system

Abstract

We provide the system. [Solution] A means of automatically collecting publicly available data, including technical information, A means for analyzing the aforementioned publicly available data and evaluating its relevance to customer organizations, A means for identifying the person in charge within the customer organization based on the aforementioned analysis, A means for generating information to propose products or services to the aforementioned person in charge, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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 Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 Corporate sales representatives are required to quickly and accurately grasp customer organization information and contact information. However, it is very difficult to extract useful information related to customers from the vast amount of information publicly available on the web. Also, the process of identifying appropriate contacts within the customer organization and proposing optimal products and services is complex, leading to inefficiencies in sales activities. 【Means for Solving the Problems】 【0005】 To solve these problems, the present invention provides means for automatically collecting publicly available data, including technical information, and means for analyzing that data to evaluate its relevance to customer organizations. Furthermore, it provides means for identifying relevant personnel within customer organizations based on the analysis, and a system for generating information to propose products or services to those personnel. This enables sales representatives to conduct sales activities efficiently. 【0006】 "Technical information" refers to knowledge and data related to industry and science, and includes detailed information about new technologies, processes, and products. 【0007】 "Public data" refers to information that is freely accessible on the internet or other public spaces and can be used without specific restrictions. 【0008】 "Means of automatic data collection" refers to methods and processes by which a system independently acquires and collects data without requiring manual operation. 【0009】 "Analysis" refers to the act of logically classifying and interpreting collected data to derive useful information and patterns. 【0010】 "Customer organization" refers to the companies or groups that sales representatives propose to, and is a concept that includes their internal structure and stakeholders. 【0011】 "Assessing relevance" refers to the process of establishing criteria for determining the degree of relevance between specific information and a customer organization, and then making a determination according to those criteria. 【0012】 "Means of identifying the person in charge" refers to methods and technologies for identifying individuals with strong relationships within a customer organization. 【0013】 "Information for proposing products or services" refers to materials and data used in sales activities, and is strategically used in approaching customers. [Brief explanation of the drawing] 【0014】 [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【Embodiments for Carrying Out the Invention】 【0015】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0016】 First, the terms used in the following description will be described. 【0017】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units 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), and the like. 【0018】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0019】 In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like. 【0020】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0021】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0022】 [First Embodiment] 【0023】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0024】 As shown in Figure 1, the 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. 【0025】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0026】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0027】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0028】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0029】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0030】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0031】 As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0032】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0033】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0034】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0035】 This invention is a system designed to support specific corporate sales activities and is implemented through a configuration centered on a server, terminals, and users. The server has high-speed processing capabilities and automatically collects publicly available data, including large amounts of technical information. This enables reliable and rapid acquisition of the information users need. The server also uses advanced algorithms and generative AI to analyze the collected data, evaluate the relevance of the data, and organize the information so that users can use it efficiently. 【0036】 Specifically, the server first crawls websites and databases on the internet to extract necessary technical information. This includes filtering useful and relevant information from publicly available data that is regularly updated. Next, the server analyzes the retrieved information to identify the appropriate person within the customer organization. This provides a foundation for suggesting information about the most suitable products or services for the target customer. 【0037】 Sales representatives, as users, receive analysis results from the server via their terminals. They then use this information to create proposals and sales materials, and conduct concrete sales activities. The proposals generated by the server are customized according to customer needs, supporting users in conducting sales activities efficiently. This system utilizes a digital business card management function to facilitate updating and managing customer information, and can perform more precise data analysis in conjunction with the server. 【0038】 As a concrete example, consider a scenario where a sales representative is looking for customers interested in a new cloud technology. The server collects the latest conference presentations on relevant technical information and identifies recommended experts from a publicly available list. Subsequently, proposals generated by the server are sent to the terminal, allowing the user to quickly and accurately engage in sales activities with customers. In this way, the system of the present invention significantly improves the efficiency of sales activities. 【0039】 The following describes the processing flow. 【0040】 Step 1: 【0041】 The server collects publicly available data. 【0042】 The server uses a web crawler to visit websites containing academic presentations and news articles at a set frequency, automatically collecting articles that include technical information. During this process, natural language processing technology is used to extract relevant keywords from the articles and tag them to determine their importance. 【0043】 Step 2: 【0044】 The server analyzes the data. 【0045】 The server compares the collected information with data in the digital business card management system. Using customer names and related keywords, it searches for past business negotiation history and contact person information, and uses generating AI to evaluate the relevance of the information. This identifies information that is beneficial to the customer. 【0046】 Step 3: 【0047】 The server identifies the person in charge. 【0048】 Based on the analysis results, the server lists the contacts with strong relationships within the customer organization. Using a generative AI model, it identifies the names and titles of appropriate contacts from publicly available information and business card data, and stores this information in a database for use in sales activities. 【0049】 Step 4: 【0050】 The server generates the suggestion information. 【0051】 The server generates materials to suggest appropriate products and services based on information related to the identified person in charge. This allows the user to take the most effective approach to the customer. 【0052】 Step 5: 【0053】 The device provides information to the user. 【0054】 The terminal receives proposal details and contact person information generated from the server and presents them to the user. Based on this data, the user can create proposals and other materials necessary for sales activities and make concrete sales approaches to customers. 【0055】 (Example 1) 【0056】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0057】 Modern sales activities require the rapid and efficient acquisition of highly relevant information from a vast amount of technical data, but traditional methods fail to adequately achieve this. In particular, data collection and analysis for creating specific proposal materials needed by sales representatives are cumbersome and time-consuming. Therefore, a system is needed to automate information selection and the generation of customized proposals, thereby supporting efficient sales activities. 【0058】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0059】 In this invention, the server includes means for automatically collecting publicly available data, including technical information; means for filtering the publicly available data using a generating AI model and selecting highly relevant information; and means for analyzing the filtered data and evaluating its relevance to customer organizations. This enables sales representatives to quickly collect the information they need and engage in accurate proposal activities. 【0060】 "Technical information" refers to data and knowledge related to science and technology, and includes research results, technical specifications, patent documents, etc. 【0061】 "Public data" refers to information that is generally accessible on the internet or other resources, and is provided in a form that anyone can use. 【0062】 A "generative AI model" is a mathematical model that uses artificial intelligence to generate new output from data, and is built on machine learning and deep learning technologies. 【0063】 "Filtering" refers to the process of selecting specific information from collected data as needed and excluding other information. 【0064】 "Analysis" is the process of thoroughly investigating and studying collected data to find useful information and patterns within it. 【0065】 A "customer organization" refers to the companies or groups that are the target of sales activities, and the recipients of goods and services. 【0066】 "Responsible person" refers to an individual within a client organization who is responsible for a specific task or project. 【0067】 "Proposal details" refers to information that summarizes the details, benefits, and usage methods of products and services presented to customers during sales or business negotiations. 【0068】 This invention is a system designed to support sales activities and is centered around a server, terminals, and users. Specific embodiments are shown below. 【0069】 The server possesses high-speed processing capabilities and automatically collects technical information from websites and databases on the internet using programming languages ​​such as Python and R. Specific software used here includes Beautiful Soup and Scrapy for data scraping. Using these tools, the server extracts relevant technical information based on specific keywords. 【0070】 Furthermore, the server utilizes generative AI models to filter the collected data. These generative AI models employ deep learning frameworks such as TENSORFLOW® and PyTorch to extract only highly relevant information. The filtered data is further analyzed using natural language processing techniques to evaluate its relevance to the customer organization. Specifically, machine learning algorithms are used to evaluate information that matches the customer's industry and needs. 【0071】 Based on the filtering and analysis results, the server identifies the appropriate contact person within the customer organization. This process matches business card information retrieved from the database and updates the relevant new contact person information. This clarifies the target of sales activities. 【0072】 AI is used to generate proposals. This automatically creates customized proposals and sales materials tailored to customer needs. Sales representatives, as users, receive these proposals via their devices and use them in their specific sales activities. This process utilizes tablets and laptops to improve the immediacy and convenience of information. 【0073】 As a concrete example, consider the need of a sales representative who wants to "gather information on the latest trends in cloud technology and create materials to propose to new customers." In this case, an example of a prompt message would be, "Gather information on the latest trends in cloud technology and form the basis for your next sales proposal." This would allow the server to efficiently collect and analyze relevant data and provide the sales representative with a useful proposal. 【0074】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0075】 Step 1: 【0076】 The server automatically collects technical information by patrolling websites and databases on the internet. Specifically, it uses Python libraries such as Beautiful Soup and Scrapy to retrieve information related to specific keywords. The input for this step is the URLs and keywords to be collected, and the output is the collected technical information data. 【0077】 Step 2: 【0078】 The server filters the collected technical information using a generating AI model. Here, the AI ​​model analyzes the data's characteristics and excludes irrelevant information to select the most relevant data. The input is the collected technical information data, and the output is the dataset deemed highly relevant. For example, it might extract only information related to new cloud technologies. 【0079】 Step 3: 【0080】 The server analyzes the filtered data using natural language processing techniques and evaluates its relevance to the customer organization. This process utilizes machine learning algorithms to analyze patterns within the data and identify information relevant to customer needs. The input is a filtered dataset, and the output is an identification of data beneficial to the customer organization. 【0081】 Step 4: 【0082】 The server identifies the appropriate person within the customer organization based on the analysis results. In this step, it matches business card information from the database to find the person associated with a specific job title or field. The inputs are the analysis results and business card information, and the output is detailed information about the identified person. 【0083】 Step 5: 【0084】 The server uses AI generation to customize proposals and generate information tailored to the identified contact person. This process includes creating proposals and sales materials that meet customer needs. Inputs are identified contact person information and collected / analyzed technical information, while output is customized materials for sales proposals. 【0085】 Step 6: 【0086】 The terminal receives proposal materials provided by the server and displays them to the user. Sales representatives use this information to prepare and execute proposal activities with customers. The input is proposal materials from the server, and the output is proposal information available to the sales representatives. 【0087】 Step 7: 【0088】 Users update new customer information obtained through sales activities using the digital business card management function. This ensures that the system maintains the most up-to-date customer data in conjunction with the server, building a foundation for more effective sales activities. The input is customer information obtained as a result of sales activities, and the output is the updated customer database. 【0089】 (Application Example 1) 【0090】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0091】 In today's business environment, improving the efficiency of information gathering and proposal development in corporate sales activities is a crucial challenge. In particular, accurately understanding customer purchasing behavior and needs, and promptly providing optimal proposals accordingly, is essential. However, traditional methods require significant time and effort for information gathering and analysis, making it difficult to substantially improve the efficiency of sales activities. 【0092】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0093】 In this invention, the server includes means for automatically collecting publicly available data, including technical information; means for analyzing the publicly available data and evaluating its relevance to customer groups; and means for identifying responsible personnel within the customer groups based on the analysis. This makes it possible to analyze customer purchase history and behavioral patterns and propose optimized payment plans. 【0094】 "Technical information" refers to data and knowledge related to technology, and specifically includes information such as patent documents, academic presentations, and technical reports. 【0095】 "Public data" is a general term for information that is accessible to the public through the internet, databases, etc., and includes technical information and market data. 【0096】 A "customer group" refers to a collection of corporations or individuals who have an interest in a particular product or service, and is primarily the target of sales activities. 【0097】 A "person in charge" is an individual responsible for a specific task or project, and in sales activities, this refers to a person involved in decision-making within a group of customers. 【0098】 "Purchase history" refers to records of past purchases and is data that provides clues to understanding a customer's consumption behavior. 【0099】 "Behavioral patterns" refer to the tendencies of customers in their repeated consumption and selection, and are used to predict future needs. 【0100】 A "payment plan" is a plan that outlines the payment methods and conditions offered to customers, and is designed with customer convenience and the company's profits in mind. 【0101】 To implement this invention, a server with high-speed processing capabilities and terminals for use by sales representatives are required. The server automatically collects publicly available data, including technical information, from the internet and analyzes that data. Generative AI models are used for the analysis to filter and select only relevant information. This process forms the foundation for proposing optimal products and services to a group of customers. 【0102】 Furthermore, the server has the ability to analyze customer purchase history and behavioral patterns and propose optimized payment plans. This function allows for a quick response to customer needs and significantly improves the efficiency of sales activities. Sales representatives receive these analysis results from the server via their terminals, create detailed proposals and sales materials, and make accurate proposals to customers. 【0103】 For example, if a sales representative needs to propose a new financial product to a client, the server retrieves publicly available market data, analyzes it, and identifies the target client segment. It then generates a settlement plan that takes into account the client's past trading patterns and sends it to the terminal. This allows the representative to quickly provide a tailored proposal to the client. 【0104】 A possible prompt message could be something like, "Please tell me how to identify potential customers who might be interested in a new product and suggest the best payment plan for them." 【0105】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0106】 Step 1: 【0107】 The server automatically collects technical information from publicly available data sources on the internet. The input is a set of URLs for publicly available technical information, and the output is the retrieved technical data. In this step, crawler software is used to periodically visit specified websites and retrieve the latest technical information. 【0108】 Step 2: 【0109】 The server analyzes the collected technical data and filters it using a generative AI model. The input is the collected technical data, and the output is highly relevant technical information. In this step, the AI ​​model is used to automatically determine the category and relevance of each data point. 【0110】 Step 3: 【0111】 The server identifies the relevant personnel within the customer group based on the analysis results. The input is filtered technical information and a customer database, and the output is a list of personnel. In this step, the system searches the database for personnel associated with technical information that matches the customer's needs. 【0112】 Step 4: 【0113】 The server generates information for proposals to be presented to the relevant personnel. The input is the identified personnel and related technical information, and the output is a draft proposal. This step utilizes a function that uses an AI model to automatically create proposals that take into account the needs of each personnel. 【0114】 Step 5: 【0115】 The user (sales representative) receives a draft proposal from the server via their terminal and customizes the content as needed. The input is a draft proposal, and the output is the final proposal. In this step, the sales representative reviews the proposal on their terminal and makes adjustments to optimize it for individual customers. 【0116】 Step 6: 【0117】 The user presents the final proposal to the customer. In this step, the proposal is made as a sales activity, and the concrete output is the successful completion of the deal with the customer. Through this process, sales representatives can efficiently approach customers and achieve results. 【0118】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0119】 This invention combines an emotion engine with a corporate sales support system to support sales activities based on the user's emotional state. This system mainly consists of three elements: a server, a terminal, and a user. 【0120】 First, the server collects publicly available data and analyzes it by comparing it with information from a business card management database. A generative AI model is used in this process to filter out only relevant technical information, thereby accurately identifying the appropriate contact person within the customer organization. This generates information to propose the most suitable products and services to sales representatives. 【0121】 The emotion engine recognizes the user's emotional state in real time and customizes the information it suggests. The device uses video and audio data input from the user's camera and microphone to perform emotion analysis. This optimizes the presentation order of suggested information received from the server according to the user's emotions. Furthermore, it considers the user's past emotional history and incorporates a mechanism to improve sales strategies through feedback. 【0122】 As a concrete example, consider a scenario where a sales representative is trying to propose a new product to an existing customer. The server collects relevant technical information, identifies the customer representative, and creates the proposal. The terminal assesses the user's emotions in real time and adjusts the order of the proposal to make it easier to understand. For example, if the system determines that the user is nervous, it will first present elements that have a relaxing effect before moving on to the specific proposal. 【0123】 In this way, the present invention can streamline sales activities and establish effective communication. This is expected to lead to improved sales results. 【0124】 The following describes the processing flow. 【0125】 Step 1: 【0126】 The server collects publicly available data. 【0127】 The server uses automated crawling technology to periodically collect technical information from relevant academic societies and news sites. Then, natural language processing is used to extract important keywords from the collected data and classify them as relevant information. 【0128】 Step 2: 【0129】 The server analyzes the data. 【0130】 The server uses a generative AI model to filter the collected data and cross-reference it with a business card management database. This allows for an assessment of the relevance to the customer organization and the identification of the appropriate contact person. This analysis also takes into account past sales history and contact person information. 【0131】 Step 3: 【0132】 The emotion engine recognizes the user's emotions. 【0133】 The device utilizes the user's camera and microphone to capture their facial expressions and voice tone. An emotion engine analyzes this data to determine the user's current emotional state in real time. 【0134】 Step 4: 【0135】 The server generates suggestion information, which is then optimized by an emotion engine. 【0136】 The server generates information to suggest appropriate products and services based on the analysis results. The emotion engine optimizes the order in which this information is presented based on the user's emotional state, adjusting it so that the information is displayed in the most effective way for the user. 【0137】 Step 5: 【0138】 The device provides information to the user. 【0139】 The device presents users with optimized proposal information. This allows users to create materials tailored to their sales activities and effectively communicate their proposals to customers. Sales strategies can also be improved by referring to past sentiment history. 【0140】 (Example 2) 【0141】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0142】 In corporate sales activities, it is crucial to appropriately identify the customer's contact person and tailor proposals accordingly. However, traditional systems often failed to adequately consider the customer's emotional state, resulting in ineffective proposals. Furthermore, it was not easy to utilize proposal feedback to improve sales strategies. These challenges need to be addressed. 【0143】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0144】 In this invention, the server includes means for collecting publicly available data, including technical information; means for analyzing the publicly available data and evaluating its relevance to customer organizations; and means for identifying responsible personnel based on the analysis. This enables the provision of optimal proposals tailored to the customer's interests and emotional state, thereby improving the efficiency of sales activities and establishing effective communication. 【0145】 "Technical information" refers to knowledge and data related to a specific field, and is information that is useful for proposing products and services. 【0146】 "Public data" refers to information that is generally accessible on the internet, and includes news articles, social media posts, press releases, and so on. 【0147】 A "customer organization" refers to a legal entity or corporate entity that is a potential or existing purchaser of a product or service. 【0148】 "Responsible person" refers to an individual or person in a position within a customer organization who is involved in proposing a specific product or service. 【0149】 A "generative AI model" refers to a model that uses artificial intelligence to analyze data and creatively generate or optimize information. 【0150】 "Emotional state" refers to the user's psychological state and includes specific emotions such as excitement, relaxation, and tension. 【0151】 "Feedback" refers to the reactions and evaluations received from users and customers, and is information used to improve systems and proposed solutions. 【0152】 This invention enables a corporate sales support system to analyze customer emotions in real time and make optimal sales proposals based on that analysis. This system mainly consists of three elements: a server, a terminal, and a user. 【0153】 First, the server is responsible for collecting publicly available data. Specifically, it automatically collects data, including technical information, from news articles, press releases, and social media posts on the internet. This data is then cross-referenced with a business card management database to analyze its relevance to customer organizations. A generative AI model is used for the analysis, filtering out only relevant information to identify the appropriate contact person within the customer organization. Finally, it generates information on the most suitable products and services to propose to the identified contact person. 【0154】 Next, the device uses the user's camera and microphone to acquire video and audio data from the user. This data is analyzed in real time by an emotion engine to recognize the user's emotional state. For example, it can determine whether the user is tense or relaxed. Based on this emotion analysis, the device optimizes the presentation order of suggested information received from the server and provides it to the user. 【0155】 Users conduct sales activities based on this optimized proposal information. The feedback provided by users is used to improve the overall sales strategy of the system and is reflected in future proposals. 【0156】 As a concrete example, consider a scenario where a new product is being proposed. The server collects technical information relevant to the customer and identifies the appropriate person to contact. The terminal analyzes the user's emotions in real time and presents the proposal content in the optimal order. For example, a nervous user would be presented with relaxing information first, followed by product information. 【0157】 An example of a prompt message might be: "We want to propose a new product released this week to a customer. Identify the customer's contact person and generate a presentation that includes a relaxing proposal." 【0158】 In this way, the present invention provides a system for supporting efficient and effective sales activities. 【0159】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0160】 Step 1: 【0161】 The server collects publicly available data from the internet. Inputs include news articles, press releases, and social media posts. This data is stored in a database, and the server processes it to extract technical information relevant to the customer. The output is a dataset of organized technical information. 【0162】 Step 2: 【0163】 The server retrieves customer information from a business card management database. The input is business card information from the database. This business card information is compared with technical information from publicly available data to identify the appropriate contact person within the customer organization. The output is a list of the identified contact persons. 【0164】 Step 3: 【0165】 The server utilizes a generative AI model to generate information on the most suitable products and services to recommend to identified contacts. The input consists of a list of identified contacts and related technical information. Through data processing and calculations, personalized recommendations are created. The output is optimized recommendation information. 【0166】 Step 4: 【0167】 The device uses the user's camera and microphone to acquire video and audio data from the user. The input is the user's real-time video and audio data. Using this data, the emotion engine analyzes the user's emotional state. The output is the evaluation result of the user's emotional state. 【0168】 Step 5: 【0169】 The terminal optimizes the presentation order of suggested information received from the server based on the user's emotional state. The input consists of suggested information from the server and the user's emotional state. The terminal adjusts the order of the suggested information to present it in the most optimal way for the user. The output is the optimized presentation order of the suggested information. 【0170】 Step 6: 【0171】 The user reviews the presented proposal information and conducts sales activities. The input is the optimized and presented proposal information. The user presents this to the customer and receives feedback. The output is the results of the sales activity and the feedback. The feedback is re-entered into the system and used to improve future sales strategies. 【0172】 (Application Example 2) 【0173】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0174】 In recent years, there has been a growing need for more efficient sales activities and customized proposals. However, conventional sales support systems lack the ability to provide real-time information that takes into account the emotional state of customers, making it difficult to make optimal proposals for individual customers. As a result, there is a lack of effective communication that meets customer needs, which hinders the improvement of sales results. 【0175】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0176】 In this invention, the server includes means for automatically collecting publicly available data including technical indicators, means for analyzing the publicly available data and evaluating its relevance to customer groups, means for identifying personnel within customer groups based on the analysis, means for analyzing the user's emotional state in real time using a camera and microphone, and means for optimizing the presentation order of suggestion information based on the emotional state. This enables suggestions optimized according to the user's emotions, thereby improving the effectiveness of sales activities. 【0177】 "Technical indicators" are a collection of specific numerical values ​​and information used to clarify the features and characteristics of a product or service. 【0178】 "Public data" refers to data obtained from publicly available sources and used for a specific purpose. 【0179】 A "customer group" is a collection of corporations or individuals that are expected to use or purchase a product or service. 【0180】 A "person in charge" is an individual within a customer group who holds a specific role or responsibility, and is identified as the person to whom sales or proposals are made. 【0181】 Cameras and microphones are devices used to acquire images and sounds, and are used as a means of data input. 【0182】 "Emotional state" refers to an individual's internal state of sensations and emotions at a given moment, and it manifests as a reaction to external stimuli. 【0183】 "Proposal information" refers to materials and data created to recommend specific products or services to customers. 【0184】 "Optimizing the presentation order" means adjusting the order and method of conveying information to be as effective as possible, based on user reactions and emotions. 【0185】 To realize this invention, the system consists of three main elements: a server, a terminal, and a user. 【0186】 The server automatically collects publicly available data, including technical metrics, and filters it using a generative AI model. This allows it to evaluate relevance to customer groups and generate information to suggest appropriate products and services to identified individuals. The server plays a central role in efficiently processing large amounts of data and providing optimal recommendation information. 【0187】 The device functions as an interface with the user, using hardware such as a camera and microphone to analyze the user's emotional state in real time. Specifically, it uses image processing technology to analyze the user's facial expressions and speech recognition technology to analyze the user's tone of voice. This allows it to grasp the user's instantaneous emotional state and transmit that information to a server. 【0188】 Users interact with the system through a provided terminal. For example, in a consumer robot system for a home, if the terminal determines that the user is relaxed, it may recommend relaxing music. Conversely, if the terminal determines that the user is tired, it may suggest, "Why not take a short break and start an activity to refresh yourself?" 【0189】 An example of a prompt statement is, "Analyze the residents' emotional state in real time and offer suggestions for relaxation or cheering up." This prompt statement functions as a keyword that supports the process by which the generative AI model performs emotion analysis and information optimization. 【0190】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0191】 Step 1: 【0192】 The server automatically collects publicly available data. In this process, it retrieves unstructured data from the internet and corporate open databases and stores it in its internal database. The input is publicly available data, and the output is the collected raw data. 【0193】 Step 2: 【0194】 The server uses a generative AI model to filter the collected data. It utilizes natural language processing and machine learning techniques with the AI ​​model to select relevant technical information and evaluate its relevance to the customer group. The input is the raw data collected in step 1, and the output is the filtered, relevant data. 【0195】 Step 3: 【0196】 The server identifies the relevant personnel within a customer group based on filtered data. Using a business card database, it analyzes the personnel's duties and roles to identify those who can most effectively receive the proposed information. The input consists of filtered data and business card information, and the output is a list of identified personnel. 【0197】 Step 4: 【0198】 The device analyzes the user's emotional state in real time. It collects video and audio using a camera and microphone, and performs image processing and audio analysis using a generative AI model. The input is the user's video and audio data, and the output is the analyzed emotional state data. 【0199】 Step 5: 【0200】 The device optimizes the presentation order of suggested information based on the analysis results. It takes into account the user's emotional state and adjusts the timing and order to present the suggested information to the user at the optimal time. Specifically, it presents suggestions that promote relaxation or pique the user's interest first, followed by detailed information. The input is the analyzed emotional state and suggested information, and the output is information on the optimized presentation order. 【0201】 Step 6: 【0202】 The user decides whether to accept the optimized suggestions. If they accept, they communicate their intention to proceed with the suggested activities or purchase procedures to the device. The input is the optimized information presented, and the output is the user's choices and feedback. 【0203】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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. 【0204】 Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0205】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14. 【0206】 [Second Embodiment] 【0207】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0208】 As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server. 【0209】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0210】 The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52. 【0211】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0212】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0213】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0214】 Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0215】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0216】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0217】 In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0218】 Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0219】 This invention is a system designed to support specific corporate sales activities and is implemented through a configuration centered on a server, terminals, and users. The server has high-speed processing capabilities and automatically collects publicly available data, including large amounts of technical information. This enables reliable and rapid acquisition of the information users need. The server also uses advanced algorithms and generative AI to analyze the collected data, evaluate the relevance of the data, and organize the information so that users can use it efficiently. 【0220】 Specifically, the server first crawls websites and databases on the internet to extract necessary technical information. This includes filtering useful and relevant information from publicly available data that is regularly updated. Next, the server analyzes the retrieved information to identify the appropriate person within the customer organization. This provides a foundation for suggesting information about the most suitable products or services for the target customer. 【0221】 Sales representatives, as users, receive analysis results from the server via their terminals. They then use this information to create proposals and sales materials, and conduct concrete sales activities. The proposals generated by the server are customized according to customer needs, supporting users in conducting sales activities efficiently. This system utilizes a digital business card management function to facilitate updating and managing customer information, and can perform more precise data analysis in conjunction with the server. 【0222】 As a concrete example, consider a scenario where a sales representative is looking for customers interested in a new cloud technology. The server collects the latest conference presentations on relevant technical information and identifies recommended experts from a publicly available list. Subsequently, proposals generated by the server are sent to the terminal, allowing the user to quickly and accurately engage in sales activities with customers. In this way, the system of the present invention significantly improves the efficiency of sales activities. 【0223】 The following describes the processing flow. 【0224】 Step 1: 【0225】 The server collects publicly available data. 【0226】 The server uses a web crawler to visit websites containing academic presentations and news articles at a set frequency, automatically collecting articles that include technical information. During this process, natural language processing technology is used to extract relevant keywords from the articles and tag them to determine their importance. 【0227】 Step 2: 【0228】 The server analyzes the data. 【0229】 The server compares the collected information with data in the digital business card management system. Using customer names and related keywords, it searches for past business negotiation history and contact person information, and uses generating AI to evaluate the relevance of the information. This identifies information that is beneficial to the customer. 【0230】 Step 3: 【0231】 The server identifies the person in charge. 【0232】 Based on the analysis results, the server lists the contacts with strong relationships within the customer organization. Using a generative AI model, it identifies the names and titles of appropriate contacts from publicly available information and business card data, and stores this information in a database for use in sales activities. 【0233】 Step 4: 【0234】 The server generates the suggestion information. 【0235】 The server generates materials to suggest appropriate products and services based on information related to the identified person in charge. This allows the user to take the most effective approach to the customer. 【0236】 Step 5: 【0237】 The device provides information to the user. 【0238】 The terminal receives proposal details and contact person information generated from the server and presents them to the user. Based on this data, the user can create proposals and other materials necessary for sales activities and make concrete sales approaches to customers. 【0239】 (Example 1) 【0240】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0241】 Modern sales activities require the rapid and efficient acquisition of highly relevant information from a vast amount of technical data, but traditional methods fail to adequately achieve this. In particular, data collection and analysis for creating specific proposal materials needed by sales representatives are cumbersome and time-consuming. Therefore, a system is needed to automate information selection and the generation of customized proposals, thereby supporting efficient sales activities. 【0242】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0243】 In this invention, the server includes means for automatically collecting publicly available data, including technical information; means for filtering the publicly available data using a generating AI model and selecting highly relevant information; and means for analyzing the filtered data and evaluating its relevance to customer organizations. This enables sales representatives to quickly collect the information they need and engage in accurate proposal activities. 【0244】 "Technical information" refers to data and knowledge related to science and technology, and includes research results, technical specifications, patent documents, etc. 【0245】 "Public data" refers to information that is generally accessible on the internet or other resources, and is provided in a form that anyone can use. 【0246】 A "generative AI model" is a mathematical model that uses artificial intelligence to generate new output from data, and is built on machine learning and deep learning technologies. 【0247】 "Filtering" refers to the process of selecting specific information from collected data as needed and excluding other information. 【0248】 "Analysis" is the process of thoroughly investigating and studying collected data to find useful information and patterns within it. 【0249】 A "customer organization" refers to the companies or groups that are the target of sales activities, and the recipients of goods and services. 【0250】 "Responsible person" refers to an individual within a client organization who is responsible for a specific task or project. 【0251】 "Proposal details" refers to information that summarizes the details, benefits, and usage methods of products and services presented to customers during sales or business negotiations. 【0252】 This invention is a system designed to support sales activities and is centered around a server, terminals, and users. Specific embodiments are shown below. 【0253】 The server possesses high-speed processing capabilities and automatically collects technical information from websites and databases on the internet using programming languages ​​such as Python and R. Specific software used here includes Beautiful Soup and Scrapy for data scraping. Using these tools, the server extracts relevant technical information based on specific keywords. 【0254】 Furthermore, the server utilizes generative AI models to filter the collected data. These generative AI models employ deep learning frameworks such as TensorFlow and PyTorch to extract only highly relevant information. The filtered data is further analyzed using natural language processing techniques to assess its relevance to the customer organization. Specifically, machine learning algorithms are used to evaluate information that matches the customer's industry and needs. 【0255】 Based on the filtering and analysis results, the server identifies the appropriate contact person within the customer organization. This process matches business card information retrieved from the database and updates the relevant new contact person information. This clarifies the target of sales activities. 【0256】 AI is used to generate proposals. This automatically creates customized proposals and sales materials tailored to customer needs. Sales representatives, as users, receive these proposals via their devices and use them in their specific sales activities. This process utilizes tablets and laptops to improve the immediacy and convenience of information. 【0257】 As a concrete example, consider the need of a sales representative who wants to "gather information on the latest trends in cloud technology and create materials to propose to new customers." In this case, an example of a prompt message would be, "Gather information on the latest trends in cloud technology and form the basis for your next sales proposal." This would allow the server to efficiently collect and analyze relevant data and provide the sales representative with a useful proposal. 【0258】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0259】 Step 1: 【0260】 The server automatically collects technical information by patrolling websites and databases on the internet. Specifically, it uses Python libraries such as Beautiful Soup and Scrapy to retrieve information related to specific keywords. The input for this step is the URLs and keywords to be collected, and the output is the collected technical information data. 【0261】 Step 2: 【0262】 The server filters the collected technical information using a generating AI model. Here, the AI ​​model analyzes the data's characteristics and excludes irrelevant information to select the most relevant data. The input is the collected technical information data, and the output is the dataset deemed highly relevant. For example, it might extract only information related to new cloud technologies. 【0263】 Step 3: 【0264】 The server analyzes the filtered data using natural language processing techniques and evaluates its relevance to the customer organization. This process utilizes machine learning algorithms to analyze patterns within the data and identify information relevant to customer needs. The input is a filtered dataset, and the output is an identification of data beneficial to the customer organization. 【0265】 Step 4: 【0266】 The server identifies the appropriate person within the customer organization based on the analysis results. In this step, it matches business card information from the database to find the person associated with a specific job title or field. The inputs are the analysis results and business card information, and the output is detailed information about the identified person. 【0267】 Step 5: 【0268】 The server uses AI generation to customize proposals and generate information tailored to the identified contact person. This process includes creating proposals and sales materials that meet customer needs. Inputs are identified contact person information and collected / analyzed technical information, while output is customized materials for sales proposals. 【0269】 Step 6: 【0270】 The terminal receives proposal materials provided by the server and displays them to the user. Sales representatives use this information to prepare and execute proposal activities with customers. The input is proposal materials from the server, and the output is proposal information available to the sales representatives. 【0271】 Step 7: 【0272】 Users update new customer information obtained through sales activities using the digital business card management function. This ensures that the system maintains the most up-to-date customer data in conjunction with the server, building a foundation for more effective sales activities. The input is customer information obtained as a result of sales activities, and the output is the updated customer database. 【0273】 (Application Example 1) 【0274】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0275】 In today's business environment, improving the efficiency of information gathering and proposal development in corporate sales activities is a crucial challenge. In particular, accurately understanding customer purchasing behavior and needs, and promptly providing optimal proposals accordingly, is essential. However, traditional methods require significant time and effort for information gathering and analysis, making it difficult to substantially improve the efficiency of sales activities. 【0276】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0277】 In this invention, the server includes means for automatically collecting publicly available data, including technical information; means for analyzing the publicly available data and evaluating its relevance to customer groups; and means for identifying responsible personnel within the customer groups based on the analysis. This makes it possible to analyze customer purchase history and behavioral patterns and propose optimized payment plans. 【0278】 "Technical information" refers to data and knowledge related to technology, specifically information including patent documents, academic publications, technical reports, etc. 【0279】 "Public data" is a general term for information that is generally accessible via the Internet, databases, etc., and includes technical information, market data, etc. 【0280】 "Customer group" refers to a collection of corporations and individuals who have an interest or concern in specific products or services, and mainly serves as the target of business activities. 【0281】 "Responsible person" refers to an individual who has the responsibility to participate in specific business or projects, and in business activities, is a person who participates in decision-making within the customer group. 【0282】 "Purchase history" is a record of past purchases and is data that provides clues to understanding customers' consumption behavior. 【0283】 "Behavior pattern" indicates the tendency of customers' repeated consumption and selection, and is used to predict future needs. 【0284】 "Payment plan" is a plan that summarizes the payment methods and conditions provided to customers, and is designed considering customers' convenience and the company's profits. 【0285】 To implement this invention, a server with high-speed processing capabilities and a terminal used by sales representatives are required. The server automatically collects public data including technical information from the Internet and analyzes the data. For the analysis, a generated AI model is utilized to filter and select only relevant information. Through this process, a basis is formed for proposing the optimal products and services for the customer group. 【0286】 Furthermore, the server has the function of analyzing the customer's purchase history and behavior patterns and proposing an optimized settlement plan. With this function, it is possible to quickly respond to the customer's needs and significantly improve the efficiency of sales activities. The salesperson receives these analysis results provided by the server through the terminal, creates specific proposals and sales materials, and makes accurate proposals to the customer. 【0287】 For example, when a salesperson needs to propose a new financial product to a customer, the server acquires the publicly available market data, analyzes it, and identifies the target customer segment. Then, it generates a settlement plan considering the customer's past transaction patterns and sends it to the terminal. As a result, the salesperson can make a proposal suitable for the customer in a short time. 【0288】 As an example of a prompt sentence, it can be considered to input like "Please teach me how to identify customers who may be interested in new products and propose an optimal settlement plan." 【0289】 The flow of the specific process in Application Example 1 will be described using FIG. 12. 【0290】 Step 1: 【0291】 The server automatically collects technical information from publicly available data sources on the Internet. The input is a group of URLs of publicly available technical information, and the output is the acquired technical data. In this step, the crawler software is used to periodically visit the specified websites to obtain the latest technical information. 【0292】 Step 2: 【0293】 The server analyzes the collected technical data and filters the data using the generated AI model. The input is the collected technical data, and the output is highly relevant technical information. In this step, the process of automatically discriminating the category and relevance of each data using the AI model is carried out. 【0294】 Step 3: 【0295】 The server identifies the relevant personnel within the customer group based on the analysis results. The input is filtered technical information and a customer database, and the output is a list of personnel. In this step, the system searches the database for personnel associated with technical information that matches the customer's needs. 【0296】 Step 4: 【0297】 The server generates information for proposals to be presented to the relevant personnel. The input is the identified personnel and related technical information, and the output is a draft proposal. This step utilizes a function that uses an AI model to automatically create proposals that take into account the needs of each personnel. 【0298】 Step 5: 【0299】 The user (sales representative) receives a draft proposal from the server via their terminal and customizes the content as needed. The input is a draft proposal, and the output is the final proposal. In this step, the sales representative reviews the proposal on their terminal and makes adjustments to optimize it for individual customers. 【0300】 Step 6: 【0301】 The user presents the final proposal to the customer. In this step, the proposal is made as a sales activity, and the concrete output is the successful completion of the deal with the customer. Through this process, sales representatives can efficiently approach customers and achieve results. 【0302】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0303】 The present invention has a structure that combines an emotion engine with a corporate business support system and supports business activities based on the emotional state of the user. This system is mainly composed of three elements: a server, a terminal, and a user. 【0304】 First, the server collects public data, collates it with the information in the business card management database, and analyzes it. In this process, a generated AI model is used to filter only relevant technical information, thereby accurately identifying the appropriate person in charge within the customer organization. As a result, information for proposing the most suitable products and services to the salesperson is generated. 【0305】 The emotion engine is responsible for recognizing the user's emotional state in real time and customizing the information to be proposed. The terminal performs emotion analysis using video and audio data input from the user's camera and microphone. As a result, the presentation order of the proposed information received from the server is optimized according to the user's emotions. In addition, there is a mechanism to consider the user's past emotional history and improve the business strategy through feedback. 【0306】 As a specific example, consider the case where a salesperson is trying to propose a new product to an existing customer. The server collects relevant technical information, identifies the person in charge of the customer, and creates the proposal content. The terminal determines the user's emotion in real time and adjusts the order so that the proposal is presented in an easy-to-understand manner. For example, if the user is judged to be nervous, elements with a relaxing effect are presented first, and then the specific proposal content is presented. 【0307】 In this way, the present invention can improve the efficiency of business activities and establish effective communication. As a result, an improvement in business results is expected. 【0308】 The following describes the processing flow. 【0309】 Step 1: 【0310】 The server collects public data. 【0311】 The server uses automated crawling technology to periodically collect technical information from relevant academic societies and news sites. Then, natural language processing is used to extract important keywords from the collected data and classify them as relevant information. 【0312】 Step 2: 【0313】 The server analyzes the data. 【0314】 The server uses a generative AI model to filter the collected data and cross-reference it with a business card management database. This allows for an assessment of the relevance to the customer organization and the identification of the appropriate contact person. This analysis also takes into account past sales history and contact person information. 【0315】 Step 3: 【0316】 The emotion engine recognizes the user's emotions. 【0317】 The device utilizes the user's camera and microphone to capture their facial expressions and voice tone. An emotion engine analyzes this data to determine the user's current emotional state in real time. 【0318】 Step 4: 【0319】 The server generates suggestion information, which is then optimized by an emotion engine. 【0320】 The server generates information to suggest appropriate products and services based on the analysis results. The emotion engine optimizes the order in which this information is presented based on the user's emotional state, adjusting it so that the information is displayed in the most effective way for the user. 【0321】 Step 5: 【0322】 The device provides information to the user. 【0323】 The device presents users with optimized proposal information. This allows users to create materials tailored to their sales activities and effectively communicate their proposals to customers. Sales strategies can also be improved by referring to past sentiment history. 【0324】 (Example 2) 【0325】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0326】 In corporate sales activities, it is crucial to appropriately identify the customer's contact person and tailor proposals accordingly. However, traditional systems often failed to adequately consider the customer's emotional state, resulting in ineffective proposals. Furthermore, it was not easy to utilize proposal feedback to improve sales strategies. These challenges need to be addressed. 【0327】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0328】 In this invention, the server includes means for collecting publicly available data, including technical information; means for analyzing the publicly available data and evaluating its relevance to customer organizations; and means for identifying responsible personnel based on the analysis. This enables the provision of optimal proposals tailored to the customer's interests and emotional state, thereby improving the efficiency of sales activities and establishing effective communication. 【0329】 "Technical information" refers to knowledge and data related to a specific field, and is information that is useful for proposing products and services. 【0330】 "Public data" refers to information that is generally accessible on the internet, and includes news articles, social media posts, press releases, and so on. 【0331】 A "customer organization" refers to a legal entity or corporate entity that is a potential or existing purchaser of a product or service. 【0332】 "Responsible person" refers to an individual or person in a position within a customer organization who is involved in proposing a specific product or service. 【0333】 A "generative AI model" refers to a model that uses artificial intelligence to analyze data and creatively generate or optimize information. 【0334】 "Emotional state" refers to the user's psychological state and includes specific emotions such as excitement, relaxation, and tension. 【0335】 "Feedback" refers to the reactions and evaluations received from users and customers, and is information used to improve systems and proposed solutions. 【0336】 This invention enables a corporate sales support system to analyze customer emotions in real time and make optimal sales proposals based on that analysis. This system mainly consists of three elements: a server, a terminal, and a user. 【0337】 First, the server is responsible for collecting publicly available data. Specifically, it automatically collects data, including technical information, from news articles, press releases, and social media posts on the internet. This data is then cross-referenced with a business card management database to analyze its relevance to customer organizations. A generative AI model is used for the analysis, filtering out only relevant information to identify the appropriate contact person within the customer organization. Finally, it generates information on the most suitable products and services to propose to the identified contact person. 【0338】 Next, the device uses the user's camera and microphone to acquire video and audio data from the user. This data is analyzed in real time by an emotion engine to recognize the user's emotional state. For example, it can determine whether the user is tense or relaxed. Based on this emotion analysis, the device optimizes the presentation order of suggested information received from the server and provides it to the user. 【0339】 Users conduct sales activities based on this optimized proposal information. The feedback provided by users is used to improve the overall sales strategy of the system and is reflected in future proposals. 【0340】 As a concrete example, consider a scenario where a new product is being proposed. The server collects technical information relevant to the customer and identifies the appropriate person to contact. The terminal analyzes the user's emotions in real time and presents the proposal content in the optimal order. For example, a nervous user would be presented with relaxing information first, followed by product information. 【0341】 An example of a prompt message might be: "We want to propose a new product released this week to a customer. Identify the customer's contact person and generate a presentation that includes a relaxing proposal." 【0342】 In this way, the present invention provides a system for supporting efficient and effective sales activities. 【0343】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0344】 Step 1: 【0345】 The server collects publicly available data from the internet. Inputs include news articles, press releases, and social media posts. This data is stored in a database, and the server processes it to extract technical information relevant to the customer. The output is a dataset of organized technical information. 【0346】 Step 2: 【0347】 The server retrieves customer information from a business card management database. The input is business card information from the database. This business card information is compared with technical information from publicly available data to identify the appropriate contact person within the customer organization. The output is a list of the identified contact persons. 【0348】 Step 3: 【0349】 The server utilizes a generative AI model to generate information on the most suitable products and services to recommend to identified contacts. The input consists of a list of identified contacts and related technical information. Through data processing and calculations, personalized recommendations are created. The output is optimized recommendation information. 【0350】 Step 4: 【0351】 The device uses the user's camera and microphone to acquire video and audio data from the user. The input is the user's real-time video and audio data. Using this data, the emotion engine analyzes the user's emotional state. The output is the evaluation result of the user's emotional state. 【0352】 Step 5: 【0353】 The terminal optimizes the presentation order of suggested information received from the server based on the user's emotional state. The input consists of suggested information from the server and the user's emotional state. The terminal adjusts the order of the suggested information to present it in the most optimal way for the user. The output is the optimized presentation order of the suggested information. 【0354】 Step 6: 【0355】 The user reviews the presented proposal information and conducts sales activities. The input is the optimized and presented proposal information. The user presents this to the customer and receives feedback. The output is the results of the sales activity and the feedback. The feedback is re-entered into the system and used to improve future sales strategies. 【0356】 (Application Example 2) 【0357】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0358】 In recent years, there has been a growing need for more efficient sales activities and customized proposals. However, conventional sales support systems lack the ability to provide real-time information that takes into account the emotional state of customers, making it difficult to make optimal proposals for individual customers. As a result, there is a lack of effective communication that meets customer needs, which hinders the improvement of sales results. 【0359】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0360】 In this invention, the server includes means for automatically collecting publicly available data including technical indicators, means for analyzing the publicly available data and evaluating its relevance to customer groups, means for identifying personnel within customer groups based on the analysis, means for analyzing the user's emotional state in real time using a camera and microphone, and means for optimizing the presentation order of suggestion information based on the emotional state. This enables suggestions optimized according to the user's emotions, thereby improving the effectiveness of sales activities. 【0361】 "Technical indicators" are a collection of specific numerical values ​​and information used to clarify the features and characteristics of a product or service. 【0362】 "Public data" refers to data obtained from publicly available sources and used for a specific purpose. 【0363】 A "customer group" is a collection of corporations or individuals that are expected to use or purchase a product or service. 【0364】 A "person in charge" is an individual within a customer group who holds a specific role or responsibility, and is identified as the person to whom sales or proposals are made. 【0365】 Cameras and microphones are devices used to acquire images and sounds, and are used as a means of data input. 【0366】 "Emotional state" refers to an individual's internal state of sensations and emotions at a given moment, and it manifests as a reaction to external stimuli. 【0367】 "Proposal information" refers to materials and data created to recommend specific products or services to customers. 【0368】 "Optimizing the presentation order" means adjusting the order and method of conveying information to be as effective as possible, based on user reactions and emotions. 【0369】 To realize this invention, the system consists of three main elements: a server, a terminal, and a user. 【0370】 The server automatically collects publicly available data, including technical metrics, and filters it using a generative AI model. This allows it to evaluate relevance to customer groups and generate information to suggest appropriate products and services to identified individuals. The server plays a central role in efficiently processing large amounts of data and providing optimal recommendation information. 【0371】 The device functions as an interface with the user, using hardware such as a camera and microphone to analyze the user's emotional state in real time. Specifically, it uses image processing technology to analyze the user's facial expressions and speech recognition technology to analyze the user's tone of voice. This allows it to grasp the user's instantaneous emotional state and transmit that information to a server. 【0372】 Users interact with the system through a provided terminal. For example, in a consumer robot system for a home, if the terminal determines that the user is relaxed, it may recommend relaxing music. Conversely, if the terminal determines that the user is tired, it may suggest, "Why not take a short break and start an activity to refresh yourself?" 【0373】 An example of a prompt statement is, "Analyze the residents' emotional state in real time and offer suggestions for relaxation or cheering up." This prompt statement functions as a keyword that supports the process by which the generative AI model performs emotion analysis and information optimization. 【0374】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0375】 Step 1: 【0376】 The server automatically collects publicly available data. In this process, it retrieves unstructured data from the internet and corporate open databases and stores it in its internal database. The input is publicly available data, and the output is the collected raw data. 【0377】 Step 2: 【0378】 The server uses a generative AI model to filter the collected data. It utilizes natural language processing and machine learning techniques with the AI ​​model to select relevant technical information and evaluate its relevance to the customer group. The input is the raw data collected in step 1, and the output is the filtered, relevant data. 【0379】 Step 3: 【0380】 The server identifies the relevant personnel within a customer group based on filtered data. Using a business card database, it analyzes the personnel's duties and roles to identify those who can most effectively receive the proposed information. The input consists of filtered data and business card information, and the output is a list of identified personnel. 【0381】 Step 4: 【0382】 The device analyzes the user's emotional state in real time. It collects video and audio using a camera and microphone, and performs image processing and audio analysis using a generative AI model. The input is the user's video and audio data, and the output is the analyzed emotional state data. 【0383】 Step 5: 【0384】 The device optimizes the presentation order of suggested information based on the analysis results. It takes into account the user's emotional state and adjusts the timing and order to present the suggested information to the user at the optimal time. Specifically, it presents suggestions that promote relaxation or pique the user's interest first, followed by detailed information. The input is the analyzed emotional state and suggested information, and the output is information on the optimized presentation order. 【0385】 Step 6: 【0386】 The user decides whether to accept the optimized suggestions. If they accept, they communicate their intention to proceed with the suggested activities or purchase procedures to the device. The input is the optimized information presented, and the output is the user's choices and feedback. 【0387】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0388】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0389】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214. 【0390】 [Third Embodiment] 【0391】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0392】 As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server. 【0393】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0394】 The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52. 【0395】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0396】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0397】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0398】 Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0399】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0400】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0401】 In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0402】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal". 【0403】 This invention is a system designed to support specific corporate sales activities and is implemented through a configuration centered on a server, terminals, and users. The server has high-speed processing capabilities and automatically collects publicly available data, including large amounts of technical information. This enables reliable and rapid acquisition of the information users need. The server also uses advanced algorithms and generative AI to analyze the collected data, evaluate the relevance of the data, and organize the information so that users can use it efficiently. 【0404】 Specifically, the server first crawls websites and databases on the internet to extract necessary technical information. This includes filtering useful and relevant information from publicly available data that is regularly updated. Next, the server analyzes the retrieved information to identify the appropriate person within the customer organization. This provides a foundation for suggesting information about the most suitable products or services for the target customer. 【0405】 Sales representatives, as users, receive analysis results from the server via their terminals. They then use this information to create proposals and sales materials, and conduct concrete sales activities. The proposals generated by the server are customized according to customer needs, supporting users in conducting sales activities efficiently. This system utilizes a digital business card management function to facilitate updating and managing customer information, and can perform more precise data analysis in conjunction with the server. 【0406】 As a concrete example, consider a scenario where a sales representative is looking for customers interested in a new cloud technology. The server collects the latest conference presentations on relevant technical information and identifies recommended experts from a publicly available list. Subsequently, proposals generated by the server are sent to the terminal, allowing the user to quickly and accurately engage in sales activities with customers. In this way, the system of the present invention significantly improves the efficiency of sales activities. 【0407】 The following describes the processing flow. 【0408】 Step 1: 【0409】 The server collects publicly available data. 【0410】 The server uses a web crawler to visit websites containing academic presentations and news articles at a set frequency, automatically collecting articles that include technical information. During this process, natural language processing technology is used to extract relevant keywords from the articles and tag them to determine their importance. 【0411】 Step 2: 【0412】 The server analyzes the data. 【0413】 The server compares the collected information with data in the digital business card management system. Using customer names and related keywords, it searches for past business negotiation history and contact person information, and uses generating AI to evaluate the relevance of the information. This identifies information that is beneficial to the customer. 【0414】 Step 3: 【0415】 The server identifies the person in charge. 【0416】 Based on the analysis results, the server lists the contacts with strong relationships within the customer organization. Using a generative AI model, it identifies the names and titles of appropriate contacts from publicly available information and business card data, and stores this information in a database for use in sales activities. 【0417】 Step 4: 【0418】 The server generates the suggestion information. 【0419】 The server generates materials to suggest appropriate products and services based on information related to the identified person in charge. This allows the user to take the most effective approach to the customer. 【0420】 Step 5: 【0421】 The device provides information to the user. 【0422】 The terminal receives proposal details and contact person information generated from the server and presents them to the user. Based on this data, the user can create proposals and other materials necessary for sales activities and make concrete sales approaches to customers. 【0423】 (Example 1) 【0424】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0425】 Modern sales activities require the rapid and efficient acquisition of highly relevant information from a vast amount of technical data, but traditional methods fail to adequately achieve this. In particular, data collection and analysis for creating specific proposal materials needed by sales representatives are cumbersome and time-consuming. Therefore, a system is needed to automate information selection and the generation of customized proposals, thereby supporting efficient sales activities. 【0426】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0427】 In this invention, the server includes means for automatically collecting publicly available data, including technical information; means for filtering the publicly available data using a generating AI model and selecting highly relevant information; and means for analyzing the filtered data and evaluating its relevance to customer organizations. This enables sales representatives to quickly collect the information they need and engage in accurate proposal activities. 【0428】 "Technical information" refers to data and knowledge related to science and technology, and includes research results, technical specifications, patent documents, etc. 【0429】 "Public data" refers to information that is generally accessible on the internet or other resources, and is provided in a form that anyone can use. 【0430】 A "generative AI model" is a mathematical model that uses artificial intelligence to generate new output from data, and is built on machine learning and deep learning technologies. 【0431】 "Filtering" refers to the process of selecting specific information from collected data as needed and excluding other information. 【0432】 "Analysis" is the process of thoroughly investigating and studying collected data to find useful information and patterns within it. 【0433】 A "customer organization" refers to the companies or groups that are the target of sales activities, and the recipients of goods and services. 【0434】 "Responsible person" refers to an individual within a client organization who is responsible for a specific task or project. 【0435】 "Proposal details" refers to information that summarizes the details, benefits, and usage methods of products and services presented to customers during sales or business negotiations. 【0436】 This invention is a system designed to support sales activities and is centered around a server, terminals, and users. Specific embodiments are shown below. 【0437】 The server possesses high-speed processing capabilities and automatically collects technical information from websites and databases on the internet using programming languages ​​such as Python and R. Specific software used here includes Beautiful Soup and Scrapy for data scraping. Using these tools, the server extracts relevant technical information based on specific keywords. 【0438】 Furthermore, the server utilizes generative AI models to filter the collected data. These generative AI models employ deep learning frameworks such as TensorFlow and PyTorch to extract only highly relevant information. The filtered data is further analyzed using natural language processing techniques to assess its relevance to the customer organization. Specifically, machine learning algorithms are used to evaluate information that matches the customer's industry and needs. 【0439】 Based on the filtering and analysis results, the server identifies the appropriate contact person within the customer organization. This process matches business card information retrieved from the database and updates the relevant new contact person information. This clarifies the target of sales activities. 【0440】 AI is used to generate proposals. This automatically creates customized proposals and sales materials tailored to customer needs. Sales representatives, as users, receive these proposals via their devices and use them in their specific sales activities. This process utilizes tablets and laptops to improve the immediacy and convenience of information. 【0441】 As a concrete example, consider the need of a sales representative who wants to "gather information on the latest trends in cloud technology and create materials to propose to new customers." In this case, an example of a prompt message would be, "Gather information on the latest trends in cloud technology and form the basis for your next sales proposal." This would allow the server to efficiently collect and analyze relevant data and provide the sales representative with a useful proposal. 【0442】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0443】 Step 1: 【0444】 The server automatically collects technical information by patrolling websites and databases on the internet. Specifically, it uses Python libraries such as Beautiful Soup and Scrapy to retrieve information related to specific keywords. The input for this step is the URLs and keywords to be collected, and the output is the collected technical information data. 【0445】 Step 2: 【0446】 The server filters the collected technical information using a generating AI model. Here, the AI ​​model analyzes the data's characteristics and excludes irrelevant information to select the most relevant data. The input is the collected technical information data, and the output is the dataset deemed highly relevant. For example, it might extract only information related to new cloud technologies. 【0447】 Step 3: 【0448】 The server analyzes the filtered data using natural language processing techniques and evaluates its relevance to the customer organization. This process utilizes machine learning algorithms to analyze patterns within the data and identify information relevant to customer needs. The input is a filtered dataset, and the output is an identification of data beneficial to the customer organization. 【0449】 Step 4: 【0450】 The server identifies the appropriate person within the customer organization based on the analysis results. In this step, it matches business card information from the database to find the person associated with a specific job title or field. The inputs are the analysis results and business card information, and the output is detailed information about the identified person. 【0451】 Step 5: 【0452】 The server uses AI generation to customize proposals and generate information tailored to the identified contact person. This process includes creating proposals and sales materials that meet customer needs. Inputs are identified contact person information and collected / analyzed technical information, while output is customized materials for sales proposals. 【0453】 Step 6: 【0454】 The terminal receives proposal materials provided by the server and displays them to the user. Sales representatives use this information to prepare and execute proposal activities with customers. The input is proposal materials from the server, and the output is proposal information available to the sales representatives. 【0455】 Step 7: 【0456】 Users update new customer information obtained through sales activities using the digital business card management function. This ensures that the system maintains the most up-to-date customer data in conjunction with the server, building a foundation for more effective sales activities. The input is customer information obtained as a result of sales activities, and the output is the updated customer database. 【0457】 (Application Example 1) 【0458】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0459】 In today's business environment, improving the efficiency of information gathering and proposal development in corporate sales activities is a crucial challenge. In particular, accurately understanding customer purchasing behavior and needs, and promptly providing optimal proposals accordingly, is essential. However, traditional methods require significant time and effort for information gathering and analysis, making it difficult to substantially improve the efficiency of sales activities. 【0460】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0461】 In this invention, the server includes means for automatically collecting publicly available data, including technical information; means for analyzing the publicly available data and evaluating its relevance to customer groups; and means for identifying responsible personnel within the customer groups based on the analysis. This makes it possible to analyze customer purchase history and behavioral patterns and propose optimized payment plans. 【0462】 "Technical information" refers to data and knowledge related to technology, and specifically includes information such as patent documents, academic presentations, and technical reports. 【0463】 "Public data" is a general term for information that is accessible to the public through the internet, databases, etc., and includes technical information and market data. 【0464】 A "customer group" refers to a collection of corporations or individuals who have an interest in a particular product or service, and is primarily the target of sales activities. 【0465】 A "person in charge" is an individual responsible for a specific task or project, and in sales activities, this refers to a person involved in decision-making within a group of customers. 【0466】 "Purchase history" refers to records of past purchases and is data that provides clues to understanding a customer's consumption behavior. 【0467】 "Behavioral patterns" refer to the tendencies of customers in their repeated consumption and selection, and are used to predict future needs. 【0468】 A "payment plan" is a plan that outlines the payment methods and conditions offered to customers, and is designed with customer convenience and the company's profits in mind. 【0469】 To implement this invention, a server with high-speed processing capabilities and terminals for use by sales representatives are required. The server automatically collects publicly available data, including technical information, from the internet and analyzes that data. Generative AI models are used for the analysis to filter and select only relevant information. This process forms the foundation for proposing optimal products and services to a group of customers. 【0470】 Furthermore, the server has the ability to analyze customer purchase history and behavioral patterns and propose optimized payment plans. This function allows for a quick response to customer needs and significantly improves the efficiency of sales activities. Sales representatives receive these analysis results from the server via their terminals, create detailed proposals and sales materials, and make accurate proposals to customers. 【0471】 For example, if a sales representative needs to propose a new financial product to a client, the server retrieves publicly available market data, analyzes it, and identifies the target client segment. It then generates a settlement plan that takes into account the client's past trading patterns and sends it to the terminal. This allows the representative to quickly provide a tailored proposal to the client. 【0472】 A possible prompt message could be something like, "Please tell me how to identify potential customers who might be interested in a new product and suggest the best payment plan for them." 【0473】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0474】 Step 1: 【0475】 The server automatically collects technical information from publicly available data sources on the internet. The input is a set of URLs for publicly available technical information, and the output is the retrieved technical data. In this step, crawler software is used to periodically visit specified websites and retrieve the latest technical information. 【0476】 Step 2: 【0477】 The server analyzes the collected technical data and filters it using a generative AI model. The input is the collected technical data, and the output is highly relevant technical information. In this step, the AI ​​model is used to automatically determine the category and relevance of each data point. 【0478】 Step 3: 【0479】 The server identifies the relevant personnel within the customer group based on the analysis results. The input is filtered technical information and a customer database, and the output is a list of personnel. In this step, the system searches the database for personnel associated with technical information that matches the customer's needs. 【0480】 Step 4: 【0481】 The server generates information for proposals to be presented to the relevant personnel. The input is the identified personnel and related technical information, and the output is a draft proposal. This step utilizes a function that uses an AI model to automatically create proposals that take into account the needs of each personnel. 【0482】 Step 5: 【0483】 The user (sales representative) receives a draft proposal from the server via their terminal and customizes the content as needed. The input is a draft proposal, and the output is the final proposal. In this step, the sales representative reviews the proposal on their terminal and makes adjustments to optimize it for individual customers. 【0484】 Step 6: 【0485】 The user presents the final proposal to the customer. In this step, the proposal is made as a sales activity, and the concrete output is the successful completion of the deal with the customer. Through this process, sales representatives can efficiently approach customers and achieve results. 【0486】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0487】 This invention combines an emotion engine with a corporate sales support system to support sales activities based on the user's emotional state. This system mainly consists of three elements: a server, a terminal, and a user. 【0488】 First, the server collects publicly available data and analyzes it by comparing it with information from a business card management database. A generative AI model is used in this process to filter out only relevant technical information, thereby accurately identifying the appropriate contact person within the customer organization. This generates information to propose the most suitable products and services to sales representatives. 【0489】 The emotion engine recognizes the user's emotional state in real time and customizes the information it suggests. The device uses video and audio data input from the user's camera and microphone to perform emotion analysis. This optimizes the presentation order of suggested information received from the server according to the user's emotions. Furthermore, it considers the user's past emotional history and incorporates a mechanism to improve sales strategies through feedback. 【0490】 As a concrete example, consider a scenario where a sales representative is trying to propose a new product to an existing customer. The server collects relevant technical information, identifies the customer representative, and creates the proposal. The terminal assesses the user's emotions in real time and adjusts the order of the proposal to make it easier to understand. For example, if the system determines that the user is nervous, it will first present elements that have a relaxing effect before moving on to the specific proposal. 【0491】 In this way, the present invention can streamline sales activities and establish effective communication. This is expected to lead to improved sales results. 【0492】 The following describes the processing flow. 【0493】 Step 1: 【0494】 The server collects publicly available data. 【0495】 The server uses automated crawling technology to periodically collect technical information from relevant academic societies and news sites. Then, natural language processing is used to extract important keywords from the collected data and classify them as relevant information. 【0496】 Step 2: 【0497】 The server analyzes the data. 【0498】 The server uses a generative AI model to filter the collected data and cross-reference it with a business card management database. This allows for an assessment of the relevance to the customer organization and the identification of the appropriate contact person. This analysis also takes into account past sales history and contact person information. 【0499】 Step 3: 【0500】 The emotion engine recognizes the user's emotions. 【0501】 The device utilizes the user's camera and microphone to capture their facial expressions and voice tone. An emotion engine analyzes this data to determine the user's current emotional state in real time. 【0502】 Step 4: 【0503】 The server generates suggestion information, which is then optimized by an emotion engine. 【0504】 The server generates information to suggest appropriate products and services based on the analysis results. The emotion engine optimizes the order in which this information is presented based on the user's emotional state, adjusting it so that the information is displayed in the most effective way for the user. 【0505】 Step 5: 【0506】 The device provides information to the user. 【0507】 The device presents users with optimized proposal information. This allows users to create materials tailored to their sales activities and effectively communicate their proposals to customers. Sales strategies can also be improved by referring to past sentiment history. 【0508】 (Example 2) 【0509】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0510】 In corporate sales activities, it is crucial to appropriately identify the customer's contact person and tailor proposals accordingly. However, traditional systems often failed to adequately consider the customer's emotional state, resulting in ineffective proposals. Furthermore, it was not easy to utilize proposal feedback to improve sales strategies. These challenges need to be addressed. 【0511】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0512】 In this invention, the server includes means for collecting publicly available data, including technical information; means for analyzing the publicly available data and evaluating its relevance to customer organizations; and means for identifying responsible personnel based on the analysis. This enables the provision of optimal proposals tailored to the customer's interests and emotional state, thereby improving the efficiency of sales activities and establishing effective communication. 【0513】 "Technical information" refers to knowledge and data related to a specific field, and is information that is useful for proposing products and services. 【0514】 "Public data" refers to information that is generally accessible on the internet, and includes news articles, social media posts, press releases, and so on. 【0515】 A "customer organization" refers to a legal entity or corporate entity that is a potential or existing purchaser of a product or service. 【0516】 "Responsible person" refers to an individual or person in a position within a customer organization who is involved in proposing a specific product or service. 【0517】 A "generative AI model" refers to a model that uses artificial intelligence to analyze data and creatively generate or optimize information. 【0518】 "Emotional state" refers to the user's psychological state and includes specific emotions such as excitement, relaxation, and tension. 【0519】 "Feedback" refers to the reactions and evaluations received from users and customers, and is information used to improve systems and proposed solutions. 【0520】 This invention enables a corporate sales support system to analyze customer emotions in real time and make optimal sales proposals based on that analysis. This system mainly consists of three elements: a server, a terminal, and a user. 【0521】 First, the server is responsible for collecting publicly available data. Specifically, it automatically collects data, including technical information, from news articles, press releases, and social media posts on the internet. This data is then cross-referenced with a business card management database to analyze its relevance to customer organizations. A generative AI model is used for the analysis, filtering out only relevant information to identify the appropriate contact person within the customer organization. Finally, it generates information on the most suitable products and services to propose to the identified contact person. 【0522】 Next, the device uses the user's camera and microphone to acquire video and audio data from the user. This data is analyzed in real time by an emotion engine to recognize the user's emotional state. For example, it can determine whether the user is tense or relaxed. Based on this emotion analysis, the device optimizes the presentation order of suggested information received from the server and provides it to the user. 【0523】 Users conduct sales activities based on this optimized proposal information. The feedback provided by users is used to improve the overall sales strategy of the system and is reflected in future proposals. 【0524】 As a concrete example, consider a scenario where a new product is being proposed. The server collects technical information relevant to the customer and identifies the appropriate person to contact. The terminal analyzes the user's emotions in real time and presents the proposal content in the optimal order. For example, a nervous user would be presented with relaxing information first, followed by product information. 【0525】 An example of a prompt message might be: "We want to propose a new product released this week to a customer. Identify the customer's contact person and generate a presentation that includes a relaxing proposal." 【0526】 In this way, the present invention provides a system for supporting efficient and effective sales activities. 【0527】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0528】 Step 1: 【0529】 The server collects publicly available data from the internet. Inputs include news articles, press releases, and social media posts. This data is stored in a database, and the server processes it to extract technical information relevant to the customer. The output is a dataset of organized technical information. 【0530】 Step 2: 【0531】 The server retrieves customer information from a business card management database. The input is business card information from the database. This business card information is compared with technical information from publicly available data to identify the appropriate contact person within the customer organization. The output is a list of the identified contact persons. 【0532】 Step 3: 【0533】 The server utilizes a generative AI model to generate information on the most suitable products and services to recommend to identified contacts. The input consists of a list of identified contacts and related technical information. Through data processing and calculations, personalized recommendations are created. The output is optimized recommendation information. 【0534】 Step 4: 【0535】 The device uses the user's camera and microphone to acquire video and audio data from the user. The input is the user's real-time video and audio data. Using this data, the emotion engine analyzes the user's emotional state. The output is the evaluation result of the user's emotional state. 【0536】 Step 5: 【0537】 The terminal optimizes the presentation order of suggested information received from the server based on the user's emotional state. The input consists of suggested information from the server and the user's emotional state. The terminal adjusts the order of the suggested information to present it in the most optimal way for the user. The output is the optimized presentation order of the suggested information. 【0538】 Step 6: 【0539】 The user reviews the presented proposal information and conducts sales activities. The input is the optimized and presented proposal information. The user presents this to the customer and receives feedback. The output is the results of the sales activity and the feedback. The feedback is re-entered into the system and used to improve future sales strategies. 【0540】 (Application Example 2) 【0541】 Next, we will explain Application Example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0542】 In recent years, there has been a growing need for more efficient sales activities and customized proposals. However, conventional sales support systems lack the ability to provide real-time information that takes into account the emotional state of customers, making it difficult to make optimal proposals for individual customers. As a result, there is a lack of effective communication that meets customer needs, which hinders the improvement of sales results. 【0543】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0544】 In this invention, the server includes means for automatically collecting publicly available data including technical indicators, means for analyzing the publicly available data and evaluating its relevance to customer groups, means for identifying personnel within customer groups based on the analysis, means for analyzing the user's emotional state in real time using a camera and microphone, and means for optimizing the presentation order of suggestion information based on the emotional state. This enables suggestions optimized according to the user's emotions, thereby improving the effectiveness of sales activities. 【0545】 "Technical indicators" are a collection of specific numerical values ​​and information used to clarify the features and characteristics of a product or service. 【0546】 "Public data" refers to data obtained from publicly available sources and used for a specific purpose. 【0547】 A "customer group" is a collection of corporations or individuals that are expected to use or purchase a product or service. 【0548】 A "person in charge" is an individual within a customer group who holds a specific role or responsibility, and is identified as the person to whom sales or proposals are made. 【0549】 Cameras and microphones are devices used to acquire images and sounds, and are used as a means of data input. 【0550】 "Emotional state" refers to an individual's internal state of sensations and emotions at a given moment, and it manifests as a reaction to external stimuli. 【0551】 "Proposal information" refers to materials and data created to recommend specific products or services to customers. 【0552】 "Optimizing the presentation order" means adjusting the order and method of conveying information to be as effective as possible, based on user reactions and emotions. 【0553】 To realize this invention, the system consists of three main elements: a server, a terminal, and a user. 【0554】 The server automatically collects publicly available data, including technical metrics, and filters it using a generative AI model. This allows it to evaluate relevance to customer groups and generate information to suggest appropriate products and services to identified individuals. The server plays a central role in efficiently processing large amounts of data and providing optimal recommendation information. 【0555】 The device functions as an interface with the user, using hardware such as a camera and microphone to analyze the user's emotional state in real time. Specifically, it uses image processing technology to analyze the user's facial expressions and speech recognition technology to analyze the user's tone of voice. This allows it to grasp the user's instantaneous emotional state and transmit that information to a server. 【0556】 Users interact with the system through a provided terminal. For example, in a consumer robot system for a home, if the terminal determines that the user is relaxed, it may recommend relaxing music. Conversely, if the terminal determines that the user is tired, it may suggest, "Why not take a short break and start an activity to refresh yourself?" 【0557】 An example of a prompt statement is, "Analyze the residents' emotional state in real time and offer suggestions for relaxation or cheering up." This prompt statement functions as a keyword that supports the process by which the generative AI model performs emotion analysis and information optimization. 【0558】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0559】 Step 1: 【0560】 The server automatically collects publicly available data. In this process, it retrieves unstructured data from the internet and corporate open databases and stores it in its internal database. The input is publicly available data, and the output is the collected raw data. 【0561】 Step 2: 【0562】 The server uses a generative AI model to filter the collected data. It utilizes natural language processing and machine learning techniques with the AI ​​model to select relevant technical information and evaluate its relevance to the customer group. The input is the raw data collected in step 1, and the output is the filtered, relevant data. 【0563】 Step 3: 【0564】 The server identifies the relevant personnel within a customer group based on filtered data. Using a business card database, it analyzes the personnel's duties and roles to identify those who can most effectively receive the proposed information. The input consists of filtered data and business card information, and the output is a list of identified personnel. 【0565】 Step 4: 【0566】 The device analyzes the user's emotional state in real time. It collects video and audio using a camera and microphone, and performs image processing and audio analysis using a generative AI model. The input is the user's video and audio data, and the output is the analyzed emotional state data. 【0567】 Step 5: 【0568】 The device optimizes the presentation order of suggested information based on the analysis results. It takes into account the user's emotional state and adjusts the timing and order to present the suggested information to the user at the optimal time. Specifically, it presents suggestions that promote relaxation or pique the user's interest first, followed by detailed information. The input is the analyzed emotional state and suggested information, and the output is information on the optimized presentation order. 【0569】 Step 6: 【0570】 The user decides whether to accept the optimized suggestions. If they accept, they communicate their intention to proceed with the suggested activities or purchase procedures to the device. The input is the optimized information presented, and the output is the user's choices and feedback. 【0571】 The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0572】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0573】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314. 【0574】 [Fourth Embodiment] 【0575】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0576】 As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server. 【0577】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0578】 The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52. 【0579】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0580】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0581】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0582】 The controlled 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0583】 Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0584】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0585】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0586】 In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0587】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0588】 This invention is a system designed to support specific corporate sales activities and is implemented through a configuration centered on a server, terminals, and users. The server has high-speed processing capabilities and automatically collects publicly available data, including large amounts of technical information. This enables reliable and rapid acquisition of the information users need. The server also uses advanced algorithms and generative AI to analyze the collected data, evaluate the relevance of the data, and organize the information so that users can use it efficiently. 【0589】 Specifically, the server first crawls websites and databases on the internet to extract necessary technical information. This includes filtering useful and relevant information from publicly available data that is regularly updated. Next, the server analyzes the retrieved information to identify the appropriate person within the customer organization. This provides a foundation for suggesting information about the most suitable products or services for the target customer. 【0590】 Sales representatives, as users, receive analysis results from the server via their terminals. They then use this information to create proposals and sales materials, and conduct concrete sales activities. The proposals generated by the server are customized according to customer needs, supporting users in conducting sales activities efficiently. This system utilizes a digital business card management function to facilitate updating and managing customer information, and can perform more precise data analysis in conjunction with the server. 【0591】 As a concrete example, consider a scenario where a sales representative is looking for customers interested in a new cloud technology. The server collects the latest conference presentations on relevant technical information and identifies recommended experts from a publicly available list. Subsequently, proposals generated by the server are sent to the terminal, allowing the user to quickly and accurately engage in sales activities with customers. In this way, the system of the present invention significantly improves the efficiency of sales activities. 【0592】 The following describes the processing flow. 【0593】 Step 1: 【0594】 The server collects publicly available data. 【0595】 The server uses a web crawler to visit websites containing academic presentations and news articles at a set frequency, automatically collecting articles that include technical information. During this process, natural language processing technology is used to extract relevant keywords from the articles and tag them to determine their importance. 【0596】 Step 2: 【0597】 The server analyzes the data. 【0598】 The server compares the collected information with data in the digital business card management system. Using customer names and related keywords, it searches for past business negotiation history and contact person information, and uses generating AI to evaluate the relevance of the information. This identifies information that is beneficial to the customer. 【0599】 Step 3: 【0600】 The server identifies the person in charge. 【0601】 Based on the analysis results, the server lists the contacts with strong relationships within the customer organization. Using a generative AI model, it identifies the names and titles of appropriate contacts from publicly available information and business card data, and stores this information in a database for use in sales activities. 【0602】 Step 4: 【0603】 The server generates the suggestion information. 【0604】 The server generates materials to suggest appropriate products and services based on information related to the identified person in charge. This allows the user to take the most effective approach to the customer. 【0605】 Step 5: 【0606】 The device provides information to the user. 【0607】 The terminal receives proposal details and contact person information generated from the server and presents them to the user. Based on this data, the user can create proposals and other materials necessary for sales activities and make concrete sales approaches to customers. 【0608】 (Example 1) 【0609】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0610】 Modern sales activities require the rapid and efficient acquisition of highly relevant information from a vast amount of technical data, but traditional methods fail to adequately achieve this. In particular, data collection and analysis for creating specific proposal materials needed by sales representatives are cumbersome and time-consuming. Therefore, a system is needed to automate information selection and the generation of customized proposals, thereby supporting efficient sales activities. 【0611】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0612】 In this invention, the server includes means for automatically collecting publicly available data, including technical information; means for filtering the publicly available data using a generating AI model and selecting highly relevant information; and means for analyzing the filtered data and evaluating its relevance to customer organizations. This enables sales representatives to quickly collect the information they need and engage in accurate proposal activities. 【0613】 "Technical information" refers to data and knowledge related to science and technology, and includes research results, technical specifications, patent documents, etc. 【0614】 "Public data" refers to information that is generally accessible on the internet or other resources, and is provided in a form that anyone can use. 【0615】 A "generative AI model" is a mathematical model that uses artificial intelligence to generate new output from data, and is built on machine learning and deep learning technologies. 【0616】 "Filtering" refers to the process of selecting specific information from collected data as needed and excluding other information. 【0617】 "Analysis" is the process of thoroughly investigating and studying collected data to find useful information and patterns within it. 【0618】 A "customer organization" refers to the companies or groups that are the target of sales activities, and the recipients of goods and services. 【0619】 "Responsible person" refers to an individual within a client organization who is responsible for a specific task or project. 【0620】 "Proposal details" refers to information that summarizes the details, benefits, and usage methods of products and services presented to customers during sales or business negotiations. 【0621】 This invention is a system designed to support sales activities and is centered around a server, terminals, and users. Specific embodiments are shown below. 【0622】 The server possesses high-speed processing capabilities and automatically collects technical information from websites and databases on the internet using programming languages ​​such as Python and R. Specific software used here includes Beautiful Soup and Scrapy for data scraping. Using these tools, the server extracts relevant technical information based on specific keywords. 【0623】 Furthermore, the server utilizes generative AI models to filter the collected data. These generative AI models employ deep learning frameworks such as TensorFlow and PyTorch to extract only highly relevant information. The filtered data is further analyzed using natural language processing techniques to assess its relevance to the customer organization. Specifically, machine learning algorithms are used to evaluate information that matches the customer's industry and needs. 【0624】 Based on the filtering and analysis results, the server identifies the appropriate contact person within the customer organization. This process matches business card information retrieved from the database and updates the relevant new contact person information. This clarifies the target of sales activities. 【0625】 AI is used to generate proposals. This automatically creates customized proposals and sales materials tailored to customer needs. Sales representatives, as users, receive these proposals via their devices and use them in their specific sales activities. This process utilizes tablets and laptops to improve the immediacy and convenience of information. 【0626】 As a concrete example, consider the need of a sales representative who wants to "gather information on the latest trends in cloud technology and create materials to propose to new customers." In this case, an example of a prompt message would be, "Gather information on the latest trends in cloud technology and form the basis for your next sales proposal." This would allow the server to efficiently collect and analyze relevant data and provide the sales representative with a useful proposal. 【0627】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0628】 Step 1: 【0629】 The server automatically collects technical information by patrolling websites and databases on the internet. Specifically, it uses Python libraries such as Beautiful Soup and Scrapy to retrieve information related to specific keywords. The input for this step is the URLs and keywords to be collected, and the output is the collected technical information data. 【0630】 Step 2: 【0631】 The server filters the collected technical information using a generating AI model. Here, the AI ​​model analyzes the data's characteristics and excludes irrelevant information to select the most relevant data. The input is the collected technical information data, and the output is the dataset deemed highly relevant. For example, it might extract only information related to new cloud technologies. 【0632】 Step 3: 【0633】 The server analyzes the filtered data using natural language processing techniques and evaluates its relevance to the customer organization. This process utilizes machine learning algorithms to analyze patterns within the data and identify information relevant to customer needs. The input is a filtered dataset, and the output is an identification of data beneficial to the customer organization. 【0634】 Step 4: 【0635】 The server identifies the appropriate person within the customer organization based on the analysis results. In this step, it matches business card information from the database to find the person associated with a specific job title or field. The inputs are the analysis results and business card information, and the output is detailed information about the identified person. 【0636】 Step 5: 【0637】 The server uses AI generation to customize proposals and generate information tailored to the identified contact person. This process includes creating proposals and sales materials that meet customer needs. Inputs are identified contact person information and collected / analyzed technical information, while output is customized materials for sales proposals. 【0638】 Step 6: 【0639】 The terminal receives proposal materials provided by the server and displays them to the user. Sales representatives use this information to prepare and execute proposal activities with customers. The input is proposal materials from the server, and the output is proposal information available to the sales representatives. 【0640】 Step 7: 【0641】 Users update new customer information obtained through sales activities using the digital business card management function. This ensures that the system maintains the most up-to-date customer data in conjunction with the server, building a foundation for more effective sales activities. The input is customer information obtained as a result of sales activities, and the output is the updated customer database. 【0642】 (Application Example 1) 【0643】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0644】 In today's business environment, improving the efficiency of information gathering and proposal development in corporate sales activities is a crucial challenge. In particular, accurately understanding customer purchasing behavior and needs, and promptly providing optimal proposals accordingly, is essential. However, traditional methods require significant time and effort for information gathering and analysis, making it difficult to substantially improve the efficiency of sales activities. 【0645】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0646】 In this invention, the server includes means for automatically collecting publicly available data, including technical information; means for analyzing the publicly available data and evaluating its relevance to customer groups; and means for identifying responsible personnel within the customer groups based on the analysis. This makes it possible to analyze customer purchase history and behavioral patterns and propose optimized payment plans. 【0647】 "Technical information" refers to data and knowledge related to technology, and specifically includes information such as patent documents, academic presentations, and technical reports. 【0648】 "Public data" is a general term for information that is accessible to the public through the internet, databases, etc., and includes technical information and market data. 【0649】 A "customer group" refers to a collection of corporations or individuals who have an interest in a particular product or service, and is primarily the target of sales activities. 【0650】 A "person in charge" is an individual responsible for a specific task or project, and in sales activities, this refers to a person involved in decision-making within a group of customers. 【0651】 "Purchase history" refers to records of past purchases and is data that provides clues to understanding a customer's consumption behavior. 【0652】 "Behavioral patterns" refer to the tendencies of customers in their repeated consumption and selection, and are used to predict future needs. 【0653】 A "payment plan" is a plan that outlines the payment methods and conditions offered to customers, and is designed with customer convenience and the company's profits in mind. 【0654】 To implement this invention, a server with high-speed processing capabilities and terminals for use by sales representatives are required. The server automatically collects publicly available data, including technical information, from the internet and analyzes that data. Generative AI models are used for the analysis to filter and select only relevant information. This process forms the foundation for proposing optimal products and services to a group of customers. 【0655】 Furthermore, the server has the ability to analyze customer purchase history and behavioral patterns and propose optimized payment plans. This function allows for a quick response to customer needs and significantly improves the efficiency of sales activities. Sales representatives receive these analysis results from the server via their terminals, create detailed proposals and sales materials, and make accurate proposals to customers. 【0656】 For example, if a sales representative needs to propose a new financial product to a client, the server retrieves publicly available market data, analyzes it, and identifies the target client segment. It then generates a settlement plan that takes into account the client's past trading patterns and sends it to the terminal. This allows the representative to quickly provide a tailored proposal to the client. 【0657】 A possible prompt message could be something like, "Please tell me how to identify potential customers who might be interested in a new product and suggest the best payment plan for them." 【0658】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0659】 Step 1: 【0660】 The server automatically collects technical information from publicly available data sources on the internet. The input is a set of URLs for publicly available technical information, and the output is the retrieved technical data. In this step, crawler software is used to periodically visit specified websites and retrieve the latest technical information. 【0661】 Step 2: 【0662】 The server analyzes the collected technical data and filters it using a generative AI model. The input is the collected technical data, and the output is highly relevant technical information. In this step, the AI ​​model is used to automatically determine the category and relevance of each data point. 【0663】 Step 3: 【0664】 The server identifies the relevant personnel within the customer group based on the analysis results. The input is filtered technical information and a customer database, and the output is a list of personnel. In this step, the system searches the database for personnel associated with technical information that matches the customer's needs. 【0665】 Step 4: 【0666】 The server generates information for proposals to be presented to the relevant personnel. The input is the identified personnel and related technical information, and the output is a draft proposal. This step utilizes a function that uses an AI model to automatically create proposals that take into account the needs of each personnel. 【0667】 Step 5: 【0668】 The user (sales representative) receives a draft proposal from the server via their terminal and customizes the content as needed. The input is a draft proposal, and the output is the final proposal. In this step, the sales representative reviews the proposal on their terminal and makes adjustments to optimize it for individual customers. 【0669】 Step 6: 【0670】 The user presents the final proposal to the customer. In this step, the proposal is made as a sales activity, and the concrete output is the successful completion of the deal with the customer. Through this process, sales representatives can efficiently approach customers and achieve results. 【0671】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0672】 This invention combines an emotion engine with a corporate sales support system to support sales activities based on the user's emotional state. This system mainly consists of three elements: a server, a terminal, and a user. 【0673】 First, the server collects publicly available data and analyzes it by comparing it with information from a business card management database. A generative AI model is used in this process to filter out only relevant technical information, thereby accurately identifying the appropriate contact person within the customer organization. This generates information to propose the most suitable products and services to sales representatives. 【0674】 The emotion engine recognizes the user's emotional state in real time and customizes the information it suggests. The device uses video and audio data input from the user's camera and microphone to perform emotion analysis. This optimizes the presentation order of suggested information received from the server according to the user's emotions. Furthermore, it considers the user's past emotional history and incorporates a mechanism to improve sales strategies through feedback. 【0675】 As a concrete example, consider a scenario where a sales representative is trying to propose a new product to an existing customer. The server collects relevant technical information, identifies the customer representative, and creates the proposal. The terminal assesses the user's emotions in real time and adjusts the order of the proposal to make it easier to understand. For example, if the system determines that the user is nervous, it will first present elements that have a relaxing effect before moving on to the specific proposal. 【0676】 In this way, the present invention can streamline sales activities and establish effective communication. This is expected to lead to improved sales results. 【0677】 The following describes the processing flow. 【0678】 Step 1: 【0679】 The server collects publicly available data. 【0680】 The server uses automated crawling technology to periodically collect technical information from relevant academic societies and news sites. Then, natural language processing is used to extract important keywords from the collected data and classify them as relevant information. 【0681】 Step 2: 【0682】 The server analyzes the data. 【0683】 The server uses a generative AI model to filter the collected data and cross-reference it with a business card management database. This allows for an assessment of the relevance to the customer organization and the identification of the appropriate contact person. This analysis also takes into account past sales history and contact person information. 【0684】 Step 3: 【0685】 The emotion engine recognizes the user's emotions. 【0686】 The device utilizes the user's camera and microphone to capture their facial expressions and voice tone. An emotion engine analyzes this data to determine the user's current emotional state in real time. 【0687】 Step 4: 【0688】 The server generates suggestion information, which is then optimized by an emotion engine. 【0689】 The server generates information to suggest appropriate products and services based on the analysis results. The emotion engine optimizes the order in which this information is presented based on the user's emotional state, adjusting it so that the information is displayed in the most effective way for the user. 【0690】 Step 5: 【0691】 The device provides information to the user. 【0692】 The device presents users with optimized proposal information. This allows users to create materials tailored to their sales activities and effectively communicate their proposals to customers. Sales strategies can also be improved by referring to past sentiment history. 【0693】 (Example 2) 【0694】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0695】 In corporate sales activities, it is crucial to appropriately identify the customer's contact person and tailor proposals accordingly. However, traditional systems often failed to adequately consider the customer's emotional state, resulting in ineffective proposals. Furthermore, it was not easy to utilize proposal feedback to improve sales strategies. These challenges need to be addressed. 【0696】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0697】 In this invention, the server includes means for collecting publicly available data, including technical information; means for analyzing the publicly available data and evaluating its relevance to customer organizations; and means for identifying responsible personnel based on the analysis. This enables the provision of optimal proposals tailored to the customer's interests and emotional state, thereby improving the efficiency of sales activities and establishing effective communication. 【0698】 "Technical information" refers to knowledge and data related to a specific field, and is information that is useful for proposing products and services. 【0699】 "Public data" refers to information that is generally accessible on the internet, and includes news articles, social media posts, press releases, and so on. 【0700】 A "customer organization" refers to a legal entity or corporate entity that is a potential or existing purchaser of a product or service. 【0701】 "Responsible person" refers to an individual or person in a position within a customer organization who is involved in proposing a specific product or service. 【0702】 A "generative AI model" refers to a model that uses artificial intelligence to analyze data and creatively generate or optimize information. 【0703】 "Emotional state" refers to the user's psychological state and includes specific emotions such as excitement, relaxation, and tension. 【0704】 "Feedback" refers to the reactions and evaluations received from users and customers, and is information used to improve systems and proposed solutions. 【0705】 This invention enables a corporate sales support system to analyze customer emotions in real time and make optimal sales proposals based on that analysis. This system mainly consists of three elements: a server, a terminal, and a user. 【0706】 First, the server is responsible for collecting publicly available data. Specifically, it automatically collects data, including technical information, from news articles, press releases, and social media posts on the internet. This data is then cross-referenced with a business card management database to analyze its relevance to customer organizations. A generative AI model is used for the analysis, filtering out only relevant information to identify the appropriate contact person within the customer organization. Finally, it generates information on the most suitable products and services to propose to the identified contact person. 【0707】 Next, the device uses the user's camera and microphone to acquire video and audio data from the user. This data is analyzed in real time by an emotion engine to recognize the user's emotional state. For example, it can determine whether the user is tense or relaxed. Based on this emotion analysis, the device optimizes the presentation order of suggested information received from the server and provides it to the user. 【0708】 Users conduct sales activities based on this optimized proposal information. The feedback provided by users is used to improve the overall sales strategy of the system and is reflected in future proposals. 【0709】 As a concrete example, consider a scenario where a new product is being proposed. The server collects technical information relevant to the customer and identifies the appropriate person to contact. The terminal analyzes the user's emotions in real time and presents the proposal content in the optimal order. For example, a nervous user would be presented with relaxing information first, followed by product information. 【0710】 An example of a prompt message might be: "We want to propose a new product released this week to a customer. Identify the customer's contact person and generate a presentation that includes a relaxing proposal." 【0711】 In this way, the present invention provides a system for supporting efficient and effective sales activities. 【0712】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0713】 Step 1: 【0714】 The server collects publicly available data from the internet. Inputs include news articles, press releases, and social media posts. This data is stored in a database, and the server processes it to extract technical information relevant to the customer. The output is a dataset of organized technical information. 【0715】 Step 2: 【0716】 The server retrieves customer information from a business card management database. The input is business card information from the database. This business card information is compared with technical information from publicly available data to identify the appropriate contact person within the customer organization. The output is a list of the identified contact persons. 【0717】 Step 3: 【0718】 The server utilizes a generative AI model to generate information on the most suitable products and services to recommend to identified contacts. The input consists of a list of identified contacts and related technical information. Through data processing and calculations, personalized recommendations are created. The output is optimized recommendation information. 【0719】 Step 4: 【0720】 The device uses the user's camera and microphone to acquire video and audio data from the user. The input is the user's real-time video and audio data. Using this data, the emotion engine analyzes the user's emotional state. The output is the evaluation result of the user's emotional state. 【0721】 Step 5: 【0722】 The terminal optimizes the presentation order of suggested information received from the server based on the user's emotional state. The input consists of suggested information from the server and the user's emotional state. The terminal adjusts the order of the suggested information to present it in the most optimal way for the user. The output is the optimized presentation order of the suggested information. 【0723】 Step 6: 【0724】 The user reviews the presented proposal information and conducts sales activities. The input is the optimized and presented proposal information. The user presents this to the customer and receives feedback. The output is the results of the sales activity and the feedback. The feedback is re-entered into the system and used to improve future sales strategies. 【0725】 (Application Example 2) 【0726】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0727】 In recent years, there has been a growing need for more efficient sales activities and customized proposals. However, conventional sales support systems lack the ability to provide real-time information that takes into account the emotional state of customers, making it difficult to make optimal proposals for individual customers. As a result, there is a lack of effective communication that meets customer needs, which hinders the improvement of sales results. 【0728】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0729】 In this invention, the server includes means for automatically collecting publicly available data including technical indicators, means for analyzing the publicly available data and evaluating its relevance to customer groups, means for identifying personnel within customer groups based on the analysis, means for analyzing the user's emotional state in real time using a camera and microphone, and means for optimizing the presentation order of suggestion information based on the emotional state. This enables suggestions optimized according to the user's emotions, thereby improving the effectiveness of sales activities. 【0730】 "Technical indicators" are a collection of specific numerical values ​​and information used to clarify the features and characteristics of a product or service. 【0731】 "Public data" refers to data obtained from publicly available sources and used for a specific purpose. 【0732】 A "customer group" is a collection of corporations or individuals that are expected to use or purchase a product or service. 【0733】 A "person in charge" is an individual within a customer group who holds a specific role or responsibility, and is identified as the person to whom sales or proposals are made. 【0734】 Cameras and microphones are devices used to acquire images and sounds, and are used as a means of data input. 【0735】 "Emotional state" refers to an individual's internal state of sensations and emotions at a given moment, and it manifests as a reaction to external stimuli. 【0736】 "Proposal information" refers to materials and data created to recommend specific products or services to customers. 【0737】 "Optimizing the presentation order" means adjusting the order and method of conveying information to be as effective as possible, based on user reactions and emotions. 【0738】 To realize this invention, the system consists of three main elements: a server, a terminal, and a user. 【0739】 The server automatically collects publicly available data, including technical metrics, and filters it using a generative AI model. This allows it to evaluate relevance to customer groups and generate information to suggest appropriate products and services to identified individuals. The server plays a central role in efficiently processing large amounts of data and providing optimal recommendation information. 【0740】 The device functions as an interface with the user, using hardware such as a camera and microphone to analyze the user's emotional state in real time. Specifically, it uses image processing technology to analyze the user's facial expressions and speech recognition technology to analyze the user's tone of voice. This allows it to grasp the user's instantaneous emotional state and transmit that information to a server. 【0741】 Users interact with the system through a provided terminal. For example, in a consumer robot system for a home, if the terminal determines that the user is relaxed, it may recommend relaxing music. Conversely, if the terminal determines that the user is tired, it may suggest, "Why not take a short break and start an activity to refresh yourself?" 【0742】 An example of a prompt statement is, "Analyze the residents' emotional state in real time and offer suggestions for relaxation or cheering up." This prompt statement functions as a keyword that supports the process by which the generative AI model performs emotion analysis and information optimization. 【0743】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0744】 Step 1: 【0745】 The server automatically collects publicly available data. In this process, it retrieves unstructured data from the internet and corporate open databases and stores it in its internal database. The input is publicly available data, and the output is the collected raw data. 【0746】 Step 2: 【0747】 The server uses a generative AI model to filter the collected data. It utilizes natural language processing and machine learning techniques with the AI ​​model to select relevant technical information and evaluate its relevance to the customer group. The input is the raw data collected in step 1, and the output is the filtered, relevant data. 【0748】 Step 3: 【0749】 The server identifies the relevant personnel within a customer group based on filtered data. Using a business card database, it analyzes the personnel's duties and roles to identify those who can most effectively receive the proposed information. The input consists of filtered data and business card information, and the output is a list of identified personnel. 【0750】 Step 4: 【0751】 The device analyzes the user's emotional state in real time. It collects video and audio using a camera and microphone, and performs image processing and audio analysis using a generative AI model. The input is the user's video and audio data, and the output is the analyzed emotional state data. 【0752】 Step 5: 【0753】 The device optimizes the presentation order of suggested information based on the analysis results. It takes into account the user's emotional state and adjusts the timing and order to present the suggested information to the user at the optimal time. Specifically, it presents suggestions that promote relaxation or pique the user's interest first, followed by detailed information. The input is the analyzed emotional state and suggested information, and the output is information on the optimized presentation order. 【0754】 Step 6: 【0755】 The user decides whether to accept the optimized suggestions. If they accept, they communicate their intention to proceed with the suggested activities or purchase procedures to the device. The input is the optimized information presented, and the output is the user's choices and feedback. 【0756】 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0757】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0758】 In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0759】 Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion. 【0760】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0761】 These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression. 【0762】 The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become. 【0763】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0764】 The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more." 【0765】 The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values. 【0766】 The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format. 【0767】 In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data. 【0768】 In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56. 【0769】 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. 【0770】 Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56. 【0771】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory. 【0772】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0773】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0774】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0775】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0776】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0777】 The following is further disclosed regarding the embodiments described above. 【0778】 (Claim 1) 【0779】 A means of automatically collecting publicly available data, including technical information, 【0780】 A means for analyzing the aforementioned publicly available data and evaluating its relevance to customer organizations, 【0781】 A means for identifying the person in charge within the customer organization based on the aforementioned analysis, 【0782】 A means for generating information to propose products or services to the aforementioned person in charge, 【0783】 A system that includes this. 【0784】 (Claim 2) 【0785】 The system according to claim 1, comprising means for obtaining business card information from a database and comparing the obtained business card information with the publicly available data that has been analyzed. 【0786】 (Claim 3) 【0787】 The system according to claim 1, further comprising means for filtering the publicly available data using a generative AI model and selecting only the relevant information. 【0788】 "Example 1" 【0789】 (Claim 1) 【0790】 A means of automatically collecting publicly available data, including technical information, 【0791】 A means for filtering the aforementioned publicly available data using a generating AI model and selecting information that is highly relevant, 【0792】 A means for analyzing the filtered data and evaluating its relevance to customer organizations, 【0793】 A means for identifying the appropriate person in the customer organization based on the aforementioned analysis, 【0794】 A means for customizing the proposal content and generating information for the aforementioned identified person, 【0795】 Means for providing the generated information to the terminal, 【0796】 A system that includes this. 【0797】 (Claim 2) 【0798】 The system according to claim 1, comprising means for obtaining business card information from a database, comparing the obtained business card information with the analyzed public data, and updating new contact person information related to the customer organization. 【0799】 (Claim 3) 【0800】 The system according to claim 1, comprising means for automatically generating proposal materials for sales activities based on collected data. 【0801】 "Application Example 1" 【0802】 (Claim 1) 【0803】 A means of automatically collecting publicly available data, including technical information, 【0804】 A means for analyzing the aforementioned publicly available data and evaluating its relationship with customer groups, 【0805】 A means for identifying the person in charge within the customer group based on the aforementioned analysis, 【0806】 A means for generating information to propose products or services to the aforementioned person in charge, 【0807】 A means of analyzing customer purchase history and behavioral patterns and proposing an optimized payment plan, 【0808】 A system that includes this. 【0809】 (Claim 2) 【0810】 The system according to claim 1, comprising means for obtaining business card information from a database and comparing the obtained business card information with the publicly available data that has been analyzed. 【0811】 (Claim 3) 【0812】 The system according to claim 1, further comprising means for filtering the publicly available data using a generative AI model and selecting only the relevant information. 【0813】 "Example 2 of combining an emotion engine" 【0814】 (Claim 1) 【0815】 A means of automatically collecting publicly available data, including technical information, 【0816】 A means for analyzing the aforementioned publicly available data and evaluating its relevance to customer organizations, 【0817】 A means for identifying the person in charge within the customer organization based on the aforementioned analysis, 【0818】 A means for generating information to propose products or services to the aforementioned person in charge, 【0819】 A means of analyzing signals to obtain the user's emotional state, 【0820】 A means for optimizing the presentation order of proposed information based on the aforementioned emotional state, 【0821】 The aforementioned optimized proposal information is used as a means to improve the sales strategy through feedback, 【0822】 A system that includes this. 【0823】 (Claim 2) 【0824】 The system according to claim 1, comprising means for obtaining business card information from a database and comparing the obtained business card information with the publicly available data that has been analyzed. 【0825】 (Claim 3) 【0826】 The system according to claim 1, further comprising means for filtering the publicly available data using a generative AI model and selecting only the relevant information. 【0827】 "Application example 2 when combining with an emotional engine" 【0828】 (Claim 1) 【0829】 A means of automatically collecting publicly available data, including technical indicators, 【0830】 A means for analyzing the aforementioned publicly available data and evaluating its relationship with customer groups, 【0831】 A means for identifying the person in charge within the customer group based on the aforementioned analysis, 【0832】 A means for generating information to propose products or services to the aforementioned person in charge, 【0833】 A method for analyzing the emotional state of users in real time using cameras and microphones, 【0834】 A means for optimizing the presentation order of proposed information based on the aforementioned emotional state, 【0835】 A system that includes this. 【0836】 (Claim 2) 【0837】 The system according to claim 1, comprising means for obtaining business card information from a database and comparing the obtained business card information with the publicly available data that has been analyzed. 【0838】 (Claim 3) 【0839】 The system according to claim 1, further comprising means for filtering the publicly available data using a generative AI model and selecting only the relevant information. [Explanation of symbols] 【0840】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] A means of automatically collecting publicly available data, including technical information, A means for analyzing the aforementioned publicly available data and evaluating its relevance to customer organizations, A means for identifying the person in charge within the customer organization based on the aforementioned analysis, A means for generating information to propose products or services to the aforementioned person in charge, A system that includes this. [Claim 2] The system according to claim 1, comprising means for obtaining business card information from a database and comparing the obtained business card information with the publicly available data that has been analyzed. [Claim 3] The system according to claim 1, further comprising means for filtering the publicly available data using a generative AI model and selecting only the relevant information.

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