system

Abstract

The system according to the embodiment aims to effectively utilize the answer space of the generation AI as an advertising space. [Solution] A system according to an embodiment includes a generation unit, a setting unit, an embedding unit, a customization unit, and a sales unit. The generation unit generates answers to user questions. The setting unit sets a portion of the answer space generated by the generation unit as an advertising space. The embedding unit embeds company information in the advertising space set by the setting unit. The customization unit displays the advertisement embedded by the embedding unit based on the content of the user's question. The sales unit purchases the advertising space displayed by the customization unit and sells it to companies.

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 does not have a method for effectively utilizing the answer space generated by the AI ​​as an advertising space, and there is room for improvement.

[0005] The system according to the embodiment aims to effectively utilize the answer space of the generation AI as an advertising space. [Means for solving the problem]

[0006] The system according to the embodiment includes a generation unit, a setting unit, an embedding unit, a customization unit, and a sales unit. The generation unit generates an answer to a user's question. The setting unit sets a portion of the answer frame generated by the generation unit as an advertising frame. The embedding unit embeds company information in the advertising frame set by the setting unit. The customization unit displays the advertisement embedded by the embedding unit based on the content of the user's question. The sales unit purchases the advertising frame displayed by the customization unit and sells it to companies. [Effects of the Invention]

[0007] The system according to the embodiment can effectively utilize the answer space of the generation AI as an advertising space. [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) An advertising space sales system according to an embodiment of the present invention sells answer spaces generated by a generation AI as advertising space. When a generation AI generates an answer to a user's question, this advertising space sales system sets a portion of the answer space as advertising space. Next, by embedding information about the investing company in the advertising space, the system can improve the company's image and promote its advertising effectiveness. For example, when a user inputs a question into the generation AI, an advertisement for the investing company is displayed as part of the answer. This advertisement is customized based on the user's interests, enabling effective advertising. Furthermore, SoftBank purchases this answer space from the provider of the generation AI and sells it to the investing company. This allows SoftBank to operate the answer space advertisements and generate revenue. Specifically, SoftBank accepts purchases of advertising space from the investing company and embeds advertisements in the generation AI's answer space. This advertisement is displayed based on the user's question content and interests, enabling effective advertising. This system allows SoftBank to improve its corporate image and promote its advertising effectiveness by utilizing the generation AI's answer space as advertising space, thereby generating revenue. This allows the advertising space sales system to utilize the response space generated by the generating AI as advertising space, thereby improving the company's image and achieving advertising effects.

[0029] An advertising space sales system according to an embodiment includes a generation unit, a setting unit, an embedding unit, a customization unit, and a sales unit. The generation unit generates an answer to a user's question. The generation unit generates an answer to the user's question using, for example, natural language processing technology. The generation unit can also generate an answer using a machine learning algorithm. For example, the generation unit receives a user's question as input and generates an answer using natural language processing technology. The generation unit can also use a machine learning algorithm to learn data on past questions and answers and generate an answer to a new question. The setting unit sets a portion of the answer space generated by the generation unit as an advertising space. For example, the setting unit sets a portion of the answer space as a banner advertisement. The setting unit can also set a portion of the answer space as a text advertisement. For example, the setting unit sets a portion of the answer space as a banner advertisement and displays an advertisement in a portion of the answer to the user's question. The setting unit can also set a portion of the answer space as a text advertisement and display a text advertisement in a portion of the answer to the user's question. The embedding unit embeds information about the investing company in the advertising space set by the setting unit. The embedding unit, for example, embeds the logo of the investing company in the advertising space. The embedding unit can also embed product information of the investing company in the advertising space. For example, the embedding unit embeds the logo of the investing company in the advertising space and displays it as part of the answer to the user's question. The embedding unit can also embed product information of the investing company in the advertising space and display it as part of the answer to the user's question. The customization unit displays the advertisement embedded by the embedding unit based on the content of the user's question and interests. The customization unit, for example, displays the advertisement based on the content of the user's question. The customization unit can also display the advertisement based on the user's interests. For example, the customization unit displays the advertisement based on the content of the user's question, and displays the advertisement related to the user's question. The customization unit can also display the advertisement based on the user's interests, and displays the advertisement related to the user's interests. The sales unit purchases the advertising space displayed by the customization unit and sells it to the investing company. The sales unit, for example, purchases the answer space from a provider of the generation AI and sells it to the investing company.The sales department can also accept purchases of advertising space from investing companies and embed advertisements in the answer spaces of the generation AI. For example, the sales department purchases answer spaces from the provider of the generation AI and sells them to investing companies. The sales department can also accept purchases of advertising space from investing companies and embed advertisements in the answer spaces of the generation AI. As a result, the advertising space sales system according to the embodiment can utilize the answer spaces of the generation AI as advertising spaces, thereby improving the company's image and achieving advertising effects.

[0030] The customization unit can display an advertisement based on the content of the user's question. The customization unit, for example, displays an advertisement based on the content of the user's question. For example, the customization unit extracts keywords related to the content of the user's question and displays an advertisement based on the keywords. The customization unit can also perform context analysis of the content of the user's question and display an advertisement based on the context. For example, the customization unit extracts keywords related to the content of the user's question and displays an advertisement based on the keywords. The customization unit can also perform context analysis of the content of the user's question and display an advertisement based on the context. This enables effective advertising by displaying an advertisement based on the content of the user's question and interests.

[0031] The sales department can purchase answer slots from the provider of the generation AI and sell them to companies. For example, the sales department purchases answer slots from the provider of the generation AI and sells them to companies. For example, the sales department purchases answer slots from the provider of the generation AI and sells them to companies. The sales department can also purchase answer slots from the provider of the generation AI and enter into a contract to sell them to companies. For example, the sales department purchases answer slots from the provider of the generation AI and sells them to companies. The sales department can also purchase answer slots from the provider of the generation AI and enter into a contract to sell them to companies. In this way, it is possible to monetize by purchasing answer slots from the provider of the generation AI and selling them to investing companies.

[0032] The setting unit can set a portion of the answer space as an advertising space when the generation AI generates an answer to a user's question. For example, when the generation AI generates an answer to a user's question, the setting unit sets a portion of the answer space as an advertising space. For example, when the generation AI generates an answer to a user's question, the setting unit sets a portion of the answer space as a banner advertisement. Furthermore, the setting unit can also set a portion of the answer space as a text advertisement when the generation AI generates an answer to a user's question. For example, when the generation AI generates an answer to a user's question, the setting unit sets a portion of the answer space as a banner advertisement. Furthermore, the setting unit can also set a portion of the answer space as a text advertisement when the generation AI generates an answer to a user's question. In this way, by setting an advertising space when the generation AI generates an answer, it becomes possible to display advertisements.

[0033] The embedding unit can embed company information into the advertising space. The embedding unit, for example, embeds company information into the advertising space. For example, the embedding unit embeds a company logo into the advertising space. The embedding unit can also embed company product information into the advertising space. For example, the embedding unit embeds a company logo into the advertising space and displays it as part of the answer to the user's question. The embedding unit can also embed company product information into the advertising space and display it as part of the answer to the user's question. In this way, by embedding information about the investing company into the advertising space, it is possible to improve the company's image and achieve advertising effects.

[0034] The customization unit may include a unit for measuring the effectiveness of the advertisement. The customization unit may include, for example, a unit for measuring the effectiveness of the advertisement. For example, the customization unit may include a unit for measuring a click rate of the advertisement. The customization unit may also include a unit for measuring a conversion rate of the advertisement. For example, the customization unit may include a unit for measuring a click rate of the advertisement, and measure the click rate of the advertisement. The customization unit may also include a unit for measuring a conversion rate of the advertisement, and measure the conversion rate of the advertisement. In this way, by measuring the effectiveness of the advertisement, the effectiveness of the advertisement can be evaluated and improved.

[0035] The generation unit can analyze the user's past question history and generate an appropriate answer. The generation unit, for example, analyzes the user's past question history and generates an appropriate answer. For example, if the user has asked a similar question in the past, the generation unit generates a new answer by referring to the answer. The generation unit can also extract a topic of interest from the user's past question history and generate an answer that includes information related to that topic. For example, if the user has asked a similar question in the past, the generation unit generates a new answer by referring to the answer. The generation unit can also extract a topic of interest from the user's past question history and generate an answer that includes information related to that topic. In this way, by analyzing the user's past question history, it is possible to provide a more appropriate answer.

[0036] The generation unit can adjust the content of the answer based on the user's current areas of interest when generating an answer. For example, the generation unit adjusts the content of the answer based on the user's current areas of interest when generating an answer. For example, the generation unit generates an answer including related information based on keywords recently searched by the user. The generation unit can also generate an answer including topics of interest by referring to the content of websites recently visited by the user. For example, the generation unit generates an answer including related information based on keywords recently searched by the user. The generation unit can also generate an answer including topics of interest by referring to the content of websites recently visited by the user. In this way, by customizing the content of the answer based on the user's current areas of interest, it is possible to provide a more relevant answer.

[0037] The generation unit can provide highly relevant information based on the user's geographical location information when generating an answer. The generation unit, for example, provides highly relevant information based on the user's geographical location information when generating an answer. For example, when the user is in a specific area, the generation unit generates an answer that includes information related to the area. Furthermore, when the user is traveling, the generation unit can also generate an answer that includes tourist information based on the user's current location. For example, when the user is in a specific area, the generation unit generates an answer that includes information related to the area. Furthermore, when the user is traveling, the generation unit can also generate an answer that includes tourist information based on the user's current location. In this way, by taking the user's geographical location information into consideration, more relevant information can be provided.

[0038] The generation unit can analyze the user's social media activity and provide related information when generating an answer. For example, the generation unit can analyze the user's social media activity and provide related information when generating an answer. For example, the generation unit can generate an answer including related information based on articles recently shared by the user on social media. The generation unit can also generate an answer including related information based on topics of accounts the user follows on social media. For example, the generation unit can generate an answer including related information based on articles recently shared by the user on social media. The generation unit can also generate an answer including related information based on topics of accounts the user follows on social media. In this way, by analyzing the user's social media activity, more relevant information can be provided.

[0039] When setting an ad space, the setting unit can analyze a user's past ad click history and select an appropriate placement. When setting an ad space, the setting unit, for example, analyzes a user's past ad click history and selects an appropriate placement. For example, the setting unit refers to the positions of ads that the user has clicked in the past and places the ad space in a similar position. The setting unit can also place the ad space in the most effective position based on the user's past click history. For example, the setting unit refers to the positions of ads that the user has clicked in the past and places the ad space in a similar position. The setting unit can also place the ad space in the most effective position based on the user's past click history. In this way, by analyzing a user's past ad click history, it is possible to place the optimal ad space.

[0040] The setting unit can adjust the content of the ad space based on the user's current areas of interest when setting the ad space. For example, the setting unit adjusts the content of the ad space based on the user's current areas of interest when setting the ad space. For example, the setting unit displays relevant advertisements based on keywords recently searched by the user. The setting unit can also display advertisements of interest to the user by referring to the content of websites recently visited by the user. For example, the setting unit displays relevant advertisements based on keywords recently searched by the user. The setting unit can also display advertisements of interest to the user by referring to the content of websites recently visited by the user. This enables more effective ad display by customizing the content of the ad space based on the user's current areas of interest.

[0041] The setting unit can display highly relevant advertisements based on the user's geographical location information when setting an advertisement space. The setting unit, for example, displays highly relevant advertisements based on the user's geographical location information when setting an advertisement space. For example, when the user is in a specific area, the setting unit displays advertisements related to the area. Furthermore, when the user is traveling, the setting unit can also display advertisements including tourist information based on the user's current location. For example, when the user is in a specific area, the setting unit displays advertisements related to the area. Furthermore, when the user is traveling, the setting unit can also display advertisements including tourist information based on the user's current location. In this way, by taking the user's geographical location information into consideration, more relevant advertisements can be displayed.

[0042] The setting unit can analyze the user's social media activity and display relevant advertisements when setting an advertisement slot. The setting unit, for example, analyzes the user's social media activity and displays relevant advertisements when setting an advertisement slot. For example, the setting unit displays relevant advertisements based on articles recently shared by the user on social media. The setting unit can also display relevant advertisements based on topics of accounts the user follows on social media. For example, the setting unit displays relevant advertisements based on articles recently shared by the user on social media. The setting unit can also display relevant advertisements based on topics of accounts the user follows on social media. In this way, by analyzing the user's social media activity, more relevant advertisements can be displayed.

[0043] The embedding unit can select appropriate content by analyzing the company's past advertising effectiveness when embedding advertising content. For example, the embedding unit analyzes the company's past advertising effectiveness when embedding advertising content and selects appropriate content. For example, the embedding unit analyzes the effectiveness of the company's past advertising campaigns and selects the most effective content. The embedding unit can also select optimal advertising content by referring to the company's past advertising click-through rate. For example, the embedding unit analyzes the effectiveness of the company's past advertising campaigns and selects the most effective content. The embedding unit can also select optimal advertising content by referring to the company's past advertising click-through rate. In this way, optimal advertising content can be selected by analyzing the company's past advertising effectiveness.

[0044] The embedding unit may adjust the content of the advertisement based on the user's current areas of interest when embedding the advertisement content. For example, the embedding unit may adjust the content of the advertisement based on the user's current areas of interest when embedding the advertisement content. For example, the embedding unit may display relevant advertisement content based on keywords recently searched by the user. The embedding unit may also display advertisement content of interest to the user by referring to the content of websites recently visited by the user. For example, the embedding unit may display relevant advertisement content based on keywords recently searched by the user. The embedding unit may also display advertisement content of interest to the user by referring to the content of websites recently visited by the user. This allows for more effective advertisement display by customizing the advertisement content based on the user's current areas of interest.

[0045] The embedding unit can prioritize displaying highly relevant advertisements by taking into consideration the user's geographical location information when embedding advertisement content. For example, the embedding unit prioritizes displaying highly relevant advertisements by taking into consideration the user's geographical location information when embedding advertisement content. For example, when the user is in a specific area, the embedding unit displays advertisements related to the area. Furthermore, when the user is traveling, the embedding unit can also display advertisements including tourist information based on the user's current location. For example, when the user is in a specific area, the embedding unit displays advertisements related to the area. Furthermore, when the user is traveling, the embedding unit can also display advertisements including tourist information based on the user's current location. In this way, more relevant advertisements can be displayed by taking into consideration the user's geographical location information.

[0046] The embedding unit can analyze the user's social media activity and display relevant advertisements when embedding the advertisement content. For example, the embedding unit analyzes the user's social media activity and display relevant advertisements when embedding the advertisement content. For example, the embedding unit displays relevant advertisements based on articles recently shared by the user on social media. The embedding unit can also display relevant advertisements based on topics of accounts the user follows on social media. For example, the embedding unit displays relevant advertisements based on articles recently shared by the user on social media. The embedding unit can also display relevant advertisements based on topics of accounts the user follows on social media. In this way, by analyzing the user's social media activity, more relevant advertisements can be displayed.

[0047] When customizing an advertisement, the customization unit can analyze the user's past ad click history and select an appropriate display method. For example, when customizing an advertisement, the customization unit analyzes the user's past ad click history and selects an appropriate display method. For example, the customization unit refers to the display method of an advertisement that the user has clicked in the past and displays the advertisement in a similar manner. The customization unit can also select the most effective display method from the user's past click history. For example, the customization unit refers to the display method of an advertisement that the user has clicked in the past and displays the advertisement in a similar manner. The customization unit can also select the most effective display method from the user's past click history. In this way, the optimal advertisement display method can be selected by analyzing the user's past ad click history.

[0048] The customization unit may adjust the content of the advertisement based on the user's current areas of interest when customizing the advertisement. For example, the customization unit may adjust the content of the advertisement based on the user's current areas of interest when customizing the advertisement. For example, the customization unit may display relevant advertisement content based on keywords recently searched by the user. The customization unit may also display advertisement content of interest to the user based on content of websites recently visited by the user. For example, the customization unit may display relevant advertisement content based on keywords recently searched by the user. The customization unit may also display advertisement content of interest to the user based on content of websites recently visited by the user. This allows for more effective advertisement display by customizing advertisement content based on the user's current areas of interest.

[0049] The customization unit can prioritize displaying highly relevant advertisements by taking into consideration the user's geographical location information when customizing advertisements. For example, the customization unit prioritizes displaying highly relevant advertisements by taking into consideration the user's geographical location information when customizing advertisements. For example, when the user is in a specific area, the customization unit displays advertisements related to the area. Furthermore, when the user is traveling, the customization unit can also display advertisements including tourist information based on the user's current location. For example, when the user is in a specific area, the customization unit displays advertisements related to the area. Furthermore, when the user is traveling, the customization unit can also display advertisements including tourist information based on the user's current location. In this way, by taking into consideration the user's geographical location information, more relevant advertisements can be displayed.

[0050] The customization unit may analyze the user's social media activity and display relevant advertisements when customizing advertisements. For example, the customization unit may analyze the user's social media activity and display relevant advertisements when customizing advertisements. For example, the customization unit may display relevant advertisements based on articles recently shared by the user on social media. The customization unit may also display relevant advertisements based on topics of accounts the user follows on social media. For example, the customization unit may display relevant advertisements based on articles recently shared by the user on social media. The customization unit may also display relevant advertisements based on topics of accounts the user follows on social media. In this way, by analyzing the user's social media activity, more relevant advertisements can be displayed.

[0051] When selling advertising space, the sales department can analyze the effectiveness of a company's past advertising and select an appropriate sales strategy. For example, when selling advertising space, the sales department analyzes the effectiveness of a company's past advertising and selects an appropriate sales strategy. For example, the sales department analyzes the effectiveness of a company's past advertising campaigns and selects the most effective sales strategy. The sales department can also select an optimal sales strategy by referring to the company's past advertising click-through rate. For example, the sales department analyzes the effectiveness of a company's past advertising campaigns and selects the most effective sales strategy. The sales department can also select an optimal sales strategy by referring to the company's past advertising click-through rate. In this way, an optimal sales strategy can be selected by analyzing the effectiveness of a company's past advertising.

[0052] The sales department can adjust the content of the advertising space based on the user's current areas of interest when selling the advertising space. For example, the sales department adjusts the content of the advertising space based on the user's current areas of interest when selling the advertising space. For example, the sales department suggests relevant advertising space based on keywords recently searched by the user. The sales department can also suggest advertising space of interest to the user by referring to the content of websites recently visited by the user. For example, the sales department suggests relevant advertising space based on keywords recently searched by the user. The sales department can also suggest advertising space of interest to the user by referring to the content of websites recently visited by the user. This enables more effective sales by customizing the content of the advertising space based on the user's current areas of interest.

[0053] The sales department can sell highly relevant advertising space by taking into account the user's geographical location information when selling advertising space. For example, the sales department sells highly relevant advertising space by taking into account the user's geographical location information when selling advertising space. For example, when a user is in a specific area, the sales department sells advertising space related to that area. Furthermore, when a user is traveling, the sales department can also sell advertising space including tourist information based on the user's current location. For example, when a user is in a specific area, the sales department sells advertising space related to that area. Furthermore, when a user is traveling, the sales department can also sell advertising space including tourist information based on the user's current location. In this way, by taking into account the user's geographical location information, more relevant advertising space can be sold.

[0054] The sales department can analyze the user's social media activity and sell relevant advertising space when selling advertising space. For example, the sales department analyzes the user's social media activity and sells relevant advertising space when selling advertising space. For example, the sales department sells relevant advertising space based on articles recently shared by the user on social media. The sales department can also sell relevant advertising space based on the topics of accounts the user follows on social media. For example, the sales department sells relevant advertising space based on articles recently shared by the user on social media. The sales department can also sell relevant advertising space based on the topics of accounts the user follows on social media. In this way, by analyzing the user's social media activity, more relevant advertising space can be sold.

[0055] The measurement unit can select an appropriate measurement method by analyzing a user's past ad click history when measuring the advertising effectiveness. For example, the measurement unit selects an appropriate measurement method by analyzing a user's past ad click history when measuring the advertising effectiveness. For example, the measurement unit selects the optimal measurement method based on the effectiveness of ads that the user has clicked in the past. The measurement unit can also select the most effective measurement method from the user's past click history. For example, the measurement unit selects the optimal measurement method based on the effectiveness of ads that the user has clicked in the past. The measurement unit can also select the most effective measurement method from the user's past click history. In this way, the optimal measurement method for measuring the advertising effectiveness can be selected by analyzing the user's past ad click history.

[0056] The measurement unit can measure highly relevant advertising effectiveness by taking into account the user's geographical location information when measuring advertising effectiveness. For example, the measurement unit measures highly relevant advertising effectiveness by taking into account the user's geographical location information when measuring advertising effectiveness. For example, when a user is in a specific area, the measurement unit measures advertising effectiveness related to the area. Furthermore, when a user is traveling, the measurement unit can also measure advertising effectiveness including tourist information based on the user's current location. For example, when a user is in a specific area, the measurement unit measures advertising effectiveness related to the area. Furthermore, when a user is traveling, the measurement unit can also measure advertising effectiveness including tourist information based on the user's current location. In this way, by taking into account the user's geographical location information, more relevant advertising effectiveness can be measured.

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

[0058] When generating an answer to a user's question, the generation unit can customize the answer by taking into account the user's past purchasing history. For example, the generation unit generates an answer that includes information related to products the user has purchased in the past. The generation unit can also suggest related new products or services based on products the user has purchased in the past. Furthermore, the generation unit can analyze the user's purchasing history and generate an answer that includes products or services that the user may be interested in. This makes it possible to provide a more personalized answer by taking into account the user's purchasing history.

[0059] When the sales department purchases response slots from the generation AI provider and sells them to companies, they can adjust the content of the ad slots based on the company's marketing strategy. For example, if a company is running a specific campaign, they can display ads related to that campaign. Or, if a company is releasing a new product, they can display ads related to that new product. Furthermore, if a company is targeting a specific target demographic, they can display ads tailored to that target demographic. This allows for more effective ad display by adjusting the content of the ad slots based on the company's marketing strategy.

[0060] When the generation AI generates an answer to a user's question and sets part of the answer frame as an advertising frame, the setting unit can display advertisements taking into account the user's current geographical location information. For example, if the user is in a specific area, advertisements related to that area can be displayed. Also, if the user is traveling, advertisements containing tourist information can be displayed based on the user's current location. Furthermore, if the user is participating in a specific event, advertisements related to that event can be displayed. In this way, by taking the user's geographical location information into consideration, more relevant advertisements can be displayed.

[0061] When embedding company information into an advertising space, the embedding unit can select an advertising design that matches the company's brand image. For example, for a luxury brand, an advertisement with a sophisticated design can be displayed. For a casual brand, an advertisement with a friendly design can be displayed. Furthermore, for an eco-brand, an advertisement with an environmentally friendly design can be displayed. This allows for more effective advertising display by selecting an advertising design that matches the company's brand image.

[0062] The customization unit may include a unit for measuring the effectiveness of the advertisement. For example, the customization unit may include a unit for measuring a click rate of the advertisement, and measure the click rate of the advertisement. The customization unit may also include a unit for measuring a conversion rate of the advertisement, and measure the conversion rate of the advertisement. Furthermore, the customization unit may include a unit for measuring the number of times the advertisement is displayed, and measure the number of times the advertisement is displayed. In this way, by measuring the effectiveness of the advertisement, the effectiveness of the advertisement can be evaluated and improved.

[0063] The generation unit can analyze the user's past question history and generate an appropriate answer. For example, if the user has asked a similar question in the past, the generation unit can generate a new answer by referring to the answer. The generation unit can also extract topics of interest from the user's past question history and generate an answer that includes information related to the topics. Furthermore, the generation unit can analyze the user's past question history and generate an answer that includes topics that the user is likely to be interested in. In this way, by analyzing the user's past question history, it is possible to provide a more appropriate answer.

[0064] When generating an answer, the generator may tailor the answer content based on the user's current areas of interest. For example, the generator may generate an answer containing relevant information based on keywords recently searched by the user. The generator may also generate an answer containing topics of interest to the user based on the content of websites recently visited by the user. Furthermore, the generator may generate an answer containing relevant information based on events recently attended by the user. This allows the generator to provide more relevant answers by customizing the answer content based on the user's current areas of interest.

[0065] The processing flow of the first embodiment will be briefly explained below.

[0066] Step 1: The generator generates an answer to the user's question. Using natural language processing technology and machine learning algorithms, the generator receives the user's question as input, learns from data on past questions and answers, and generates an answer to the new question. Step 2: The setting unit sets a part of the answer space generated by the generation unit as an advertisement space. The setting unit sets a part of the answer space as a banner advertisement or a text advertisement, and displays the advertisement as part of the answer to the user's question. Step 3: The embedding unit embeds the information of the investing company in the advertising space set by the setting unit. The embedding unit embeds the logo and product information of the investing company in the advertising space and displays it as part of the answer to the user's question. Step 4: The customization unit displays the advertisement embedded by the embedding unit based on the user's question and interests. The customization unit displays advertisements related to the user's question and interests. Step 5: The sales department purchases the ad space displayed by the customization department and sells it to the investing company. The sales department purchases the answer space from the provider of the generation AI and sells it to the investing company. The sales department can also accept purchases of ad space from the investing company and embed advertisements in the answer space of the generation AI.

[0067] (Example 2) An advertising space sales system according to an embodiment of the present invention sells answer spaces generated by a generation AI as advertising space. When a generation AI generates an answer to a user's question, this advertising space sales system sets a portion of the answer space as advertising space. Next, by embedding information about the investing company in the advertising space, the system can improve the company's image and promote its advertising effectiveness. For example, when a user inputs a question into the generation AI, an advertisement for the investing company is displayed as part of the answer. This advertisement is customized based on the user's interests, enabling effective advertising. Furthermore, SoftBank purchases this answer space from the provider of the generation AI and sells it to the investing company. This allows SoftBank to operate the answer space advertisements and generate revenue. Specifically, SoftBank accepts purchases of advertising space from the investing company and embeds advertisements in the generation AI's answer space. This advertisement is displayed based on the user's question content and interests, enabling effective advertising. This system allows SoftBank to improve its corporate image and promote its advertising effectiveness by utilizing the generation AI's answer space as advertising space, thereby generating revenue. This allows the advertising space sales system to utilize the response space generated by the generating AI as advertising space, thereby improving the company's image and achieving advertising effects.

[0068] An advertising space sales system according to an embodiment includes a generation unit, a setting unit, an embedding unit, a customization unit, and a sales unit. The generation unit generates an answer to a user's question. The generation unit generates an answer to the user's question using, for example, natural language processing technology. The generation unit can also generate an answer using a machine learning algorithm. For example, the generation unit receives a user's question as input and generates an answer using natural language processing technology. The generation unit can also use a machine learning algorithm to learn data on past questions and answers and generate an answer to a new question. The setting unit sets a portion of the answer space generated by the generation unit as an advertising space. For example, the setting unit sets a portion of the answer space as a banner advertisement. The setting unit can also set a portion of the answer space as a text advertisement. For example, the setting unit sets a portion of the answer space as a banner advertisement and displays an advertisement in a portion of the answer to the user's question. The setting unit can also set a portion of the answer space as a text advertisement and display a text advertisement in a portion of the answer to the user's question. The embedding unit embeds information about the investing company in the advertising space set by the setting unit. The embedding unit, for example, embeds the logo of the investing company in the advertising space. The embedding unit can also embed product information of the investing company in the advertising space. For example, the embedding unit embeds the logo of the investing company in the advertising space and displays it as part of the answer to the user's question. The embedding unit can also embed product information of the investing company in the advertising space and display it as part of the answer to the user's question. The customization unit displays the advertisement embedded by the embedding unit based on the content of the user's question and interests. The customization unit, for example, displays the advertisement based on the content of the user's question. The customization unit can also display the advertisement based on the user's interests. For example, the customization unit displays the advertisement based on the content of the user's question, and displays the advertisement related to the user's question. The customization unit can also display the advertisement based on the user's interests, and displays the advertisement related to the user's interests. The sales unit purchases the advertising space displayed by the customization unit and sells it to the investing company. The sales unit, for example, purchases the answer space from a provider of the generation AI and sells it to the investing company.The sales department can also accept purchases of advertising space from investing companies and embed advertisements in the answer spaces of the generation AI. For example, the sales department purchases answer spaces from the provider of the generation AI and sells them to investing companies. The sales department can also accept purchases of advertising space from investing companies and embed advertisements in the answer spaces of the generation AI. As a result, the advertising space sales system according to the embodiment can utilize the answer spaces of the generation AI as advertising spaces, thereby improving the company's image and achieving advertising effects.

[0069] The customization unit can display an advertisement based on the content of the user's question. The customization unit, for example, displays an advertisement based on the content of the user's question. For example, the customization unit extracts keywords related to the content of the user's question and displays an advertisement based on the keywords. The customization unit can also perform context analysis of the content of the user's question and display an advertisement based on the context. For example, the customization unit extracts keywords related to the content of the user's question and displays an advertisement based on the keywords. The customization unit can also perform context analysis of the content of the user's question and display an advertisement based on the context. This enables effective advertising by displaying an advertisement based on the content of the user's question and interests.

[0070] The sales department can purchase answer slots from the provider of the generation AI and sell them to companies. For example, the sales department purchases answer slots from the provider of the generation AI and sells them to companies. For example, the sales department purchases answer slots from the provider of the generation AI and sells them to companies. The sales department can also purchase answer slots from the provider of the generation AI and enter into a contract to sell them to companies. For example, the sales department purchases answer slots from the provider of the generation AI and sells them to companies. The sales department can also purchase answer slots from the provider of the generation AI and enter into a contract to sell them to companies. In this way, it is possible to monetize by purchasing answer slots from the provider of the generation AI and selling them to investing companies.

[0071] The setting unit can set a portion of the answer space as an advertising space when the generation AI generates an answer to a user's question. For example, when the generation AI generates an answer to a user's question, the setting unit sets a portion of the answer space as an advertising space. For example, when the generation AI generates an answer to a user's question, the setting unit sets a portion of the answer space as a banner advertisement. Furthermore, the setting unit can also set a portion of the answer space as a text advertisement when the generation AI generates an answer to a user's question. For example, when the generation AI generates an answer to a user's question, the setting unit sets a portion of the answer space as a banner advertisement. Furthermore, the setting unit can also set a portion of the answer space as a text advertisement when the generation AI generates an answer to a user's question. In this way, by setting an advertising space when the generation AI generates an answer, it becomes possible to display advertisements.

[0072] The embedding unit can embed company information into the advertising space. The embedding unit, for example, embeds company information into the advertising space. For example, the embedding unit embeds a company logo into the advertising space. The embedding unit can also embed company product information into the advertising space. For example, the embedding unit embeds a company logo into the advertising space and displays it as part of the answer to the user's question. The embedding unit can also embed company product information into the advertising space and display it as part of the answer to the user's question. In this way, by embedding information about the investing company into the advertising space, it is possible to improve the company's image and achieve advertising effects.

[0073] The customization unit may include a unit for measuring the effectiveness of the advertisement. The customization unit may include, for example, a unit for measuring the effectiveness of the advertisement. For example, the customization unit may include a unit for measuring a click rate of the advertisement. The customization unit may also include a unit for measuring a conversion rate of the advertisement. For example, the customization unit may include a unit for measuring a click rate of the advertisement, and measure the click rate of the advertisement. The customization unit may also include a unit for measuring a conversion rate of the advertisement, and measure the conversion rate of the advertisement. In this way, by measuring the effectiveness of the advertisement, the effectiveness of the advertisement can be evaluated and improved.

[0074] The generation unit can estimate the user's emotion and adjust the tone of the answer based on the estimated user's emotion. The generation unit, for example, estimates the user's emotion and adjusts the tone of the answer based on the estimated user's emotion. For example, if the user is feeling stressed, the generation unit generates an answer in a gentle tone that helps the user relax. Also, if the user is excited, the generation unit can generate an answer in an energetic tone. For example, if the user is feeling stressed, the generation unit generates an answer in a gentle tone that helps the user relax. Also, if the user is excited, the generation unit can generate an answer in an energetic tone. In this way, by adjusting the tone and style of the answer according to the user's emotion, it is possible to provide a more appropriate answer.

[0075] The generation unit can analyze the user's past question history and generate an appropriate answer. The generation unit, for example, analyzes the user's past question history and generates an appropriate answer. For example, if the user has asked a similar question in the past, the generation unit generates a new answer by referring to the answer. The generation unit can also extract a topic of interest from the user's past question history and generate an answer that includes information related to that topic. For example, if the user has asked a similar question in the past, the generation unit generates a new answer by referring to the answer. The generation unit can also extract a topic of interest from the user's past question history and generate an answer that includes information related to that topic. In this way, by analyzing the user's past question history, it is possible to provide a more appropriate answer.

[0076] The generation unit can adjust the content of the answer based on the user's current areas of interest when generating an answer. For example, the generation unit adjusts the content of the answer based on the user's current areas of interest when generating an answer. For example, the generation unit generates an answer including related information based on keywords recently searched by the user. The generation unit can also generate an answer including topics of interest by referring to the content of websites recently visited by the user. For example, the generation unit generates an answer including related information based on keywords recently searched by the user. The generation unit can also generate an answer including topics of interest by referring to the content of websites recently visited by the user. In this way, by customizing the content of the answer based on the user's current areas of interest, it is possible to provide a more relevant answer.

[0077] The generation unit can estimate the user's emotions and determine the order of answers based on the estimated user's emotions. The generation unit, for example, estimates the user's emotions and determines the order of answers based on the estimated user's emotions. For example, if the user asks an urgent question, the generation unit causes the generation AI to prioritize answering the question. Furthermore, the generation unit can also cause the generation AI to prioritize providing answers that include detailed information when the user is relaxed. For example, if the user asks an urgent question, the generation unit causes the generation AI to prioritize answering the question. Furthermore, the generation unit can cause the generation AI to prioritize providing answers that include detailed information when the user is relaxed. In this way, by determining the priority of answers based on the user's emotions, more appropriate answers can be provided.

[0078] The generation unit can provide highly relevant information based on the user's geographical location information when generating an answer. The generation unit, for example, provides highly relevant information based on the user's geographical location information when generating an answer. For example, when the user is in a specific area, the generation unit generates an answer that includes information related to the area. Furthermore, when the user is traveling, the generation unit can also generate an answer that includes tourist information based on the user's current location. For example, when the user is in a specific area, the generation unit generates an answer that includes information related to the area. Furthermore, when the user is traveling, the generation unit can also generate an answer that includes tourist information based on the user's current location. In this way, by taking the user's geographical location information into consideration, more relevant information can be provided.

[0079] The generation unit can analyze the user's social media activity and provide related information when generating an answer. For example, the generation unit can analyze the user's social media activity and provide related information when generating an answer. For example, the generation unit can generate an answer including related information based on articles recently shared by the user on social media. The generation unit can also generate an answer including related information based on topics of accounts the user follows on social media. For example, the generation unit can generate an answer including related information based on articles recently shared by the user on social media. The generation unit can also generate an answer including related information based on topics of accounts the user follows on social media. In this way, by analyzing the user's social media activity, more relevant information can be provided.

[0080] The setting unit can estimate the user's emotions and adjust the position of the advertisement space based on the estimated user's emotions. The setting unit, for example, estimates the user's emotions and adjusts the position of the advertisement space based on the estimated user's emotions. For example, when the user is relaxed, the setting unit places the advertisement space in an inconspicuous position. Furthermore, when the user is excited, the setting unit can also place the advertisement space in a conspicuous position. For example, when the user is relaxed, the setting unit places the advertisement space in an inconspicuous position. Furthermore, when the user is excited, the setting unit can also place the advertisement space in a conspicuous position. In this way, by adjusting the placement of the advertisement space based on the user's emotions, more effective advertisement display is possible.

[0081] When setting an ad space, the setting unit can analyze a user's past ad click history and select an appropriate placement. When setting an ad space, the setting unit, for example, analyzes a user's past ad click history and selects an appropriate placement. For example, the setting unit refers to the positions of ads that the user has clicked in the past and places the ad space in a similar position. The setting unit can also place the ad space in the most effective position based on the user's past click history. For example, the setting unit refers to the positions of ads that the user has clicked in the past and places the ad space in a similar position. The setting unit can also place the ad space in the most effective position based on the user's past click history. In this way, by analyzing a user's past ad click history, it is possible to place the optimal ad space.

[0082] The setting unit can adjust the content of the ad space based on the user's current areas of interest when setting the ad space. For example, the setting unit adjusts the content of the ad space based on the user's current areas of interest when setting the ad space. For example, the setting unit displays relevant advertisements based on keywords recently searched by the user. The setting unit can also display advertisements of interest to the user by referring to the content of websites recently visited by the user. For example, the setting unit displays relevant advertisements based on keywords recently searched by the user. The setting unit can also display advertisements of interest to the user by referring to the content of websites recently visited by the user. This enables more effective ad display by customizing the content of the ad space based on the user's current areas of interest.

[0083] The setting unit can estimate the user's emotions and adjust the number of times the ad slots are displayed based on the estimated user's emotions. The setting unit, for example, estimates the user's emotions and adjusts the number of times the ad slots are displayed based on the estimated user's emotions. For example, the setting unit sets the display frequency of the ad slots low when the user is relaxed. The setting unit can also set the display frequency of the ad slots high when the user is excited. For example, the setting unit sets the display frequency of the ad slots low when the user is relaxed. The setting unit can also set the display frequency of the ad slots high when the user is excited. In this way, by adjusting the display frequency of the ad slots based on the user's emotions, more effective ad display is possible.

[0084] The setting unit can display highly relevant advertisements based on the user's geographical location information when setting an advertisement space. The setting unit, for example, displays highly relevant advertisements based on the user's geographical location information when setting an advertisement space. For example, when the user is in a specific area, the setting unit displays advertisements related to the area. Furthermore, when the user is traveling, the setting unit can also display advertisements including tourist information based on the user's current location. For example, when the user is in a specific area, the setting unit displays advertisements related to the area. Furthermore, when the user is traveling, the setting unit can also display advertisements including tourist information based on the user's current location. In this way, by taking the user's geographical location information into consideration, more relevant advertisements can be displayed.

[0085] The setting unit can analyze the user's social media activity and display relevant advertisements when setting an advertisement slot. The setting unit, for example, analyzes the user's social media activity and displays relevant advertisements when setting an advertisement slot. For example, the setting unit displays relevant advertisements based on articles recently shared by the user on social media. The setting unit can also display relevant advertisements based on topics of accounts the user follows on social media. For example, the setting unit displays relevant advertisements based on articles recently shared by the user on social media. The setting unit can also display relevant advertisements based on topics of accounts the user follows on social media. In this way, by analyzing the user's social media activity, more relevant advertisements can be displayed.

[0086] The embedding unit can estimate the user's emotion and adjust the content of the advertisement based on the estimated user's emotion. The embedding unit, for example, estimates the user's emotion and adjusts the content of the advertisement based on the estimated user's emotion. For example, the embedding unit can display advertisement content in a calm tone when the user is relaxed. Also, the embedding unit can display advertisement content in an energetic tone when the user is excited. For example, the embedding unit can display advertisement content in a calm tone when the user is relaxed. Also, the embedding unit can display advertisement content in an energetic tone when the user is excited. In this way, by adjusting the advertisement content based on the user's emotion, more effective advertisement display is possible.

[0087] The embedding unit can select appropriate content by analyzing the company's past advertising effectiveness when embedding advertising content. For example, the embedding unit analyzes the company's past advertising effectiveness when embedding advertising content and selects appropriate content. For example, the embedding unit analyzes the effectiveness of the company's past advertising campaigns and selects the most effective content. The embedding unit can also select optimal advertising content by referring to the company's past advertising click-through rate. For example, the embedding unit analyzes the effectiveness of the company's past advertising campaigns and selects the most effective content. The embedding unit can also select optimal advertising content by referring to the company's past advertising click-through rate. In this way, optimal advertising content can be selected by analyzing the company's past advertising effectiveness.

[0088] The embedding unit may adjust the content of the advertisement based on the user's current areas of interest when embedding the advertisement content. For example, the embedding unit may adjust the content of the advertisement based on the user's current areas of interest when embedding the advertisement content. For example, the embedding unit may display relevant advertisement content based on keywords recently searched by the user. The embedding unit may also display advertisement content of interest to the user by referring to the content of websites recently visited by the user. For example, the embedding unit may display relevant advertisement content based on keywords recently searched by the user. The embedding unit may also display advertisement content of interest to the user by referring to the content of websites recently visited by the user. This allows for more effective advertisement display by customizing the advertisement content based on the user's current areas of interest.

[0089] The embedding unit can estimate the user's emotion and adjust the advertisement display method based on the estimated user's emotion. The embedding unit, for example, estimates the user's emotion and adjusts the advertisement display method based on the estimated user's emotion. For example, the embedding unit can display advertisement content in a calm tone when the user is relaxed. Also, the embedding unit can display advertisement content in an energetic tone when the user is excited. For example, the embedding unit can display advertisement content in a calm tone when the user is relaxed. Also, the embedding unit can display advertisement content in an energetic tone when the user is excited. In this way, by adjusting the advertisement display method based on the user's emotion, more effective advertisement display is possible.

[0090] The embedding unit can prioritize displaying highly relevant advertisements by taking into consideration the user's geographical location information when embedding advertisement content. For example, the embedding unit prioritizes displaying highly relevant advertisements by taking into consideration the user's geographical location information when embedding advertisement content. For example, when the user is in a specific area, the embedding unit displays advertisements related to the area. Furthermore, when the user is traveling, the embedding unit can also display advertisements including tourist information based on the user's current location. For example, when the user is in a specific area, the embedding unit displays advertisements related to the area. Furthermore, when the user is traveling, the embedding unit can also display advertisements including tourist information based on the user's current location. In this way, more relevant advertisements can be displayed by taking into consideration the user's geographical location information.

[0091] The embedding unit can analyze the user's social media activity and display relevant advertisements when embedding the advertisement content. For example, the embedding unit analyzes the user's social media activity and display relevant advertisements when embedding the advertisement content. For example, the embedding unit displays relevant advertisements based on articles recently shared by the user on social media. The embedding unit can also display relevant advertisements based on topics of accounts the user follows on social media. For example, the embedding unit displays relevant advertisements based on articles recently shared by the user on social media. The embedding unit can also display relevant advertisements based on topics of accounts the user follows on social media. In this way, by analyzing the user's social media activity, more relevant advertisements can be displayed.

[0092] The customization unit can estimate the user's emotions and adjust the advertisement display method based on the estimated user's emotions. The customization unit, for example, estimates the user's emotions and adjusts the advertisement display method based on the estimated user's emotions. For example, the customization unit can display the advertisement in a calm tone when the user is relaxed. Also, the customization unit can display the advertisement in an energetic tone when the user is excited. For example, the customization unit can display the advertisement in a calm tone when the user is relaxed. Also, the customization unit can display the advertisement in an energetic tone when the user is excited. In this way, by adjusting the advertisement display method based on the user's emotions, more effective advertisement display is possible.

[0093] When customizing an advertisement, the customization unit can analyze the user's past ad click history and select an appropriate display method. For example, when customizing an advertisement, the customization unit analyzes the user's past ad click history and selects an appropriate display method. For example, the customization unit refers to the display method of an advertisement that the user has clicked in the past and displays the advertisement in a similar manner. The customization unit can also select the most effective display method from the user's past click history. For example, the customization unit refers to the display method of an advertisement that the user has clicked in the past and displays the advertisement in a similar manner. The customization unit can also select the most effective display method from the user's past click history. In this way, the optimal advertisement display method can be selected by analyzing the user's past ad click history.

[0094] The customization unit may adjust the content of the advertisement based on the user's current areas of interest when customizing the advertisement. For example, the customization unit may adjust the content of the advertisement based on the user's current areas of interest when customizing the advertisement. For example, the customization unit may display relevant advertisement content based on keywords recently searched by the user. The customization unit may also display advertisement content of interest to the user based on content of websites recently visited by the user. For example, the customization unit may display relevant advertisement content based on keywords recently searched by the user. The customization unit may also display advertisement content of interest to the user based on content of websites recently visited by the user. This allows for more effective advertisement display by customizing advertisement content based on the user's current areas of interest.

[0095] The customization unit can estimate the user's emotions and adjust the number of times an advertisement is displayed based on the estimated user's emotions. The customization unit, for example, estimates the user's emotions and adjusts the number of times an advertisement is displayed based on the estimated user's emotions. For example, the customization unit sets the advertisement display frequency low when the user is relaxed. The customization unit can also set the advertisement display frequency high when the user is excited. For example, the customization unit sets the advertisement display frequency low when the user is relaxed. The customization unit can also set the advertisement display frequency high when the user is excited. In this way, adjusting the advertisement display frequency based on the user's emotions enables more effective advertisement display.

[0096] The customization unit can prioritize displaying highly relevant advertisements by taking into consideration the user's geographical location information when customizing advertisements. For example, the customization unit prioritizes displaying highly relevant advertisements by taking into consideration the user's geographical location information when customizing advertisements. For example, when the user is in a specific area, the customization unit displays advertisements related to the area. Furthermore, when the user is traveling, the customization unit can also display advertisements including tourist information based on the user's current location. For example, when the user is in a specific area, the customization unit displays advertisements related to the area. Furthermore, when the user is traveling, the customization unit can also display advertisements including tourist information based on the user's current location. In this way, by taking into consideration the user's geographical location information, more relevant advertisements can be displayed.

[0097] The customization unit may analyze the user's social media activity and display relevant advertisements when customizing advertisements. For example, the customization unit may analyze the user's social media activity and display relevant advertisements when customizing advertisements. For example, the customization unit may display relevant advertisements based on articles recently shared by the user on social media. The customization unit may also display relevant advertisements based on topics of accounts the user follows on social media. For example, the customization unit may display relevant advertisements based on articles recently shared by the user on social media. The customization unit may also display relevant advertisements based on topics of accounts the user follows on social media. In this way, by analyzing the user's social media activity, more relevant advertisements can be displayed.

[0098] The sales department can estimate the user's emotions and adjust the sales strategy for the advertising space based on the estimated user's emotions. The sales department, for example, estimates the user's emotions and adjusts the sales strategy for the advertising space based on the estimated user's emotions. For example, if the user is relaxed, the sales department can propose the sale of the advertising space in a calm tone. Also, if the user is excited, the sales department can propose the sale of the advertising space in an energetic tone. For example, if the user is relaxed, the sales department can propose the sale of the advertising space in a calm tone. Also, if the user is excited, the sales department can propose the sale of the advertising space in an energetic tone. In this way, by adjusting the sales strategy for the advertising space based on the user's emotions, more effective sales are possible.

[0099] When selling advertising space, the sales department can analyze the effectiveness of a company's past advertising and select an appropriate sales strategy. For example, when selling advertising space, the sales department analyzes the effectiveness of a company's past advertising and selects an appropriate sales strategy. For example, the sales department analyzes the effectiveness of a company's past advertising campaigns and selects the most effective sales strategy. The sales department can also select an optimal sales strategy by referring to the company's past advertising click-through rate. For example, the sales department analyzes the effectiveness of a company's past advertising campaigns and selects the most effective sales strategy. The sales department can also select an optimal sales strategy by referring to the company's past advertising click-through rate. In this way, an optimal sales strategy can be selected by analyzing the effectiveness of a company's past advertising.

[0100] The sales department can adjust the content of the advertising space based on the user's current areas of interest when selling the advertising space. For example, the sales department adjusts the content of the advertising space based on the user's current areas of interest when selling the advertising space. For example, the sales department suggests relevant advertising space based on keywords recently searched by the user. The sales department can also suggest advertising space of interest to the user by referring to the content of websites recently visited by the user. For example, the sales department suggests relevant advertising space based on keywords recently searched by the user. The sales department can also suggest advertising space of interest to the user by referring to the content of websites recently visited by the user. This enables more effective sales by customizing the content of the advertising space based on the user's current areas of interest.

[0101] The sales department can estimate the user's emotions and adjust the price of the advertising space based on the estimated user's emotions. The sales department, for example, estimates the user's emotions and adjusts the price of the advertising space based on the estimated user's emotions. For example, the sales department sets the selling price of the advertising space low when the user is relaxed. Also, the sales department can set the selling price of the advertising space high when the user is excited. For example, the sales department sets the selling price of the advertising space low when the user is relaxed. Also, the sales department can set the selling price of the advertising space high when the user is excited. In this way, adjusting the selling price of the advertising space based on the user's emotions enables more effective sales.

[0102] The sales department can sell highly relevant advertising space by taking into account the user's geographical location information when selling advertising space. For example, the sales department sells highly relevant advertising space by taking into account the user's geographical location information when selling advertising space. For example, when a user is in a specific area, the sales department sells advertising space related to that area. Furthermore, when a user is traveling, the sales department can also sell advertising space including tourist information based on the user's current location. For example, when a user is in a specific area, the sales department sells advertising space related to that area. Furthermore, when a user is traveling, the sales department can also sell advertising space including tourist information based on the user's current location. In this way, by taking into account the user's geographical location information, more relevant advertising space can be sold.

[0103] The sales department can analyze the user's social media activity and sell relevant advertising space when selling advertising space. For example, the sales department analyzes the user's social media activity and sells relevant advertising space when selling advertising space. For example, the sales department sells relevant advertising space based on articles recently shared by the user on social media. The sales department can also sell relevant advertising space based on the topics of accounts the user follows on social media. For example, the sales department sells relevant advertising space based on articles recently shared by the user on social media. The sales department can also sell relevant advertising space based on the topics of accounts the user follows on social media. In this way, by analyzing the user's social media activity, more relevant advertising space can be sold.

[0104] The measurement unit can estimate the user's emotions and adjust the method for measuring the advertising effectiveness based on the estimated user's emotions. The measurement unit, for example, estimates the user's emotions and adjusts the method for measuring the advertising effectiveness based on the estimated user's emotions. For example, the measurement unit measures the advertising effectiveness with a calm tone when the user is relaxed. Also, the measurement unit can measure the advertising effectiveness with an energetic tone when the user is excited. For example, the measurement unit measures the advertising effectiveness with a calm tone when the user is relaxed. Also, the measurement unit can measure the advertising effectiveness with an energetic tone when the user is excited. In this way, by adjusting the method for measuring the advertising effectiveness based on the user's emotions, it is possible to measure the advertising effectiveness more accurately.

[0105] The measurement unit can select an appropriate measurement method by analyzing a user's past ad click history when measuring the advertising effectiveness. For example, the measurement unit selects an appropriate measurement method by analyzing a user's past ad click history when measuring the advertising effectiveness. For example, the measurement unit selects the optimal measurement method based on the effectiveness of ads that the user has clicked in the past. The measurement unit can also select the most effective measurement method from the user's past click history. For example, the measurement unit selects the optimal measurement method based on the effectiveness of ads that the user has clicked in the past. The measurement unit can also select the most effective measurement method from the user's past click history. In this way, the optimal measurement method for measuring the advertising effectiveness can be selected by analyzing the user's past ad click history.

[0106] The measurement unit can estimate the user's emotions and adjust the number of times the advertising effectiveness is measured based on the estimated user's emotions. The measurement unit, for example, estimates the user's emotions and adjusts the number of times the advertising effectiveness is measured based on the estimated user's emotions. For example, the measurement unit sets the frequency of measuring the advertising effectiveness low when the user is relaxed. The measurement unit can also set the frequency of measuring the advertising effectiveness high when the user is excited. For example, the measurement unit sets the frequency of measuring the advertising effectiveness low when the user is relaxed. The measurement unit can also set the frequency of measuring the advertising effectiveness high when the user is excited. In this way, by adjusting the frequency of measuring the advertising effectiveness based on the user's emotions, more accurate measurement of the advertising effectiveness is possible.

[0107] The measurement unit can measure highly relevant advertising effectiveness by taking into account the user's geographical location information when measuring advertising effectiveness. For example, the measurement unit measures highly relevant advertising effectiveness by taking into account the user's geographical location information when measuring advertising effectiveness. For example, when a user is in a specific area, the measurement unit measures advertising effectiveness related to the area. Furthermore, when a user is traveling, the measurement unit can also measure advertising effectiveness including tourist information based on the user's current location. For example, when a user is in a specific area, the measurement unit measures advertising effectiveness related to the area. Furthermore, when a user is traveling, the measurement unit can also measure advertising effectiveness including tourist information based on the user's current location. In this way, by taking into account the user's geographical location information, more relevant advertising effectiveness can be measured. === Hard Collateral 1-1 === Each of the multiple elements including the generation unit, setting unit, embedding unit, customization unit, and sales unit described above is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates an answer to a user's question. The setting unit is realized, for example, by the control unit 46A of the smart device 14 and sets a part of the generated answer frame as an advertisement frame. The embedding unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and embeds information of the investing company in the set advertisement frame. The customization unit is realized, for example, by the control unit 46A of the smart device 14 and displays the embedded advertisement based on the content of the user's question and interests. The sales unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and purchases advertisement frames and sells them to the investing company. === Hard Collateral 1-2 === Each of the multiple elements including the above-mentioned generation unit, setting unit, embedding unit, customization unit, and sales unit is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates an answer to a user's question. The setting unit is realized, for example, by the control unit 46A of the smart glasses 214 and sets a part of the generated answer frame as an advertisement frame. The embedding unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and embeds information of the investing company in the set advertisement frame. The customization unit is realized, for example, by the control unit 46A of the smart glasses 214 and displays the embedded advertisement based on the content of the user's question and interests. The sales unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and purchases advertisement frames and sells them to the investing company. === Hard Collateral 1-3 === Each of the multiple elements including the above-mentioned generation unit, setting unit, embedding unit, customization unit, and sales unit is realized, for example, by at least one of the headset type terminal 314 and the data processing device 12. For example, the generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates an answer to a user's question. The setting unit is realized, for example, by the control unit 46A of the headset type terminal 314 and sets a part of the generated answer frame as an advertisement frame. The embedding unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and embeds information of the investing company in the set advertisement frame. The customization unit is realized, for example, by the control unit 46A of the headset type terminal 314 and displays the embedded advertisement based on the content of the user's question and interests. The sales unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and purchases advertisement frames and sells them to the investing company. === Hard Collateral 1-4 === Each of the multiple elements including the above-mentioned generation unit, setting unit, embedding unit, customization unit, and sales unit is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates an answer to a user's question. The setting unit is realized, for example, by the control unit 46A of the robot 414 and sets a part of the generated answer frame as an advertisement frame. The embedding unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and embeds information of the investing company in the set advertisement frame. The customization unit is realized, for example, by the control unit 46A of the robot 414 and displays the embedded advertisement based on the content of the user's question and interests. The sales unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and purchases advertisement frames and sells them to the investing company.

[0108] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0109] When generating an answer to a user's question, the generation unit can customize the answer by taking into account the user's past purchasing history. For example, the generation unit generates an answer that includes information related to products the user has purchased in the past. The generation unit can also suggest related new products or services based on products the user has purchased in the past. Furthermore, the generation unit can analyze the user's purchasing history and generate an answer that includes products or services that the user may be interested in. This makes it possible to provide a more personalized answer by taking into account the user's purchasing history.

[0110] When displaying advertisements based on the content of the user's question, the customization unit can estimate the user's current mood and display advertisements that match that mood. For example, if the user is feeling stressed, advertisements for products and services that will help them relax can be displayed. If the user is excited, advertisements for products and services that will energize the user can be displayed. Furthermore, if the user is sad, advertisements that will brighten the user's mood can be displayed. This allows for more effective advertisement display by displaying advertisements that match the user's mood.

[0111] When the sales department purchases response slots from the generation AI provider and sells them to companies, they can adjust the content of the ad slots based on the company's marketing strategy. For example, if a company is running a specific campaign, they can display ads related to that campaign. Or, if a company is releasing a new product, they can display ads related to that new product. Furthermore, if a company is targeting a specific target demographic, they can display ads tailored to that target demographic. This allows for more effective ad display by adjusting the content of the ad slots based on the company's marketing strategy.

[0112] When the generation AI generates an answer to a user's question and sets part of the answer frame as an advertising frame, the setting unit can display advertisements taking into account the user's current geographical location information. For example, if the user is in a specific area, advertisements related to that area can be displayed. Also, if the user is traveling, advertisements containing tourist information can be displayed based on the user's current location. Furthermore, if the user is participating in a specific event, advertisements related to that event can be displayed. In this way, by taking the user's geographical location information into consideration, more relevant advertisements can be displayed.

[0113] When embedding company information into an advertising space, the embedding unit can select an advertising design that matches the company's brand image. For example, for a luxury brand, an advertisement with a sophisticated design can be displayed. For a casual brand, an advertisement with a friendly design can be displayed. Furthermore, for an eco-brand, an advertisement with an environmentally friendly design can be displayed. This allows for more effective advertising display by selecting an advertising design that matches the company's brand image.

[0114] The customization unit may include a unit for measuring the effectiveness of the advertisement. For example, the customization unit may include a unit for measuring a click rate of the advertisement, and measure the click rate of the advertisement. The customization unit may also include a unit for measuring a conversion rate of the advertisement, and measure the conversion rate of the advertisement. Furthermore, the customization unit may include a unit for measuring the number of times the advertisement is displayed, and measure the number of times the advertisement is displayed. In this way, by measuring the effectiveness of the advertisement, the effectiveness of the advertisement can be evaluated and improved.

[0115] The generation unit can estimate the user's emotions and adjust the tone of the answer based on the estimated user's emotions. For example, if the user is feeling stressed, the generation unit can generate an answer in a gentle tone that helps the user relax. If the user is excited, the generation unit can also generate an answer in an energetic tone. Furthermore, if the user is sad, the generation unit can also generate an answer in a comforting tone. This makes it possible to provide a more appropriate answer by adjusting the tone and style of the answer according to the user's emotions.

[0116] The generation unit can analyze the user's past question history and generate an appropriate answer. For example, if the user has asked a similar question in the past, the generation unit can generate a new answer by referring to the answer. The generation unit can also extract topics of interest from the user's past question history and generate an answer that includes information related to the topics. Furthermore, the generation unit can analyze the user's past question history and generate an answer that includes topics that the user is likely to be interested in. In this way, by analyzing the user's past question history, it is possible to provide a more appropriate answer.

[0117] When generating an answer, the generator may tailor the answer content based on the user's current areas of interest. For example, the generator may generate an answer containing relevant information based on keywords recently searched by the user. The generator may also generate an answer containing topics of interest to the user based on the content of websites recently visited by the user. Furthermore, the generator may generate an answer containing relevant information based on events recently attended by the user. This allows the generator to provide more relevant answers by customizing the answer content based on the user's current areas of interest.

[0118] The generation unit can estimate the user's emotions and determine the order of answers based on the estimated user's emotions. For example, if the user asks an urgent question, the generation unit can cause the generation AI to prioritize answers to that question. Also, if the user is relaxed, the generation unit can cause the generation AI to prioritize answers that include detailed information. Furthermore, if the user is excited, the generation unit can cause the generation AI to provide answers in an energetic tone. This makes it possible to provide more appropriate answers by determining the priority of answers based on the user's emotions.

[0119] The processing flow of the second embodiment will be briefly explained below.

[0120] Step 1: The generator generates an answer to the user's question. Using natural language processing technology and machine learning algorithms, the generator receives the user's question as input, learns from data on past questions and answers, and generates an answer to the new question. Step 2: The setting unit sets a part of the answer space generated by the generation unit as an advertisement space. The setting unit sets a part of the answer space as a banner advertisement or a text advertisement, and displays the advertisement as part of the answer to the user's question. Step 3: The embedding unit embeds the information of the investing company in the advertising space set by the setting unit. The embedding unit embeds the logo and product information of the investing company in the advertising space and displays it as part of the answer to the user's question. Step 4: The customization unit displays the advertisement embedded by the embedding unit based on the user's question and interests. The customization unit displays advertisements related to the user's question and interests. Step 5: The sales department purchases the ad space displayed by the customization department and sells it to the investing company. The sales department purchases the answer space from the provider of the generation AI and sells it to the investing company. The sales department can also accept purchases of ad space from the investing company and embed advertisements in the answer space of the generation AI.

[0121] 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.

[0122] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of the generative AI include a neural network (NN) and a neural network (NN). The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, image data, etc. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and may perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-mentioned parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. The processing performed by an AI including the generative AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI including the generative AI.

[0123] 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.

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

[0125] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0126] 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.

[0127] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0128] The 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.

[0129] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0130] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0131] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0132] Fig. 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.

[0133] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0134] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0135] In the 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.

[0136] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0137] The specific processing unit 290 transmits the result of the specific processing to the 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.

[0138] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0139] The data processing system 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.

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

[0141] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0142] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0143] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0144] The 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.

[0145] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0146] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (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).

[0147] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0152] 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.

[0153] 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.

[0154] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0155] 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.

[0156] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0157] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0158] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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).

[0163] 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.

[0164] 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.

[0165] 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.

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

[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 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.

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

[0172] 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.

[0173] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] 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).

[0178] 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.

[0179] 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."

[0180] 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.

[0181] 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.

[0182] 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.

[0183] 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.

[0184] 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.

[0185] 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.

[0186] 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.

[0187] 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.

[0188] 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.

[0189] 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.

[0190] 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.

[0191] 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.

[0192] [Explanation of symbols]

[0193] 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 generator that generates an answer to a user's question; a setting unit that sets a part of the answer space generated by the generation unit as an advertisement space; an embedding unit that embeds company information in the advertisement space set by the setting unit; a customization unit that displays the advertisement embedded by the embedding unit based on the content of a user's question; a sales department that purchases the advertising space displayed by the customization department and sells it to companies. A system characterized by:

2. The customization unit Display ads based on user questions 2. The system of claim 1.

3. The sales department Purchase answer slots from generator AI providers and sell them to companies 2. The system of claim 1.

4. The setting unit When the generation AI generates an answer to a user's question, a part of the answer frame is set as an advertising frame.

2. The system of claim 1.

5. The embedded portion is Embedding company information into ad space 2. The system of claim 1.

6. The customization unit Equipped with a section for measuring the effectiveness of advertising 2. The system of claim 1.

7. The generation unit Infer user sentiment and adjust the tone of responses based on the inferred sentiment 2. The system of claim 1.

8. The generation unit Analyze the user's past question history and generate appropriate answers 2. The system of claim 1.

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