performance graphics card and large-capacity memory for a computer used for design. The suggestion unit also proposes computer configurations for different uses. For example, it proposes a configuration equipped with a high-speed processor and large-capacity storage for a computer used for programming. The suggestion unit also proposes computer configurations for different uses. For example, it proposes a configuration equipped with a high-performance audio interface and a large-screen display for a computer used for entertainment. This makes it possible to propose optimal configurations for different uses.

[0059] The suggestion unit can add an option to use eco-friendly parts or recyclable materials to the proposed computer configuration. For example, the suggestion unit adds an option to use eco-friendly parts to the computer configuration proposed by the generation AI. For example, it proposes a low-power processor or parts made from recyclable materials. The suggestion unit also adds an option to use recyclable materials to the proposed computer configuration. For example, it proposes parts made from recycled plastic or recycled aluminum. The suggestion unit also adds an option to use eco-friendly parts or recyclable materials to the computer configuration proposed by the generation AI. For example, it proposes parts that have undergone an environmentally friendly manufacturing process. This makes it possible to make environmentally friendly suggestions.

[0060] The customization unit can dynamically adjust the customization option options according to the user's budget and intended use. For example, the customization option options are dynamically adjusted according to the user's budget. For example, the optimal parts are selected within the budget set by the user and customization options are presented. The customization unit also dynamically adjusts the customization option options according to the user's intended use. For example, if the user desires a PC for gaming, options equipped with a high-performance graphics card and large memory capacity are presented. The customization unit also dynamically adjusts the customization option options according to the user's budget and intended use. For example, if the user desires a high-performance PC for work, options equipped with a high-speed processor and large storage capacity are presented. This enables customization according to the user's budget and intended use.

[0061] The customization unit can propose a discount to the estimated price after customization, taking into consideration the user's ability to pay and past purchase history. For example, the customization unit proposes a discount to the estimated price after customization, taking into consideration the user's ability to pay. For example, the customization unit applies an optimal discount within the budget set by the user and presents the estimated price. The customization unit also proposes a discount to the estimated price after customization, taking into consideration the user's past purchase history. For example, a repeat customer discount is applied to a user who has purchased parts of the same brand in the past. The customization unit also proposes a discount to the estimated price after customization, taking into consideration the user's ability to pay and past purchase history. For example, if the user has purchased an expensive computer in the past, a special discount is applied. This makes it possible to propose a discount based on the user's ability to pay and past purchase history.

[0062] The customization unit can provide a function that allows a user to add parts and accessories that the user has designed himself to the customization options. For example, the customization unit provides a function that allows a user to add parts that the user has designed himself to the customization options. For example, the customization unit provides an option to incorporate a case or keyboard that the user has designed into the PC. The customization unit also provides a function that allows a user to add accessories that the user has designed himself to the customization options. For example, the customization unit provides an option to attach stickers or decals that the user has designed to the PC. The customization unit also provides a function that allows a user to add parts and accessories that the user has designed himself to the customization options. For example, the customization unit provides an option to incorporate a custom fan or LED light that the user has designed into the PC. This enables customization that allows a user to add parts and accessories that the user has designed himself to the customization options.

[0063] The estimating unit can accommodate different currencies and payment methods for the estimated amount to accommodate international users. For example, the estimated amount can be accommodated in different currencies to accommodate international users. For example, the estimated amount can be displayed in a currency selected by the user. The estimating unit can also accommodate different payment methods for the estimated amount to accommodate international users. For example, the payment method can be selected, such as credit card, electronic money, or bank transfer. The estimating unit can also accommodate different currencies and payment methods for the estimated amount to accommodate international users. For example, the estimated amount can be displayed in a currency and payment method selected by the user to allow the payment procedure to proceed smoothly. This makes it possible to provide an estimate that is suitable for international users.

[0064] The purchase procedure unit can provide a personalized guide for each step of the purchase procedure based on the user's past purchase history and preferences. For example, a personalized guide for each step of the purchase procedure based on the user's past purchase history is provided. For example, the optimal procedure is suggested based on the specifications and intended use of computers purchased in the past. The purchase procedure unit also provides a personalized guide for each step of the purchase procedure based on the user's preferences. For example, the optimal procedure is suggested based on the user's preferred brands and parts. The purchase procedure unit also provides a personalized guide for each step of the purchase procedure based on the user's past purchase history and preferences. For example, the optimal procedure is suggested based on the frequency of use and intended use of computers purchased in the past. In this way, a personalized guide can be provided based on the user's past purchase history and preferences.

[0065] The purchase checkout unit can provide a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, a chatbot function is provided in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, if the user has a question during the checkout, the generation AI will respond in real time. The purchase checkout unit also provides a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, if the user asks about the progress of the checkout, the generation AI will provide a detailed explanation. The purchase checkout unit also provides a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, if the user asks about payment methods, the generation AI will provide appropriate advice. This makes it possible to provide a chatbot function that instantly answers any questions or concerns the user may have.

[0066] The purchase procedure unit can introduce a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, a voice assistant can be introduced to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, the user gives instructions for the procedure by voice, and the generation AI proceeds with the procedure according to those instructions. The purchase procedure unit can also introduce a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, the user asks a question by voice, and the generation AI responds by voice. The purchase procedure unit can also introduce a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, the user selects a payment method by voice, and the generation AI proceeds with the procedure according to that selection. In this way, a voice assistant can be provided that allows the user to proceed with the procedure by voice.

[0067] The purchase checkout section can provide multilingual support for purchase checkout support that corresponds to different languages ​​and cultures. For example, multilingual support for purchase checkout support that corresponds to different languages ​​is provided. For example, a procedure guide is displayed in a language selected by the user, and the generation AI provides support in that language. The purchase checkout section also provides multilingual support for purchase checkout support that corresponds to different cultures. For example, appropriate procedure methods and advice are provided based on the culture selected by the user. The purchase checkout section also provides multilingual support for purchase checkout support that corresponds to different languages ​​and cultures. For example, procedure guides and support are customized based on the language and culture selected by the user. This makes it possible to provide multilingual support that corresponds to different languages ​​and cultures.

[0068] The support department can provide personalized guides for post-purchase support that take into account the user's past trouble history and usage status. For example, for post-purchase support, personalized guides are provided that take into account the user's past trouble history. For example, optimal support is provided based on how to resolve troubles that have occurred in the past. The support department also provides personalized guides that take into account the user's usage status. For example, support is provided for software and applications that the user uses frequently. The support department also provides personalized guides for post-purchase support that take into account the user's past trouble history and usage status. For example, support is provided for how to resolve troubles that have occurred in the past and for frequently used functions. In this way, personalized guides can be provided that are based on the user's past trouble history and usage status.

[0069] The support department can provide a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, for post-purchase support, the support department can provide a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, if a user asks a question about initial setup, the generation AI will respond in real time. The support department can also provide a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, if a user asks a question about troubleshooting, the generation AI will provide a detailed solution. The support department can also provide a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, if a user asks a question about upgrading, the generation AI will provide appropriate advice. This makes it possible to provide a chatbot function that instantly answers the user's questions and concerns.

[0070] The support department can introduce video tutorials and online seminars for post-purchase support to allow users to understand visually. For example, video tutorials can be introduced for post-purchase support to allow users to understand visually. For example, initial setup and troubleshooting procedures can be explained using videos. The support department can also introduce online seminars for post-purchase support to allow users to understand visually. For example, seminars can be held on PC maintenance and upgrades. The support department can also introduce video tutorials and online seminars for post-purchase support to allow users to understand visually. For example, videos can be used to explain how to use specific software or applications. This makes it possible to provide video tutorials and online seminars that allow users to understand visually.

[0071] The support department can provide multilingual support that corresponds to different languages ​​and cultures for post-purchase support. For example, multilingual support that corresponds to different languages ​​is provided for post-purchase support. For example, a support guide is displayed in a language selected by the user, and the generation AI provides support in that language. The support department also provides multilingual support that corresponds to different cultures. For example, appropriate support methods and advice are provided based on the culture selected by the user. The support department also provides multilingual support that corresponds to different languages ​​and cultures for post-purchase support. For example, a support guide and support are customized based on the language and culture selected by the user. This makes it possible to provide multilingual support that corresponds to different languages ​​and cultures.

[0072] The processing flow of the first embodiment will be briefly explained below.

[0073] Step 1: The needs gathering unit gathers the user's needs. For example, the user can input requests such as "I want a PC for gaming" or "I need a high-performance PC for work." Step 2: The analysis unit analyzes the collected needs. For example, the generation AI analyzes the user's input information and understands their needs. Step 3: The proposal unit proposes the optimal PC configuration based on the analyzed needs. For example, for a user who wants a PC for gaming, the proposal will suggest a configuration equipped with a high-performance graphics card and large memory capacity. Step 4: The customization section provides customization options based on the proposed PC configuration. For example, if a user wants to increase storage capacity or use a specific brand of parts, the generative AI will present customization options accordingly. Step 5: The quote unit calculates an estimated price based on the provided customization options. For example, the quote unit automatically calculates an estimated price after customization and presents it to the user.

[0074] (Example 2) The BTO PC purchase support system according to an embodiment of the present invention is a system in which a generation AI provides appropriate advice and suggestions so that users can easily select and purchase a PC that meets their needs. As a result, the BTO PC purchase support system allows users to easily select and purchase a PC that meets their needs even without specialized knowledge.

[0075] A BTO PC purchase support system according to an embodiment includes a needs collection unit, an analysis unit, a proposal unit, a customization unit, and an estimate unit. The needs collection unit collects user needs. For example, a user may input requests such as "I want a PC for gaming" or "I need a high-performance PC for work." The analysis unit analyzes the collected needs. For example, a generation AI analyzes the user's input information and understands the needs. The proposal unit proposes an optimal PC configuration based on the analyzed needs. For example, a user looking for a PC for gaming may be suggested a configuration equipped with a high-performance graphics card and large memory capacity. The customization unit provides customization options based on the proposed PC configuration. For example, if a user wants to increase storage capacity or use a specific brand of parts, the generation AI presents corresponding customization options. The estimate unit calculates an estimated price based on the provided customization options. For example, the estimate after customization may be automatically calculated and presented to the user. This allows users to easily select and purchase a PC that meets their needs, even without specialized knowledge.

[0076] The needs collection unit performs emotional analysis on the user's input information and can analyze the needs in detail based on the intensity and type of emotion. For example, in the needs collection unit, the generation AI performs emotional analysis on the requests entered by the user and quantifies the intensity and type of emotion. For example, when a user enters "I want a PC for gaming," the generation AI analyzes emotions such as excitement and anticipation and analyzes the needs in detail based on their intensity. The needs collection unit also performs emotional analysis on the user's input information and identifies the type of emotion. For example, when a user enters "I need a high-performance PC for work," the generation AI analyzes emotions such as stress and impatience and analyzes the needs in detail based on their type. The needs collection unit also performs emotional analysis on the user's input information and analyzes the needs in detail based on the intensity and type of emotion. For example, when a user enters "I want a PC for video editing," the generation AI analyzes emotions such as creativity and concentration and analyzes the needs in detail based on their intensity. This enables needs analysis that takes the user's emotions into consideration.

[0077] The needs gathering unit can analyze the user's past purchase history and usage history to predict future needs. The needs gathering unit, for example, analyzes the user's past purchase history to predict future needs. For example, the needs gathering unit predicts the next required PC specifications based on the specifications and purpose of use of PCs purchased in the past. The needs gathering unit also analyzes the user's past usage history to predict future needs. For example, the needs gathering unit predicts the next required PC specifications based on data on software and applications used in the past. The needs gathering unit also analyzes the user's past purchase history and usage history to predict future needs. For example, the needs gathering unit predicts the next required PC specifications based on the frequency and duration of use of PCs purchased in the past. This makes it possible to predict the user's future needs and make more appropriate suggestions.

[0078] The needs gathering unit can make more personalized suggestions by taking into account the user's lifestyle and hobbies and preferences. The needs gathering unit, for example, takes into account the user's lifestyle, and the generation AI makes personalized suggestions. For example, if the user likes the outdoors, the generation AI will suggest a lightweight computer that is easy to carry. The needs gathering unit also takes into account the user's hobbies and preferences, and the generation AI will make personalized suggestions. For example, if the user's hobby is music production, the generation AI will suggest a computer with a high-performance audio interface. The needs gathering unit also takes into account the user's lifestyle and hobbies and preferences, and the generation AI will make personalized suggestions. For example, if the user's hobby is photography, the generation AI will suggest a computer with a large capacity storage device. This makes it possible to make suggestions that meet the individual needs of the user.

[0079] The needs gathering unit can collect a wider variety of information using voice input or image input. For example, the needs gathering unit allows the user to input their needs using voice input, and the generation AI analyzes the voice data. For example, if a user voice-inputs, "I want a PC for gaming," the voice data is analyzed to understand their needs. The needs gathering unit also allows the user to input their needs using image input, and the generation AI analyzes the image data. For example, if a user uploads an image of the PC they want, the image data is analyzed to understand their needs. The needs gathering unit also allows the user to input their needs using voice input or image input, and the generation AI analyzes the data. For example, if a user voice-inputs, "I need a high-performance PC for work," and uploads an image of the PC they want, the data is analyzed to understand their needs. This makes it possible to collect a wider variety of information using voice and images.

[0080] The needs gathering unit can compare the needs of users of different age groups and regions, and analyze the region-specific needs. For example, the needs gathering unit compares the needs of users of different age groups, and the generation AI analyzes the region-specific needs. For example, the needs of young users and elderly users are compared, and the region-specific needs of each are understood. The needs gathering unit also compares the needs of users of different regions, and the generation AI analyzes the region-specific needs. For example, the needs of users in urban areas and rural areas are compared, and the region-specific needs of each are understood. The needs gathering unit also compares the needs of users of different age groups and regions, and the generation AI analyzes the region-specific needs. For example, the needs of young urban users and elderly rural users are compared, and the region-specific needs of each are understood. This makes it possible to analyze region-specific needs and make more appropriate suggestions.

[0081] The needs collection unit can use the emotion estimation function to analyze the emotions of the user when they enter text in real time and generate questions that elicit positive emotions. For example, the needs collection unit analyzes the emotions of the user when they enter text in real time and generates questions that elicit positive emotions. For example, when a user enters, "I want a PC for gaming," the generation AI asks, "What kind of games do you play?" The needs collection unit also uses the emotion estimation function to analyze the emotions of the user when they enter text in real time and generate questions that elicit positive emotions. For example, when a user enters, "I need a high-performance PC for work," the generation AI asks, "What kind of work do you do?" The needs collection unit also analyzes the emotions of the user when they enter text in real time and generates questions that elicit positive emotions. For example, when a user enters, "I want a PC for video editing," the generation AI asks, "What kind of videos do you edit?" This elicits positive emotions from the user and enables better suggestions.

[0082] The suggestion unit can monitor the user's emotional reactions in real time to the PC configuration proposed by the generation AI and adjust the optimal configuration. For example, the suggestion unit monitors the user's emotional reactions in real time to the PC configuration proposed by the generation AI and adjusts the optimal configuration. For example, if the user has a positive reaction to the proposed configuration, it will prioritize proposing that configuration. The suggestion unit also monitors the user's emotional reactions in real time and the generation AI will adjust the optimal PC configuration. For example, if the user has a negative reaction to the proposed configuration, it will propose a different configuration. The suggestion unit also monitors the user's emotional reactions in real time to the PC configuration proposed by the generation AI and adjusts the optimal configuration. For example, if the user expresses excitement or anticipation about the proposed configuration, it will prioritize proposing that configuration. This makes it possible to suggest the optimal PC configuration based on the user's emotions.

[0083] The suggestion unit can reflect the latest technological trends and market trends in the proposed PC configuration. For example, the suggestion unit reflects the latest technological trends in the PC configuration proposed by the generation AI. For example, it may propose a configuration equipped with the latest graphics cards and processors. The suggestion unit also reflects market trends in the proposed PC configuration. For example, it may propose a configuration using currently popular parts and brands. The suggestion unit also reflects the latest technological trends and market trends in the PC configuration proposed by the generation AI. For example, it may propose a configuration using parts that incorporate the latest technology or parts that are in high demand in the current market. This makes it possible to make proposals that reflect the latest technological trends and market trends.

[0084] The proposal unit can generate multiple configuration proposals based on the user's needs and compare the advantages and disadvantages of each. For example, the proposal unit uses a generation AI to generate multiple PC configuration proposals based on the user's needs and compare the advantages and disadvantages of each. For example, a performance-oriented configuration is compared with a cost-oriented configuration. The proposal unit also uses a generation AI to generate multiple PC configuration proposals based on the user's needs and compare the advantages and disadvantages of each. For example, a configuration equipped with a high-performance graphics card is compared with a configuration equipped with large-capacity storage. The proposal unit also uses a generation AI to generate multiple PC configuration proposals based on the user's needs and compare the advantages and disadvantages of each. For example, a configuration incorporating the latest technology is compared with a configuration offering excellent cost performance. This allows the proposal unit to compare multiple configuration proposals and make the optimal proposal.

[0085] The suggestion unit can propose computer configurations according to different uses. For example, the generation AI in the suggestion unit proposes computer configurations according to different uses. For example, it proposes a configuration equipped with a high-performance graphics card and large-capacity memory for a computer used for design. The suggestion unit also proposes computer configurations according to different uses. For example, it proposes a configuration equipped with a high-speed processor and large-capacity storage for a computer used for programming. The suggestion unit also proposes computer configurations according to different uses. For example, it proposes a configuration equipped with a high-performance audio interface and a large-screen display for a computer used for entertainment. This makes it possible to propose optimal configurations according to different uses.

[0086] The suggestion unit can add an option to use eco-friendly parts or recyclable materials to the proposed computer configuration. For example, the suggestion unit adds an option to use eco-friendly parts to the computer configuration proposed by the generation AI. For example, it suggests a low-power processor or parts made from recyclable materials. The suggestion unit also adds an option to use recyclable materials to the proposed computer configuration. For example, it suggests parts made from recycled plastic or recycled aluminum. The suggestion unit also adds an option to use eco-friendly parts or recyclable materials to the computer configuration proposed by the generation AI. For example, it suggests parts that have undergone an environmentally friendly manufacturing process. This makes it possible to make environmentally friendly suggestions.

[0087] The suggestion unit can use the emotion estimation function to identify the PC configuration that will most satisfy the user and preferentially suggest that configuration. For example, the suggestion unit uses the emotion estimation function to identify the PC configuration that will most satisfy the user and preferentially suggest that configuration. For example, if the user expresses positive emotions toward a proposed configuration, the suggestion unit preferentially suggests that configuration. The suggestion unit also monitors the user's emotional reactions in real time to identify the configuration that will most satisfy the generation AI. For example, if the user expresses emotions of excitement or anticipation toward a proposed configuration, the suggestion unit preferentially suggests that configuration. The suggestion unit also uses the emotion estimation function to identify the PC configuration that will most satisfy the user and preferentially suggest that configuration. For example, if the user expresses positive emotions toward a proposed configuration, the suggestion unit preferentially suggests that configuration. This enables suggestions that increase user satisfaction.

[0088] The customization unit can analyze the user's emotional response to the customization options and prioritize presenting the option that elicits the most positive response. For example, the customization unit analyzes the user's emotional response to the customization options and prioritize presenting the option that elicits the most positive response. For example, if the user has a positive response to parts of a particular brand, the customization unit prioritizes presenting parts of that brand. The customization unit also analyzes the user's emotional response in real time, and the generation AI presents the customization option that elicits the most positive response. For example, if the user has expressed excitement or anticipation toward a particular customization option, the customization unit prioritizes presenting that option. The customization unit also analyzes the user's emotional response to the customization options and prioritizes presenting the option that elicits the most positive response. For example, if the user has expressed positive emotions toward a particular customization option, the customization unit prioritizes presenting that option. This makes it possible to present customization options that elicit a positive response from the user.

[0089] The customization unit can dynamically adjust the options of customization options according to the user's budget and intended use. For example, the customization unit dynamically adjusts the options of customization options according to the user's budget. For example, the customization unit selects optimal parts within the budget set by the user and presents customization options. The customization unit also dynamically adjusts the options of customization options according to the user's intended use. For example, if the user wants a PC for gaming, the customization unit presents options equipped with a high-performance graphics card and large-capacity memory. The customization unit also dynamically adjusts the options of customization options according to the user's budget and intended use. For example, if the user wants a high-performance PC for work, the customization unit presents options equipped with a high-speed processor and large-capacity storage. This enables customization according to the user's budget and intended use.

[0090] The customization unit can propose a discount to the estimated price after customization, taking into consideration the user's ability to pay and past purchase history. The customization unit, for example, proposes a discount to the estimated price after customization, taking into consideration the user's ability to pay. For example, the customization unit applies an optimal discount within the budget set by the user and presents the estimated price. The customization unit also proposes a discount to the estimated price after customization, taking into consideration the user's past purchase history. For example, a repeat customer discount is applied to a user who has purchased parts of the same brand in the past. The customization unit also proposes a discount to the estimated price after customization, taking into consideration the user's ability to pay and past purchase history. For example, if the user has purchased an expensive computer in the past, a special discount is applied. This makes it possible to propose a discount based on the user's ability to pay and past purchase history.

[0091] The customization unit can provide a function that allows a user to add parts and accessories that the user has designed himself to the customization options. The customization unit, for example, provides a function that allows a user to add parts that the user has designed himself to the customization options. For example, it provides an option to incorporate a case or keyboard that the user has designed into the personal computer. The customization unit also provides a function that allows a user to add accessories that the user has designed himself to the customization options. For example, it provides an option to attach stickers or decals that the user has designed to the personal computer. The customization unit also provides a function that allows a user to add parts and accessories that the user has designed himself to the customization options. For example, it provides an option to incorporate a custom fan or LED light that the user has designed into the personal computer. This enables customization that allows a user to add parts and accessories that the user has designed himself to the customization options.

[0092] The estimating unit can accommodate different currencies and payment methods for the estimated amount to accommodate international users. The estimating unit, for example, accommodates different currencies for the estimated amount to accommodate international users. For example, the estimated amount is displayed in a currency selected by the user. The estimating unit also accommodates different payment methods for the estimated amount to accommodate international users. For example, payment methods such as credit card, electronic money, and bank transfer can be selected. The estimating unit also accommodates different currencies and payment methods for the estimated amount to accommodate international users. For example, the estimated amount is displayed in the currency and payment method selected by the user to allow the payment procedure to proceed smoothly. This makes it possible to provide an estimate that accommodates international users.

[0093] The customization unit can use the emotion estimation function to identify the customization option that will most satisfy the user and present that option preferentially. The customization unit, for example, uses the emotion estimation function to identify the customization option that will most satisfy the user and present that option preferentially. For example, if the user expresses positive emotions toward a particular customization option, the option is presented preferentially. The customization unit also monitors the user's emotional reactions in real time and identifies the customization option that will most satisfy the generation AI. For example, if the user expresses emotions of excitement or anticipation toward a particular customization option, the option is presented preferentially. The customization unit also uses the emotion estimation function to identify the customization option that will most satisfy the user and present that option preferentially. For example, if the user expresses positive emotions toward a particular customization option, the option is presented preferentially. This makes it possible to present customization options that increase user satisfaction.

[0094] The purchase checkout unit can monitor the user's emotional responses in real time during the purchase checkout and provide support to reduce stress. For example, if the user is feeling stressed, the generation AI provides advice on how to relax. The purchase checkout unit can also monitor the user's emotional responses in real time during the purchase checkout and provide support to reduce stress during the purchase checkout. For example, if the user is feeling anxious, the generation AI provides information to give the user a sense of security. The purchase checkout unit can also monitor the user's emotional responses in real time during the purchase checkout and provide support to reduce stress. For example, if the user is feeling impatient, the generation AI can explain the progress of the checkout in an easy-to-understand manner. This reduces the user's stress and supports a smooth purchase checkout.

[0095] The purchase procedure unit can provide a personalized guide for each step of the purchase procedure based on the user's past purchase history and preferences. The purchase procedure unit, for example, provides a personalized guide for each step of the purchase procedure based on the user's past purchase history. For example, the purchase procedure unit suggests the optimal procedure based on the specifications and intended use of computers purchased in the past. The purchase procedure unit also provides a personalized guide for each step of the purchase procedure based on the user's preferences. For example, the purchase procedure unit suggests the optimal procedure based on the user's preferred brands and parts. The purchase procedure unit also provides a personalized guide for each step of the purchase procedure based on the user's past purchase history and preferences. For example, the purchase procedure unit suggests the optimal procedure based on the frequency of use and intended use of computers purchased in the past. In this way, a personalized guide can be provided based on the user's past purchase history and preferences.

[0096] The purchase checkout unit can provide a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. The purchase checkout unit, for example, provides a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, if the user has a question during the checkout, the generation AI will respond in real time. The purchase checkout unit also provides a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, if the user asks about the progress of the checkout, the generation AI will provide a detailed explanation. The purchase checkout unit also provides a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, if the user asks about payment methods, the generation AI will provide appropriate advice. This makes it possible to provide a chatbot function that instantly answers any questions or concerns the user may have.

[0097] The purchase procedure unit can introduce a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. The purchase procedure unit, for example, introduces a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, the user gives instructions for the procedure by voice, and the generation AI proceeds with the procedure in accordance with those instructions. The purchase procedure unit also introduces a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, the user asks a question by voice, and the generation AI responds by voice. The purchase procedure unit also introduces a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, the user selects a payment method by voice, and the generation AI proceeds with the procedure in accordance with that selection. In this way, a voice assistant can be provided that allows the user to proceed with the procedure by voice.

[0098] The purchase checkout unit can provide multilingual support for purchase checkout support that corresponds to different languages ​​and cultures. The purchase checkout unit, for example, provides multilingual support for purchase checkout support that corresponds to different languages. For example, a procedure guide is displayed in a language selected by the user, and the generation AI provides support in that language. The purchase checkout unit also provides multilingual support for purchase checkout support that corresponds to different cultures. For example, appropriate procedure methods and advice are provided based on the culture selected by the user. The purchase checkout unit also provides multilingual support for purchase checkout support that corresponds to different languages ​​and cultures. For example, procedure guides and support are customized based on the language and culture selected by the user. This makes it possible to provide multilingual support for purchase checkout support that corresponds to different languages ​​and cultures.

[0099] The purchase procedure unit can use the emotion estimation function to provide appropriate support so that the user can proceed with the purchase procedure with the utmost confidence. The purchase procedure unit, for example, uses the emotion estimation function to provide appropriate support so that the user can proceed with the purchase procedure with the utmost confidence. For example, if the user is feeling anxious, the generation AI provides information to give them a sense of security. The purchase procedure unit also monitors the user's emotional reactions in real time and supports the generation AI so that the user can proceed with the purchase procedure with the utmost confidence. For example, if the user is feeling stressed, the generation AI provides advice on how to relax. The purchase procedure unit also uses the emotion estimation function to provide appropriate support so that the user can proceed with the purchase procedure with the utmost confidence. For example, if the user is feeling impatient, the generation AI will explain the progress of the procedure in an easy-to-understand manner. This makes it possible to provide support so that the user can proceed with the purchase procedure with the utmost confidence.

[0100] The support unit can monitor the user's emotional responses in real time to post-purchase support and provide optimal support. For example, when the user is confused, the generation AI provides detailed guidance. The support unit can also monitor the user's emotional responses in real time and provide optimal support. For example, when the user is feeling anxious, the generation AI provides information to reassure the user. The support unit can also monitor the user's emotional responses in real time to provide optimal support for post-purchase support. For example, when the user is feeling stressed, the generation AI provides advice on how to relax. This makes it possible to provide optimal support based on the user's emotional responses.

[0101] The support department can provide personalized guides for post-purchase support that take into account the user's past trouble history and usage status. For example, the support department provides personalized guides for post-purchase support that take into account the user's past trouble history. For example, optimal support is provided based on solutions to problems that have occurred in the past. The support department also provides personalized guides that take into account the user's usage status. For example, support is provided for software and applications that the user uses frequently. The support department also provides personalized guides for post-purchase support that take into account the user's past trouble history and usage status. For example, support is provided for solutions to problems that have occurred in the past and for frequently used functions. This makes it possible to provide personalized guides based on the user's past trouble history and usage status.

[0102] The support department can provide a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, for post-purchase support, the support department provides a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, if a user asks a question about initial setup, the generation AI answers in real time. The support department also provides a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, if a user asks a question about troubleshooting, the generation AI provides a detailed solution. The support department also provides a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, if a user asks a question about upgrading, the generation AI provides appropriate advice. This makes it possible to provide a chatbot function that instantly answers the user's questions and concerns.

[0103] The support department can introduce video tutorials and online seminars for post-purchase support to allow users to understand visually. For example, the support department can introduce video tutorials for post-purchase support to allow users to understand visually. For example, videos can be used to explain initial setup and troubleshooting procedures. The support department can also introduce online seminars for post-purchase support to allow users to understand visually. For example, seminars can be held on PC maintenance and upgrades. The support department can also introduce video tutorials and online seminars for post-purchase support to allow users to understand visually. For example, videos can be used to explain how to use specific software or applications. This makes it possible to provide video tutorials and online seminars that allow users to understand visually.

[0104] The support department can provide multilingual support that corresponds to different languages ​​and cultures for post-purchase support. For example, the support department provides multilingual support that corresponds to different languages ​​for post-purchase support. For example, a support guide is displayed in a language selected by the user, and the generation AI provides support in that language. The support department also provides multilingual support that corresponds to different cultures. For example, appropriate support methods and advice are provided based on the culture selected by the user. The support department also provides multilingual support that corresponds to different languages ​​and cultures for post-purchase support. For example, a support guide and support are customized based on the language and culture selected by the user. This makes it possible to provide multilingual support that corresponds to different languages ​​and cultures.

[0105] The support unit can use the emotion estimation function to identify the support that the user is most satisfied with and provide that support preferentially. For example, the support unit can use the emotion estimation function to identify the support that the user is most satisfied with and provide that support preferentially. For example, if the user expresses positive emotions toward a specific support, that support is provided preferentially. The support unit also monitors the user's emotional reactions in real time and identifies the support that the generation AI is most satisfied with. For example, if the user expresses emotions of excitement or anticipation toward a specific support, that support is provided preferentially. The support unit can also use the emotion estimation function to identify the support that the user is most satisfied with and provide that support preferentially. For example, if the user expresses positive emotions toward a specific support, that support is provided preferentially. This makes it possible to provide support that increases user satisfaction.

[0106] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0107] The needs collection unit collects user needs. For example, a user can input requests such as "I want a PC for gaming" or "I need a high-performance PC for work." The analysis unit analyzes the collected needs. For example, a generation AI analyzes the user's input information and understands the needs. The proposal unit proposes the optimal PC configuration based on the analyzed needs. For example, a user looking for a PC for gaming might be suggested a configuration with a high-performance graphics card and large memory capacity. The customization unit provides customization options based on the proposed PC configuration. For example, if a user wants to increase storage capacity or use a specific brand of parts, the generation AI presents corresponding customization options. The estimation unit calculates an estimated price based on the provided customization options. For example, it automatically calculates the estimated price after customization and presents it to the user. This allows the PC BTO purchase support system to easily select and purchase a PC that meets their needs, even without specialized knowledge.

[0108] The needs collection unit performs emotional analysis on the user's input information and can analyze the needs in detail based on the intensity and type of emotion. For example, the generation AI performs emotional analysis on the request entered by the user and quantifies the intensity and type of emotion. For example, when a user enters "I want a PC for gaming," the generation AI analyzes emotions such as excitement and anticipation and analyzes the needs in detail based on their intensity. The needs collection unit also performs emotional analysis on the user's input information and identifies the type of emotion. For example, when a user enters "I need a high-performance PC for work," the generation AI analyzes emotions such as stress and impatience and analyzes the needs in detail based on their type. The needs collection unit also performs emotional analysis on the user's input information and analyzes the needs in detail based on the intensity and type of emotion. For example, when a user enters "I want a PC for video editing," the generation AI analyzes emotions such as creativity and concentration and analyzes the needs in detail based on their intensity. This enables needs analysis that takes the user's emotions into account.

[0109] The needs gathering unit can analyze a user's past purchase history and usage history to predict future needs. For example, the unit analyzes a user's past purchase history to predict future needs. For example, the unit predicts the next required PC specifications based on the specifications and purpose of use of previously purchased PCs. The needs gathering unit also analyzes a user's past usage history to predict future needs. For example, the unit predicts the next required PC specifications based on data on software and applications used in the past. The needs gathering unit also analyzes a user's past purchase history and usage history to predict future needs. For example, the unit predicts the next required PC specifications based on the frequency and duration of use of previously purchased PCs. This makes it possible to predict the user's future needs and make more appropriate suggestions.

[0110] The needs gathering unit can make more personalized suggestions by taking into account the user's lifestyle and hobbies and preferences. For example, the generation AI makes personalized suggestions by taking into account the user's lifestyle. For example, if the user likes the outdoors, it will suggest a lightweight computer that is easy to carry. The needs gathering unit also takes into account the user's hobbies and preferences, and the generation AI makes personalized suggestions. For example, if the user's hobby is music production, it will suggest a computer with a high-performance audio interface. The needs gathering unit also takes into account the user's lifestyle and hobbies and preferences, and the generation AI makes personalized suggestions. For example, if the user's hobby is photography, it will suggest a computer with a large capacity storage device. This makes it possible to make suggestions that meet the individual needs of the user.

[0111] The needs gathering unit can collect a wider variety of information using voice and image input. For example, the user can input their needs using voice input, and the generation AI analyzes the voice data. For example, if a user inputs "I want a PC for gaming" by voice, the voice data is analyzed to understand their needs. The needs gathering unit can also allow the user to input their needs using image input, and the generation AI analyzes the image data. For example, if a user uploads an image of the PC they want, the image data is analyzed to understand their needs. The needs gathering unit can also allow the user to input their needs using voice or image input, and the generation AI analyzes the data. For example, if a user inputs "I need a high-performance PC for work" by voice and uploads an image of the PC they want, the data is analyzed to understand their needs. This makes it possible to collect a wider variety of information using voice and images.

[0112] The needs gathering unit can compare the needs of users of different age groups and regions, and analyze the region-specific needs. For example, the needs of users of different age groups are compared, and the generation AI analyzes the region-specific needs. For example, the needs of young users and elderly users are compared, and the region-specific needs of each are understood. The needs gathering unit also compares the needs of users of different regions, and the generation AI analyzes the region-specific needs. For example, the needs of users in urban areas and rural areas are compared, and the region-specific needs of each are understood. The needs gathering unit also compares the needs of users of different age groups and regions, and the generation AI analyzes the region-specific needs. For example, the needs of young urban users and elderly rural users are compared, and the region-specific needs of each are understood. This makes it possible to analyze region-specific needs and make more appropriate proposals.

[0113] The needs collection unit can use the emotion estimation function to analyze the emotions of the user when they enter text in real time and generate questions that elicit positive emotions. For example, the emotions of the user when they enter text can be analyzed in real time and questions that elicit positive emotions can be generated. For example, when a user enters, "I want a PC for gaming," the generation AI asks, "What kind of games do you play?" The needs collection unit can also use the emotion estimation function to analyze the emotions of the user when they enter text in real time and generate questions that elicit positive emotions. For example, when a user enters, "I need a high-performance PC for work," the generation AI asks, "What kind of work do you do?" The needs collection unit can also analyze the emotions of the user when they enter text in real time and generate questions that elicit positive emotions. For example, when a user enters, "I want a PC for video editing," the generation AI asks, "What kind of videos do you edit?" This elicits positive emotions from the user and enables better suggestions.

[0114] The suggestion unit can monitor the user's emotional reactions in real time to the PC configuration proposed by the generation AI and adjust the optimal configuration. For example, the suggestion unit can monitor the user's emotional reactions in real time to the PC configuration proposed by the generation AI and adjust the optimal configuration. For example, if the user has a positive reaction to the proposed configuration, that configuration is preferentially proposed. The suggestion unit can also monitor the user's emotional reactions in real time and adjust the optimal PC configuration by the generation AI. For example, if the user has a negative reaction to the proposed configuration, a different configuration is proposed. The suggestion unit can also monitor the user's emotional reactions in real time to the PC configuration proposed by the generation AI and adjust the optimal configuration. For example, if the user expresses excitement or anticipation about the proposed configuration, that configuration is preferentially proposed. This makes it possible to suggest the optimal PC configuration based on the user's emotions.

[0115] The proposal unit can reflect the latest technological trends and market trends in the proposed PC configuration. For example, the proposal unit can reflect the latest technological trends in the PC configuration proposed by the generation AI. For example, it can propose a configuration equipped with the latest graphics cards and processors. The proposal unit can also reflect market trends in the proposed PC configuration. For example, it can propose a configuration using currently popular parts and brands. The proposal unit can also reflect the latest technological trends and market trends in the PC configuration proposed by the generation AI. For example, it can propose a configuration using parts that incorporate the latest technology or parts that are in high demand in the current market. This makes it possible to make proposals that reflect the latest technological trends and market trends.

[0116] The proposal unit can generate multiple configuration proposals based on the user's needs and compare the advantages and disadvantages of each. For example, the generation AI generates multiple PC configuration proposals based on the user's needs and compares the advantages and disadvantages of each. For example, a performance-oriented configuration is compared with a cost-oriented configuration. The proposal unit also generates multiple PC configuration proposals based on the user's needs and compares the advantages and disadvantages of each. For example, a configuration equipped with a high-performance graphics card is compared with a configuration equipped with large-capacity storage. The proposal unit also generates multiple PC configuration proposals based on the user's needs and compares the advantages and disadvantages of each. For example, a configuration incorporating the latest technology is compared with a configuration offering excellent cost performance. This allows the proposal unit to compare multiple configuration proposals and make the optimal proposal.

[0117] The suggestion unit can propose computer configurations for different uses. For example, the generation AI proposes computer configurations for different uses. For example, it proposes a configuration equipped with a high-performance graphics card and large-capacity memory for a computer used for design. The suggestion unit also proposes computer configurations for different uses. For example, it proposes a configuration equipped with a high-speed processor and large-capacity storage for a computer used for programming. The suggestion unit also proposes computer configurations for different uses. For example, it proposes a configuration equipped with a high-performance audio interface and a large-screen display for a computer used for entertainment. This makes it possible to propose optimal configurations for different uses.

[0118] The suggestion unit can add an option to use eco-friendly parts or recyclable materials to the proposed computer configuration. For example, the suggestion unit adds an option to use eco-friendly parts to the computer configuration proposed by the generation AI. For example, it proposes a low-power processor or parts made from recyclable materials. The suggestion unit also adds an option to use recyclable materials to the proposed computer configuration. For example, it proposes parts made from recycled plastic or recycled aluminum. The suggestion unit also adds an option to use eco-friendly parts or recyclable materials to the computer configuration proposed by the generation AI. For example, it proposes parts that have undergone an environmentally friendly manufacturing process. This makes it possible to make environmentally friendly suggestions.

[0119] The suggestion unit can use the emotion estimation function to identify the configuration that will most satisfy the user and preferentially suggest that configuration. For example, the suggestion unit can use the emotion estimation function to identify the PC configuration that will most satisfy the user and preferentially suggest that configuration. For example, if the user expresses positive emotions toward the proposed configuration, the suggestion unit preferentially suggests that configuration. The suggestion unit also monitors the user's emotional reactions in real time to identify the configuration that will most satisfy the generation AI. For example, if the user expresses emotions of excitement or anticipation toward the proposed configuration, the suggestion unit preferentially suggests that configuration. The suggestion unit can also use the emotion estimation function to identify the PC configuration that will most satisfy the user and preferentially suggest that configuration. For example, if the user expresses positive emotions toward the proposed configuration, the suggestion unit preferentially suggests that configuration. This enables suggestions that increase user satisfaction.

[0120] The customization unit can analyze the user's emotional response to the customization options and prioritize presenting the options that elicit the most positive response. For example, the customization unit can analyze the user's emotional response to the customization options and prioritize presenting the options that elicit the most positive response. For example, if the user has a positive response to parts of a particular brand, the customization unit can prioritize presenting parts of that brand. The customization unit can also analyze the user's emotional response in real time and present the customization options that elicit the most positive response from the generation AI. For example, if the user has expressed excitement or anticipation toward a particular customization option, the customization unit can prioritize presenting that option. The customization unit can also analyze the user's emotional response to the customization options and prioritize presenting the options that elicit the most positive response. For example, if the user has expressed positive emotions toward a particular customization option, the customization unit can prioritize presenting that option. This makes it possible to present customization options that elicit a positive response from the user.

[0121] The customization unit can dynamically adjust the customization option options according to the user's budget and intended use. For example, the customization option options are dynamically adjusted according to the user's budget. For example, the optimal parts are selected within the budget set by the user and customization options are presented. The customization unit also dynamically adjusts the customization option options according to the user's intended use. For example, if the user desires a PC for gaming, options equipped with a high-performance graphics card and large memory capacity are presented. The customization unit also dynamically adjusts the customization option options according to the user's budget and intended use. For example, if the user desires a high-performance PC for work, options equipped with a high-speed processor and large storage capacity are presented. This enables customization according to the user's budget and intended use.

[0122] The customization unit can propose a discount to the estimated price after customization, taking into consideration the user's ability to pay and past purchase history. For example, the customization unit proposes a discount to the estimated price after customization, taking into consideration the user's ability to pay. For example, the customization unit applies an optimal discount within the budget set by the user and presents the estimated price. The customization unit also proposes a discount to the estimated price after customization, taking into consideration the user's past purchase history. For example, a repeat customer discount is applied to a user who has purchased parts of the same brand in the past. The customization unit also proposes a discount to the estimated price after customization, taking into consideration the user's ability to pay and past purchase history. For example, if the user has purchased an expensive computer in the past, a special discount is applied. This makes it possible to propose a discount based on the user's ability to pay and past purchase history.

[0123] The customization unit can provide a function that allows a user to add parts and accessories that the user has designed himself to the customization options. For example, the customization unit provides a function that allows a user to add parts that the user has designed himself to the customization options. For example, the customization unit provides an option to incorporate a case or keyboard that the user has designed into the PC. The customization unit also provides a function that allows a user to add accessories that the user has designed himself to the customization options. For example, the customization unit provides an option to attach stickers or decals that the user has designed to the PC. The customization unit also provides a function that allows a user to add parts and accessories that the user has designed himself to the customization options. For example, the customization unit provides an option to incorporate a custom fan or LED light that the user has designed into the PC. This enables customization that allows a user to add parts and accessories that the user has designed himself to the customization options.

[0124] The estimating unit can accommodate different currencies and payment methods for the estimated amount to accommodate international users. For example, the estimated amount can be accommodated in different currencies to accommodate international users. For example, the estimated amount can be displayed in a currency selected by the user. The estimating unit can also accommodate different payment methods for the estimated amount to accommodate international users. For example, the payment method can be selected, such as credit card, electronic money, or bank transfer. The estimating unit can also accommodate different currencies and payment methods for the estimated amount to accommodate international users. For example, the estimated amount can be displayed in a currency and payment method selected by the user to allow the payment procedure to proceed smoothly. This makes it possible to provide an estimate that is suitable for international users.

[0125] The customization unit can use the emotion estimation function to identify the customization option that will most satisfy the user and present that option preferentially. For example, the emotion estimation function can be used to identify the customization option that will most satisfy the user and present that option preferentially. For example, if the user expresses positive emotions toward a particular customization option, that option is presented preferentially. The customization unit also monitors the user's emotional reactions in real time and identifies the customization option that will most satisfy the generation AI. For example, if the user expresses emotions of excitement or anticipation toward a particular customization option, that option is presented preferentially. The customization unit can also use the emotion estimation function to identify the customization option that will most satisfy the user and present that option preferentially. For example, if the user expresses positive emotions toward a particular customization option, that option is presented preferentially. This makes it possible to present customization options that increase user satisfaction.

[0126] The purchase checkout unit can monitor the user's emotional responses in real time during the purchase process and provide support to reduce stress. For example, during the purchase process, the user's emotional responses can be monitored in real time and support can be provided to reduce stress. For example, if the user is feeling stressed, the generation AI can provide advice on how to relax. The purchase checkout unit can also monitor the user's emotional responses in real time and provide support to reduce stress during the purchase process. For example, if the user is feeling anxious, the generation AI can provide information to reassure the user. The purchase checkout unit can also monitor the user's emotional responses in real time during the purchase process and provide support to reduce stress. For example, if the user is feeling impatient, the generation AI can explain the progress of the process in an easy-to-understand manner. This can reduce the user's stress and support a smooth purchase process.

[0127] The purchase procedure unit can provide a personalized guide for each step of the purchase procedure based on the user's past purchase history and preferences. For example, a personalized guide for each step of the purchase procedure based on the user's past purchase history is provided. For example, the optimal procedure is suggested based on the specifications and intended use of computers purchased in the past. The purchase procedure unit also provides a personalized guide for each step of the purchase procedure based on the user's preferences. For example, the optimal procedure is suggested based on the user's preferred brands and parts. The purchase procedure unit also provides a personalized guide for each step of the purchase procedure based on the user's past purchase history and preferences. For example, the optimal procedure is suggested based on the frequency of use and intended use of computers purchased in the past. In this way, a personalized guide can be provided based on the user's past purchase history and preferences.

[0128] The purchase checkout unit can provide a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, a chatbot function is provided in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, if the user has a question during the checkout, the generation AI will respond in real time. The purchase checkout unit also provides a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, if the user asks about the progress of the checkout, the generation AI will provide a detailed explanation. The purchase checkout unit also provides a chatbot function in which the generation AI instantly answers any questions or concerns the user may have during the purchase checkout. For example, if the user asks about payment methods, the generation AI will provide appropriate advice. This makes it possible to provide a chatbot function that instantly answers any questions or concerns the user may have.

[0129] The purchase procedure unit can introduce a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, a voice assistant can be introduced to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, the user gives instructions for the procedure by voice, and the generation AI proceeds with the procedure according to those instructions. The purchase procedure unit can also introduce a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, the user asks a question by voice, and the generation AI responds by voice. The purchase procedure unit can also introduce a voice assistant to support the purchase procedure, allowing the user to proceed with the procedure by voice. For example, the user selects a payment method by voice, and the generation AI proceeds with the procedure according to that selection. In this way, a voice assistant can be provided that allows the user to proceed with the procedure by voice.

[0130] The purchase checkout section can provide multilingual support for purchase checkout support that corresponds to different languages ​​and cultures. For example, multilingual support for purchase checkout support that corresponds to different languages ​​is provided. For example, a procedure guide is displayed in a language selected by the user, and the generation AI provides support in that language. The purchase checkout section also provides multilingual support for purchase checkout support that corresponds to different cultures. For example, appropriate procedure methods and advice are provided based on the culture selected by the user. The purchase checkout section also provides multilingual support for purchase checkout support that corresponds to different languages ​​and cultures. For example, procedure guides and support are customized based on the language and culture selected by the user. This makes it possible to provide multilingual support that corresponds to different languages ​​and cultures.

[0131] The purchase procedure unit can use the emotion estimation function to provide appropriate support so that the user can proceed with the purchase procedure with the utmost confidence. For example, if the user is feeling anxious, the generation AI provides information to reassure the user. The purchase procedure unit also monitors the user's emotional reactions in real time and supports the generation AI so that the user can proceed with the purchase procedure with the utmost confidence. For example, if the user is feeling stressed, the generation AI provides advice on how to relax. The purchase procedure unit also uses the emotion estimation function to provide appropriate support so that the user can proceed with the purchase procedure with the utmost confidence. For example, if the user is feeling impatient, the generation AI will explain the progress of the procedure in an easy-to-understand manner. This makes it possible to provide support so that the user can proceed with the purchase procedure with the utmost confidence.

[0132] The support unit can monitor the user's emotional responses in real time for post-purchase support and provide optimal support. For example, for post-purchase support, the support unit can monitor the user's emotional responses in real time and provide optimal support. For example, if the user is confused, the generation AI can provide detailed guidance. The support unit can also monitor the user's emotional responses in real time and provide optimal support. For example, if the user is feeling anxious, the generation AI can provide information to reassure the user. The support unit can also monitor the user's emotional responses in real time for post-purchase support and provide optimal support. For example, if the user is feeling stressed, the generation AI can provide advice on how to relax. This makes it possible to provide optimal support based on the user's emotional responses.

[0133] The support department can provide personalized guides for post-purchase support that take into account the user's past trouble history and usage status. For example, for post-purchase support, personalized guides are provided that take into account the user's past trouble history. For example, optimal support is provided based on how to resolve troubles that have occurred in the past. The support department also provides personalized guides that take into account the user's usage status. For example, support is provided for software and applications that the user uses frequently. The support department also provides personalized guides for post-purchase support that take into account the user's past trouble history and usage status. For example, support is provided for how to resolve troubles that have occurred in the past and for frequently used functions. In this way, personalized guides can be provided that are based on the user's past trouble history and usage status.

[0134] The support department can provide a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, for post-purchase support, the support department can provide a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, if a user asks a question about initial setup, the generation AI will respond in real time. The support department can also provide a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, if a user asks a question about troubleshooting, the generation AI will provide a detailed solution. The support department can also provide a chatbot function for post-purchase support in which the generation AI instantly answers the user's questions and concerns. For example, if a user asks a question about upgrading, the generation AI will provide appropriate advice. This makes it possible to provide a chatbot function that instantly answers the user's questions and concerns.

[0135] The support department can introduce video tutorials and online seminars for post-purchase support to allow users to understand visually. For example, video tutorials can be introduced for post-purchase support to allow users to understand visually. For example, initial setup and troubleshooting procedures can be explained using videos. The support department can also introduce online seminars for post-purchase support to allow users to understand visually. For example, seminars can be held on PC maintenance and upgrades. The support department can also introduce video tutorials and online seminars for post-purchase support to allow users to understand visually. For example, videos can be used to explain how to use specific software or applications. This makes it possible to provide video tutorials and online seminars that allow users to understand visually.

[0136] The support department can provide multilingual support that corresponds to different languages ​​and cultures for post-purchase support. For example, multilingual support that corresponds to different languages ​​is provided for post-purchase support. For example, a support guide is displayed in a language selected by the user, and the generation AI provides support in that language. The support department also provides multilingual support that corresponds to different cultures. For example, appropriate support methods and advice are provided based on the culture selected by the user. The support department also provides multilingual support that corresponds to different languages ​​and cultures for post-purchase support. For example, a support guide and support are customized based on the language and culture selected by the user. This makes it possible to provide multilingual support that corresponds to different languages ​​and cultures.

[0137] The support unit can use the emotion estimation function to identify the support that the user is most satisfied with and provide that support preferentially. For example, the emotion estimation function can be used to identify the support that the user is most satisfied with and provide that support preferentially. For example, if the user expresses positive emotions toward a specific support, that support is provided preferentially. The support unit also monitors the user's emotional reactions in real time and identifies the support that the generation AI is most satisfied with. For example, if the user expresses emotions of excitement or anticipation toward a specific support, that support is provided preferentially. The support unit can also use the emotion estimation function to identify the support that the user is most satisfied with and provide that support preferentially. For example, if the user expresses positive emotions toward a specific support, that support is provided preferentially. This makes it possible to provide support that increases user satisfaction.

[0138] The processing flow of the second embodiment will be briefly explained below.

[0139] Step 1: The needs gathering unit gathers the user's needs. For example, the user can input requests such as "I want a PC for gaming" or "I need a high-performance PC for work." Step 2: The analysis unit analyzes the collected needs. For example, the generation AI analyzes the user's input information and understands their needs. Step 3: The proposal unit proposes the optimal PC configuration based on the analyzed needs. For example, for a user who wants a PC for gaming, the proposal will suggest a configuration equipped with a high-performance graphics card and large memory capacity. Step 4: The customization section provides customization options based on the proposed PC configuration. For example, if a user wants to increase storage capacity or use a specific brand of parts, the generative AI will present customization options accordingly. Step 5: The quote unit calculates an estimated price based on the provided customization options. For example, the quote unit automatically calculates an estimated price after customization and presents it to the user.

[0140] 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.

[0141] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0142] 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.

[0143] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0144] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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).

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0157] 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.

[0158] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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).

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] In the headset type terminal 314, 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. 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 specific processing unit 290 using these models.

[0169] 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.

[0170] 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.

[0171] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0172] 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.

[0173] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0174] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0175] 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.

[0176] 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.

[0177] 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.

[0178] 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).

[0179] 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.

[0180] 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.

[0181] 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.

[0182] 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.

[0183] 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.

[0184] In the robot 414, 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 robot 414 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.

[0185] 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.

[0186] 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.

[0187] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0188] 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.

[0189] 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.

[0190] 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.

[0191] 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.

[0192] 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).

[0193] 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.

[0194] 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."

[0195] 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.

[0196] 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.

[0197] 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.

[0198] 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.

[0199] 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.

[0200] 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.

[0201] 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.

[0202] 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.

[0203] 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.

[0204] 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.

[0205] 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.

[0206] 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. [Explanation of symbols]

[0207] 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 needs gathering unit that gathers user needs; an analysis unit that analyzes the needs collected by the needs collection unit; a proposal unit that proposes an optimal personal computer configuration based on the needs analyzed by the analysis unit; a customization unit that provides customization options based on the PC configuration suggested by the suggestion unit; an estimate unit that calculates an estimate based on the customization options provided by the customization unit; A system characterized by:

2. The needs collection unit A sentiment analysis is performed on the information input by the user, and the needs are analyzed in detail based on the intensity and type of the sentiment.

2. The system of claim 1.

3. The needs collection unit Analyzing the user's past purchase history and usage history to predict future needs 2. The system of claim 1.

4. The needs collection unit Taking into account the user's lifestyle and preferences, we make more personalized suggestions.

2. The system of claim 1.

5. The needs collection unit Use voice and image input to collect more diverse information 2. The system of claim 1.

6. The needs collection unit Compare the needs of users of different age groups and regions and analyze the specific needs of each region.

2. The system of claim 1.

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