system

Abstract

We provide the system. [Solution] Means for obtaining data from information exchange means, A means of analyzing acquired data and extracting important information, A means of registering and managing tasks based on the extracted information, Means for generating and sending notifications related to business operations, A means of providing an interface for updating and reporting the status of operations, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern business environments, many information exchange means are used, and each provides information in a different format, making business management complex. As a result, important tasks are overlooked, record inconsistencies occur, duplicate management work is generated, leading to a decrease in productivity. Furthermore, when grasping the progress of business, each information source must be referred to individually, and there is a problem that efficient information transmission is difficult.

Means for Solving the Problems

[0005] This invention includes a module that automatically acquires data from information exchange means and extracts important information by analyzing the acquired data. Furthermore, by providing a function to register and manage tasks based on the extracted information, it prevents oversights and errors in tasks and enables efficient information integration. In addition, by generating notifications related to tasks, it provides users with timely alerts to prevent delays in tasks and provides an intuitive interface for updating and reporting task status, thereby achieving effective problem solving.

[0006] "Information exchange means" refers to tools such as email and short message services that users use for communication, and includes functions for obtaining business-related information from these tools.

[0007] "Means of acquiring data" refers to a device or program that has the function of automatically collecting data from information exchange means and is continuously accessible using an appropriate interface or API.

[0008] "Means of analysis" refers to a device or program that extracts important business-related information from acquired data through natural language processing technology or rule-based filtering, and converts it into the required format.

[0009] "Means for registering and managing tasks" refers to devices or programs that utilize databases or task management software to generate new tasks based on analyzed information, structurally organize existing tasks, and manage them efficiently.

[0010] "Means for generating and sending notifications" refers to a device or program for generating alerts and reminders to a user in a timely manner in relation to registered tasks and sending them in a configured manner (e.g., push notifications, email).

[0011] "An interface for updating and reporting the status of work" refers to a device or program that provides an operating screen or platform that allows users to check, update, and report the progress of their work. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This 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 a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying out the Invention

[0013] 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.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, a 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.

[0016] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, a 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, etc.

[0018] 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).

[0019] 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."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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".

[0033] The present invention is implemented as a system that acquires data from information exchange means, analyzes it to extract important information, and then registers, manages, notifies, and reports on business operations based on this information. Specific embodiments for carrying out the invention are described below.

[0034] The server first obtains data from information exchange channels. These channels include email, micromessaging services, and other communication platforms. By granting the user access to these tools, the server can automatically retrieve the relevant data.

[0035] The server then analyzes the acquired data. Using natural language processing and filtering techniques, it extracts important business-related information from the data, clarifying task names, deadlines, and related project information. Based on these analysis results, it generates business processes and registers them in the task management system.

[0036] Once a task is registered, the server prepares the associated reminder function. Reminders are automatically sent as the task's due date approaches, using the method selected by the user (e.g., push notification or email). The server also receives user feedback and progress updates through various interfaces to keep the work status up-to-date.

[0037] As a concrete example, consider an email received by a sales representative containing the instruction, "Propose a plan to the customer by next Monday." The server analyzes the email containing this instruction and registers the task "Customer Proposal" in the task management system with a Monday deadline. The day before the deadline, the server sends a push notification to the user's device prompting them to check the progress of the proposal preparation. The user receives the reminder, opens the task management screen, updates the progress, or requests assistance from team members as needed.

[0038] In this way, the present invention supports users' work management by improving work efficiency and preventing communication breakdowns.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The server connects to the APIs of each information exchange method permitted by the user and periodically retrieves messages and email data. During this process, the data is temporarily stored in a database.

[0042] Step 2:

[0043] The server analyzes the acquired data. Using natural language processing techniques, it extracts important information such as task names, deadlines, and related project information from the text and organizes it as structured data.

[0044] Step 3:

[0045] The server generates new tasks based on the analysis results and registers them in the task management database. During registration, priority and due dates are set for the tasks, and they are categorized according to their related projects.

[0046] Step 4:

[0047] The server schedules reminders based on registered tasks. It takes into account deadlines and priorities to ensure that notifications are sent to users at the appropriate time.

[0048] Step 5:

[0049] When it's time for a reminder, the server sends a reminder to the user's device via push notification or email.

[0050] Step 6:

[0051] Users can review received reminders and open the task management screen as needed. On this screen, users can update task progress and perform actions such as completing tasks or changing deadlines.

[0052] Step 7:

[0053] The server updates the task status based on user feedback. This update information is shared in real time with other relevant systems and project members.

[0054] (Example 1)

[0055] 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."

[0056] In managing business tasks, a common problem is reduced work efficiency due to overlooking important information or failing to properly manage deadlines. Traditional systems require manual information extraction and task management, placing a heavy burden on users. Therefore, there is a need for a system that can automatically collect and analyze information and manage tasks efficiently.

[0057] 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.

[0058] In this invention, the server includes means for acquiring data from information exchange means, means for analyzing and extracting important business information using natural language processing technology, and means for registering and managing tasks in a task management system based on the extracted information. This enables automatic extraction of business information and efficient task management.

[0059] An "information exchange method" is a communication interface that allows data to be sent and received via platforms such as email or short message services.

[0060] "Means of acquiring data" refers to the processes and technologies for collecting necessary information from information exchange channels, including technologies such as APIs and database connections.

[0061] "Natural language processing technology" refers to techniques for analyzing text data and extracting useful information, and includes morphological analysis, grammatical analysis, and semantic analysis.

[0062] A "task management system" is information management software used to manage individual tasks and projects, allowing for task creation, assignment, tracking, and reporting.

[0063] "Means for generating notifications and setting up alert functions on devices" refers to technologies for automatically issuing alerts to users based on deadlines or task status, and includes push notifications and email notifications.

[0064] An "interactive window for updating and reporting progress" is an interface that allows users to record and report the progress of their work, enabling real-time information sharing.

[0065] A "generative AI model" is an artificial intelligence technology that learns from large amounts of data and makes judgments and predictions for specific tasks.

[0066] This invention is implemented as a system that acquires data from information exchange means, analyzes it to extract important information, and then registers, manages, notifies, and reports on business operations based on this information. The following describes in detail how the invention can be implemented.

[0067] The server first obtains data through an information exchange mechanism. This mechanism can include email services or short message services. Specifically, the server uses a communication protocol to fetch messages and emails via an API and stores them in a database.

[0068] The acquired data is then analyzed on the server using natural language processing (NLTK) techniques. These techniques include Python libraries such as NLTK and spaCy. The server tokenizes the text and extracts important business information (e.g., task name, due date) through contextual understanding.

[0069] The server uses this extracted information to register tasks in the task management system. By creating tasks using management software like Jira and automatically registering that information in the system, users can monitor the task status in real time.

[0070] Furthermore, the server has a function that automatically sends notifications to the device when the deadline for registered tasks approaches. These notifications are delivered to the user's device as push notifications using Firebase Cloud Messaging.

[0071] Upon receiving this notification, users can access the issue management system via their device to update their progress. Furthermore, if users provide feedback or add information using the interface, that information is sent to all clients via the server, ensuring everyone shares the latest information.

[0072] As a concrete example, consider a scenario where a sales representative receives an email instructing them to "submit the proposal by next Monday." The server analyzes this email and registers the task "Proposal Creation" in the task management system with a Monday deadline. The day before the deadline, the server sends a push notification to the user's terminal, prompting them to check the progress of their proposal.

[0073] An example of a prompt message would be: "Analyze the work instructions from the following email, extract the task name and due date, and register them in the task management system."

[0074] Thus, the present invention aims to improve business efficiency through collaboration between servers, terminals, and users.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] The server retrieves data from information exchange channels. It uses APIs to obtain raw data from email services and short message services authorized by the user. The input for this step is raw text data such as emails and messages, which is stored in a database to prepare for subsequent analysis processes.

[0078] Step 2:

[0079] The server analyzes the acquired data using natural language processing techniques. Using the stored text data as input, it applies Python's NLTK and spaCy libraries to tokenize the text and partially label it. Here, important business information such as task names and due dates is extracted. The output is task information in a structured format.

[0080] Step 3:

[0081] The server registers the extracted task information into the issue tracking system. The input for this step is the analyzed task information, and using an API such as Jira, the server adds the issue to the system along with the specified due date and assignee information. The output is the newly registered task in the issue tracking system.

[0082] Step 4:

[0083] The server sets reminders related to tasks. It receives task information registered as input and sets reminders via Firebase Cloud Messaging. Push notifications are sent to the device at a time or date specified by the user. The output is the notification information for which the reminder has been set.

[0084] Step 5:

[0085] Users receive notifications and access the task management system via their devices. Input consists of notification information received from the server, which triggers them to check or update task progress. Users update the progress and add comments and new information as needed. Output is the latest progress information shared within the system.

[0086] This series of steps allows the system to manage business tasks automatically and efficiently, reducing the burden on users.

[0087] (Application Example 1)

[0088] 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."

[0089] In today's information society, the widespread adoption of electronic payments generates a vast amount of transaction data, but efficiently identifying and managing important transactions within this data is not easy. Therefore, there is a need to enable safe and efficient transaction management by quickly identifying unusual or high-value transactions based on specific conditions and providing appropriate notifications.

[0090] 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.

[0091] In this invention, the server includes means for acquiring data from information exchange means, means for analyzing the acquired data and extracting important information, and means for monitoring transaction data and identifying high-value or abnormal transactions based on specific conditions. This makes it possible to respond quickly to identified transactions and provide appropriate notifications to users.

[0092] "Information exchange means" refers to communication methods used to collect data, including email and short message services.

[0093] "Means of acquiring data" refers to the function of receiving necessary data from information exchange means.

[0094] "Means for analyzing data and extracting important information" refers to a function that analyzes received data, identifies the necessary information, and extracts it.

[0095] "Means for registering and managing tasks" refers to a function that records tasks based on extracted information and monitors their progress.

[0096] "Means for generating and sending notifications" refers to functions for sending alerts and reminders to users based on work-related information.

[0097] "Means of providing an interface" refers to user interfaces and communication methods that users can use to change or report the status of their work.

[0098] "Means of monitoring transaction data and identifying high-value or unusual transactions based on specific conditions" refers to a function that monitors transaction information in real time and automatically detects transactions that meet set criteria.

[0099] "Communication methods" refer to technologies and protocols for transmitting data to remote locations, but here they are specifically used for sending notifications.

[0100] The system implementing this invention consists of a server, a user terminal, and network communication means. In this system, the server acquires data from the information exchange means, analyzes it, and extracts important information. The acquired data is analyzed using natural language processing technology to extract necessary information related to the business.

[0101] The analyzed information is registered within the system through task registration and management mechanisms. This clarifies the tasks to be handled, allowing users to proceed with their work efficiently. Notifications are generated from the server and sent to the user via a method selected by the user (e.g., email or push notification).

[0102] Furthermore, user terminals are provided with an interface from which users can check and modify the status of their work. By providing feedback to the system, the progress of work is updated and reported as needed.

[0103] Specifically, the transaction data monitoring mechanism involves a server monitoring transaction data in real time and identifying high-value or unusual transactions based on specific conditions. The communication mechanism allows the server to quickly send notifications to users when these transactions occur.

[0104] As a concrete example, when an electronic payment for a high-value item is made at a physical store, this information is sent to a server and analyzed. As a result, the server determines it to be an abnormal transaction and immediately sends a notification to the user. This allows users to quickly detect signs of fraudulent transactions and take appropriate action.

[0105] An example of a prompt might be, "Write a Python program that identifies high-value transactions and sends a notification to the user." This prompt can be used to further improve or train the system using a generative AI model.

[0106] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0107] Step 1:

[0108] The server acquires data from emails and short messages via information exchange methods. Inputs include emails and communication data. Outputs the dataset to be analyzed. This allows the server to collect information that will serve as the basis for data analysis in the next step.

[0109] Step 2:

[0110] The server analyzes the acquired data using natural language processing techniques and extracts important information. The input is the dataset obtained in step 1. The output is information related to the identified business (e.g., transaction amount, customer information, etc.). This process makes it possible to structure meaningful text information contained within the data.

[0111] Step 3:

[0112] The server registers the tasks in the task management system based on the extracted information. The input is the information about the tasks generated in step 2. As output, specific task items are added to the task management system. In terms of specific operation, the server makes the registered tasks available for users to review later.

[0113] Step 4:

[0114] The server continuously monitors transaction data in real time to automatically detect high-value or unusual transactions. The input is continuously updated transaction data. The output is transaction information that meets specific criteria. The server identifies transactions that match these criteria and processes them promptly.

[0115] Step 5:

[0116] The server sends notifications to the user regarding identified transactions. The input is the transaction information identified in step 4. The output is the notification sent to the user's device or email. Specifically, the server sends alerts in a user-specified manner to support immediate action.

[0117] Step 6:

[0118] Users check notifications sent via their terminals and, if necessary, open the task management interface to check or update the progress of their tasks. Input is notification information sent from the server. Output is the updated task progress. This allows users to easily manage their tasks.

[0119] 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.

[0120] This invention is a system that acquires data from information exchange means, analyzes it to extract important information, and registers and manages tasks based on that information. Furthermore, by incorporating an emotion engine that analyzes user emotions, it achieves more efficient and personalized task management.

[0121] The server periodically retrieves messages from email and micromessaging services via APIs of information exchange methods permitted by the user. This data is temporarily stored in a database. Next, the server analyzes this data and uses natural language processing techniques to extract task names, deadlines, project information, etc., and registers it as structured business data.

[0122] Furthermore, the emotion engine analyzes user communication data and infers the user's emotional state from natural language expressions and other parameters. This emotional state is taken into consideration when setting task priorities and adjusting notification content. In addition, the user experience is improved by providing a customized interface that responds to the user's emotions.

[0123] As a concrete example, the server analyzes an email received by a sales representative stating, "Please prepare the presentation materials by next Tuesday," and registers it as a task. Simultaneously, if the emotion engine detects signs of stress or tension from the sales representative's text style, the server adjusts the timing and method of the reminder, taking into account the task's priority. For example, it might use a gentler notification language to reduce user stress.

[0124] Thus, by utilizing an emotion engine, the present invention enables flexible responses to the user's situation, making more intuitive and effective business management possible.

[0125] The following describes the processing flow.

[0126] Step 1:

[0127] The server connects to the APIs of the information exchange methods (email and short message services) used by the user and periodically retrieves message data. This data is temporarily stored in a database.

[0128] Step 2:

[0129] The server analyzes the stored message data using natural language processing technology. This analysis extracts important information such as task names, deadlines, and related projects, and registers it in the task management database.

[0130] Step 3:

[0131] The server uses an emotion engine to analyze the user's emotional state from the acquired communication data. This analysis is based on the context of the text, the expressions used, and the choice of words.

[0132] Step 4:

[0133] The server considers the user's emotional state, as determined by the emotion engine, to set the priority of registered tasks and the timing of reminders. If the user is experiencing stress, it adjusts task priorities and adds supportive messages as needed.

[0134] Step 5:

[0135] The server sends a notification to the user's device based on the set reminder time. The tone and content of this notification change according to the user's emotional state, providing a more personalized message.

[0136] Step 6:

[0137] Users can check notifications on their devices and open the relevant task management screen to update the task's progress. User feedback is reflected on the server in real time and shared with relevant parties.

[0138] Step 7:

[0139] The server integrates this information and provides analytical results that help improve the user's work performance. This supports the user in working more efficiently.

[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] Traditional business management systems have limited information gathering and analysis capabilities, making it difficult to manage tasks while considering the individual circumstances and emotional states of users. As a result, task prioritization and notification methods are uniform, hindering improvements in the user experience. Therefore, there is a need to analyze users' emotional states and manage tasks flexibly and individually based on this analysis.

[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 a mechanism for acquiring information from an information exchange device, a mechanism for analyzing the acquired information and extracting important information, and a mechanism for analyzing the user's emotional state. This makes it possible to register and manage tasks based on the extracted information, while adjusting priorities and notification content according to the user's emotional state.

[0145] An "information exchange device" refers to a means of communication that can acquire or transmit data via electronic messages or short message services.

[0146] A "system" refers to a series of processes or devices designed to achieve a specific function.

[0147] "Acquisition" refers to the process of receiving information from an external source and making that information available for use internally.

[0148] "Analysis" refers to the process of performing necessary processing to evaluate and understand acquired information, and extracting meaningful data.

[0149] "Important information" refers to information essential for registering and managing tasks, and specifically includes task names, deadlines, and priorities.

[0150] "Extraction" refers to the process of selecting specific elements from analyzed information.

[0151] "Registration" refers to the process of saving extracted information to the system and making it accessible later.

[0152] "Notification" refers to an electronic message used to convey work-related information to the user.

[0153] "Emotional state" refers to the psychological state inferred from the content and parameters of a user's communication.

[0154] An "interface" refers to a means or screen display that enables the exchange of information between a user and a system.

[0155] In this invention, a server plays a central role in securely acquiring electronic messages and short-message data from an information exchange device. The acquired data is first temporarily stored in a database. Subsequently, the server analyzes this data using natural language processing technology to extract important information necessary for the business, specifically task names, deadlines, and project information. As natural language processing technology, software such as SpaCy or NLTK can be used.

[0156] The analyzed information is converted into structured data for business registration and management and registered within the system. Furthermore, for sentiment analysis, the server utilizes a sentiment analysis engine. This engine analyzes natural language expressions and other parameters based on the user's communication data to infer the user's emotional state. As a sentiment analysis engine, technologies such as IBM Watson® Tone Analyzer could be used.

[0157] Based on these analysis results, users can manage their work through a appropriately customized interface. The interface is designed to adjust according to the user's emotional state, thereby improving the user experience.

[0158] As a concrete example, when the server receives an email from a sales representative saying, "Please prepare the presentation materials by next Tuesday," it registers this information as a task. At the same time, the emotion engine can recognize stress and tension from the sales representative's text style and adjust the reminder accordingly. Such a system enables task management that is more appropriate to the situation the user is facing.

[0159] An example of a prompt to input into a generative AI model is: "Explain how to analyze the user's incoming messages and perform appropriate task management while considering their emotional state."

[0160] This invention provides a new method for information acquisition and analysis, and enables flexible and intuitive business management based on user emotions.

[0161] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0162] Step 1:

[0163] The server retrieves electronic messages and short message service data from information exchange devices. Input is message data transmitted via the user-authorized electronic message or short message data API. Output is stored in a database in a temporary storage format. Specifically, it securely retrieves data using OAuth authentication, organizes it in the database according to the message format, and stores it there.

[0164] Step 2:

[0165] The server analyzes stored message data using natural language processing techniques. The input is temporarily stored message data. The output provides business-related information such as task names, deadlines, and project information. Specifically, it uses natural language processing software (e.g., SpaCy, NLTK) to analyze the text and extract necessary keywords and phrases.

[0166] Step 3:

[0167] The server structures business data based on the analyzed information and registers it in the task management system. The input is information analyzed using natural language processing technology. As output, the structured business data is stored in the task management system and becomes accessible to users. Specifically, it creates a new entry in the database using the extracted information and registers the task.

[0168] Step 4:

[0169] The server utilizes an emotion analysis engine to analyze the user's emotional state. The input is the user's communication data. The output is an inference of the user's emotional state. Specifically, it analyzes natural language expressions and keywords to identify the user's emotional state (e.g., stress, tension).

[0170] Step 5:

[0171] The server prioritizes tasks and adjusts notifications based on emotional states. Inputs include analyzed emotional states and structured work data. Outputs include emotionally-considered priorities and adjusted notifications. Specifically, it adjusts actual task deadlines and priorities and customizes how users are reminded.

[0172] Step 6:

[0173] The server provides the user with an interface tailored to their emotional state. The input is the user's emotional state. The output is a customized user interface. Specifically, it adjusts the system's visuals and message tone to optimize the user experience.

[0174] (Application Example 2)

[0175] 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 device 14 will be referred to as the "terminal."

[0176] In modern households and for individuals, efficiently managing multiple activities and schedules is difficult. Furthermore, flexible activity adjustments that take into account the user's emotions are crucial for reducing their psychological burden. However, existing systems and methods fail to adequately meet these requirements, making optimal management tailored to individual circumstances challenging.

[0177] 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.

[0178] In this invention, the server includes means for acquiring information, means for analyzing the acquired information and extracting important data, and means for providing interaction means to support activities in the physical environment. This enables efficient management of household and personal activities and flexible adjustments according to the user's emotional state.

[0179] "Information acquisition means" refers to a function for acquiring data from information exchange means.

[0180] "Means for analyzing acquired information and extracting important data" refers to a function that processes acquired information and performs operations to select particularly important parts.

[0181] "Means for registering and managing activities" refers to functions for organizing and tracking activities based on extracted data.

[0182] "Means for generating and sending notifications" refers to functions that inform users of information related to their activities.

[0183] "Emotional analysis technology" is a technology that analyzes a user's input and communication to infer their emotional state.

[0184] "Interaction means" are means of facilitating interaction with users in a physical environment.

[0185] The invention will now be described in terms of its implementation. This system is designed to efficiently manage household and personal activities and to enable flexible responses that respond to the user's emotions. The server retrieves information through email and short message service APIs, temporarily stores this data in a database, and analyzes it using natural language processing technology.

[0186] The server uses open-source natural language processing libraries to extract task names, deadlines, and activity-related information, and registers this as structured data. For example, it uses NLTK to analyze key information from messages. For sentiment analysis, it is possible to infer the emotional state from the user's messages using an analysis tool called EmotionAnalyzer. Based on the user's emotions, activity priorities can be adjusted, and the content and timing of notifications can be optimized.

[0187] The device functions as a smartphone or home robot, enabling interaction with the user. This allows for support of activities in the physical environment and the provision of a customized interface tailored to the user's current state. For example, if the system detects that the user is experiencing stress, it can provide notifications in a gentler tone. Such a system would allow users to reduce their psychological burden while effectively pursuing their plans.

[0188] An example of a prompt message is: "Adjust the task management system for the home robot assistant using sentiment analysis. If the user is stressed, label it and adjust the notifications accordingly."

[0189] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0190] Step 1:

[0191] The server periodically retrieves emails and short message communications via an API (Application Programming Interface). The input is the raw message data retrieved from the API, while the output is the message data temporarily stored in a database.

[0192] Step 2:

[0193] The server analyzes message data stored in the database using natural language processing techniques. The input is the stored message data, and the output is extracted important information such as task names, deadlines, and project information. This process utilizes natural language processing libraries such as NLTK to perform text analysis.

[0194] Step 3:

[0195] The server uses EmotionAnalyzer to infer the emotional state of the analyzed message. The input is the text information extracted in step 2, and the output is an emotional score or emotional label. Based on the analysis results, the server understands the user's current mental state.

[0196] Step 4:

[0197] The server determines task priorities and reminder content based on the extracted task information and emotional state, and generates notifications at the optimal time. The input is the task information and emotional score obtained in the previous step, and the output is the generated notification message. The server uses this information to prepare tailored notifications for the user.

[0198] Step 5:

[0199] The device sends generated notifications to the user in an appropriate format. The input is the notification message prepared by the server, and the output is provided to the user as a notification via display or audio. The device can adjust the notification method according to the user's emotions and context.

[0200] 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.

[0201] 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.

[0202] 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.

[0203] [Second Embodiment]

[0204] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0205] 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.

[0206] 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).

[0207] 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.

[0208] 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.

[0209] 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).

[0210] 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.

[0211] 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.

[0212] 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.

[0213] 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.

[0214] 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.

[0215] 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".

[0216] The present invention is implemented as a system that acquires data from information exchange means, analyzes it to extract important information, and then registers, manages, notifies, and reports on business operations based on this information. Specific embodiments for carrying out the invention are described below.

[0217] The server first obtains data from information exchange channels. These channels include email, micromessaging services, and other communication platforms. By granting the user access to these tools, the server can automatically retrieve the relevant data.

[0218] The server then analyzes the acquired data. Using natural language processing and filtering techniques, it extracts important business-related information from the data, clarifying task names, deadlines, and related project information. Based on these analysis results, it generates business processes and registers them in the task management system.

[0219] Once a task is registered, the server prepares the associated reminder function. Reminders are automatically sent as the task's due date approaches, using the method selected by the user (e.g., push notification or email). The server also receives user feedback and progress updates through various interfaces to keep the work status up-to-date.

[0220] As a concrete example, consider an email received by a sales representative containing the instruction, "Propose a plan to the customer by next Monday." The server analyzes the email containing this instruction and registers the task "Customer Proposal" in the task management system with a Monday deadline. The day before the deadline, the server sends a push notification to the user's device prompting them to check the progress of the proposal preparation. The user receives the reminder, opens the task management screen, updates the progress, or requests assistance from team members as needed.

[0221] In this way, the present invention supports users' work management by improving work efficiency and preventing communication breakdowns.

[0222] The following describes the processing flow.

[0223] Step 1:

[0224] The server connects to the APIs of each information exchange method permitted by the user and periodically retrieves messages and email data. During this process, the data is temporarily stored in a database.

[0225] Step 2:

[0226] The server analyzes the acquired data. Using natural language processing techniques, it extracts important information such as task names, deadlines, and related project information from the text and organizes it as structured data.

[0227] Step 3:

[0228] The server generates new tasks based on the analysis results and registers them in the task management database. During registration, priority and due dates are set for the tasks, and they are categorized according to their related projects.

[0229] Step 4:

[0230] The server schedules reminders based on registered tasks. It takes into account deadlines and priorities to ensure that notifications are sent to users at the appropriate time.

[0231] Step 5:

[0232] When it's time for a reminder, the server sends a reminder to the user's device via push notification or email.

[0233] Step 6:

[0234] Users can review received reminders and open the task management screen as needed. On this screen, users can update task progress and perform actions such as completing tasks or changing deadlines.

[0235] Step 7:

[0236] The server updates the task status based on user feedback. This update information is shared in real time with other relevant systems and project members.

[0237] (Example 1)

[0238] 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."

[0239] In managing business tasks, a common problem is reduced work efficiency due to overlooking important information or failing to properly manage deadlines. Traditional systems require manual information extraction and task management, placing a heavy burden on users. Therefore, there is a need for a system that can automatically collect and analyze information and manage tasks efficiently.

[0240] 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.

[0241] In this invention, the server includes means for acquiring data from information exchange means, means for analyzing and extracting important business information using natural language processing technology, and means for registering and managing tasks in a task management system based on the extracted information. This enables automatic extraction of business information and efficient task management.

[0242] An "information exchange method" is a communication interface that allows data to be sent and received via platforms such as email or short message services.

[0243] "Means of acquiring data" refers to the processes and technologies for collecting necessary information from information exchange channels, including technologies such as APIs and database connections.

[0244] "Natural language processing technology" refers to techniques for analyzing text data and extracting useful information, and includes morphological analysis, grammatical analysis, and semantic analysis.

[0245] A "task management system" is information management software used to manage individual tasks and projects, allowing for task creation, assignment, tracking, and reporting.

[0246] "Means for generating notifications and setting up alert functions on devices" refers to technologies for automatically issuing alerts to users based on deadlines or task status, and includes push notifications and email notifications.

[0247] An "interactive window for updating and reporting progress" is an interface that allows users to record and report the progress of their work, enabling real-time information sharing.

[0248] A "generative AI model" is an artificial intelligence technology that learns from large amounts of data and makes judgments and predictions for specific tasks.

[0249] This invention is implemented as a system that acquires data from information exchange means, analyzes it to extract important information, and then registers, manages, notifies, and reports on business operations based on this information. The following describes in detail how the invention can be implemented.

[0250] The server first obtains data through an information exchange mechanism. This mechanism can include email services or short message services. Specifically, the server uses a communication protocol to fetch messages and emails via an API and stores them in a database.

[0251] The acquired data is then analyzed on the server using natural language processing (NLTK) techniques. These techniques include Python libraries such as NLTK and spaCy. The server tokenizes the text and extracts important business information (e.g., task name, due date) through contextual understanding.

[0252] The server uses this extracted information to register tasks in the task management system. By creating tasks using management software like Jira and automatically registering that information in the system, users can monitor the task status in real time.

[0253] Furthermore, the server has a function that automatically sends notifications to the device when the deadline for registered tasks approaches. These notifications are delivered to the user's device as push notifications using Firebase Cloud Messaging.

[0254] Upon receiving this notification, users can access the issue management system via their device to update their progress. Furthermore, if users provide feedback or add information using the interface, that information is sent to all clients via the server, ensuring everyone shares the latest information.

[0255] As a concrete example, consider a scenario where a sales representative receives an email instructing them to "submit the proposal by next Monday." The server analyzes this email and registers the task "Proposal Creation" in the task management system with a Monday deadline. The day before the deadline, the server sends a push notification to the user's terminal, prompting them to check the progress of their proposal.

[0256] An example of a prompt message would be: "Analyze the work instructions from the following email, extract the task name and due date, and register them in the task management system."

[0257] Thus, the present invention aims to improve business efficiency through collaboration between servers, terminals, and users.

[0258] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0259] Step 1:

[0260] The server retrieves data from information exchange channels. It uses APIs to obtain raw data from email services and short message services authorized by the user. The input for this step is raw text data such as emails and messages, which is stored in a database to prepare for subsequent analysis processes.

[0261] Step 2:

[0262] The server analyzes the acquired data using natural language processing techniques. Using the stored text data as input, it applies Python's NLTK and spaCy libraries to tokenize the text and partially label it. Here, important business information such as task names and due dates is extracted. The output is task information in a structured format.

[0263] Step 3:

[0264] The server registers the extracted task information into the issue tracking system. The input for this step is the analyzed task information, and using an API such as Jira, the server adds the issue to the system along with the specified due date and assignee information. The output is the newly registered task in the issue tracking system.

[0265] Step 4:

[0266] The server sets reminders related to tasks. It receives task information registered as input and sets reminders via Firebase Cloud Messaging. Push notifications are sent to the device at a time or date specified by the user. The output is the notification information for which the reminder has been set.

[0267] Step 5:

[0268] Users receive notifications and access the task management system via their devices. Input consists of notification information received from the server, which triggers them to check or update task progress. Users update the progress and add comments and new information as needed. Output is the latest progress information shared within the system.

[0269] This series of steps allows the system to manage business tasks automatically and efficiently, reducing the burden on users.

[0270] (Application Example 1)

[0271] 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."

[0272] In today's information society, the widespread adoption of electronic payments generates a vast amount of transaction data, but efficiently identifying and managing important transactions within this data is not easy. Therefore, there is a need to enable safe and efficient transaction management by quickly identifying unusual or high-value transactions based on specific conditions and providing appropriate notifications.

[0273] 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.

[0274] In this invention, the server includes means for acquiring data from information exchange means, means for analyzing the acquired data and extracting important information, and means for monitoring transaction data and identifying high-value or abnormal transactions based on specific conditions. This makes it possible to respond quickly to identified transactions and provide appropriate notifications to users.

[0275] "Information exchange means" refers to communication methods used to collect data, including email and short message services.

[0276] "Means of acquiring data" refers to the function of receiving necessary data from information exchange means.

[0277] "Means for analyzing data and extracting important information" refers to a function that analyzes received data, identifies the necessary information, and extracts it.

[0278] "Means for registering and managing tasks" refers to a function that records tasks based on extracted information and monitors their progress.

[0279] "Means for generating and sending notifications" refers to functions for sending alerts and reminders to users based on work-related information.

[0280] The "means for providing an interface" refers to an operation screen or communication means that can be used when a user changes or reports the status of a business.

[0281] The "means for monitoring transaction data and identifying high-value or abnormal transactions based on specific conditions" refers to a function that monitors transaction information in real time and automatically detects transactions that meet the set criteria.

[0282] The "communication means" refers to the technology or protocol for transmitting data to a remote location, and here it is particularly used for sending notifications.

[0283] The system for implementing this invention is composed of a combination of a server, a user terminal, and network communication means. In this system, the server acquires data from the information exchange means, analyzes it, and extracts important information. The captured data is analyzed using natural language processing technology to extract the necessary information related to the business.

[0284] The analyzed information is registered in the system by the business registration and management means. This clarifies the business to be handled, and the user can efficiently proceed with the business. Notifications are generated by the server and sent to the user by the selected method (e.g., email or push notification).

[0285] Furthermore, an interface is provided on the user terminal, and the user can check and change the status of the business from here. By providing feedback to the system by the user, the progress of the business is updated and reported as necessary.

[0286] In particular, the means for monitoring transaction data is such that the server monitors transaction data in real time and identifies high-value or abnormal transactions based on specific conditions. The communication means is such that when these transactions occur, the server promptly sends a notification to the user.

[0287] As a concrete example, when an electronic payment for a high-value item is made at a physical store, this information is sent to a server and analyzed. As a result, the server determines it to be an abnormal transaction and immediately sends a notification to the user. This allows users to quickly detect signs of fraudulent transactions and take appropriate action.

[0288] An example of a prompt might be, "Write a Python program that identifies high-value transactions and sends a notification to the user." This prompt can be used to further improve or train the system using a generative AI model.

[0289] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0290] Step 1:

[0291] The server acquires data from emails and short messages via information exchange methods. Inputs include emails and communication data. Outputs the dataset to be analyzed. This allows the server to collect information that will serve as the basis for data analysis in the next step.

[0292] Step 2:

[0293] The server analyzes the acquired data using natural language processing techniques and extracts important information. The input is the dataset obtained in step 1. The output is information related to the identified business (e.g., transaction amount, customer information, etc.). This process makes it possible to structure meaningful text information contained within the data.

[0294] Step 3:

[0295] The server registers the tasks in the task management system based on the extracted information. The input is the information about the tasks generated in step 2. As output, specific task items are added to the task management system. In terms of specific operation, the server makes the registered tasks available for users to review later.

[0296] Step 4:

[0297] The server continuously monitors transaction data in real time to automatically detect high-value or unusual transactions. The input is continuously updated transaction data. The output is transaction information that meets specific criteria. The server identifies transactions that match these criteria and processes them promptly.

[0298] Step 5:

[0299] The server sends notifications to the user regarding identified transactions. The input is the transaction information identified in step 4. The output is the notification sent to the user's device or email. Specifically, the server sends alerts in a user-specified manner to support immediate action.

[0300] Step 6:

[0301] Users check notifications sent via their terminals and, if necessary, open the task management interface to check or update the progress of their tasks. Input is notification information sent from the server. Output is the updated task progress. This allows users to easily manage their tasks.

[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 is a system that acquires data from information exchange means, analyzes it to extract important information, and registers and manages business operations based on that information. Furthermore, by incorporating an emotion engine that analyzes the emotions of users, more efficient and personalized business management is achieved.

[0304] The server periodically obtains messages from email and short message communication services via the API of the information exchange means permitted by the user. This data is temporarily stored in a database. Next, this data is analyzed by the server, and using natural language processing technology, task names, deadlines, project information, etc. are extracted and registered as structured data of the business operations.

[0305] Also, the emotion engine analyzes the communication data of the user and infers the emotional state of the user from the expressions of natural language and other parameters. This emotional state is considered when setting the priority of business operations or adjusting the content of notifications. Furthermore, by providing a customized interface according to the emotions of the user, the user experience is improved.

[0306] As a specific example, the server analyzes an email such as "Please prepare presentation materials by next Tuesday" received by a salesperson and registers it as a task. At the same time, if the emotion engine recognizes signs of stress or tension from the text style of the salesperson, the server adjusts the reminder timing and method while considering the priority of the task. For example, by using a notification with a milder expression, efforts are made to reduce the stress of the user.

[0307] In this way, the present invention utilizes the emotion engine to flexibly respond to the situation of the user and enables more intuitive and effective business management.

[0308] The following describes the processing flow.

[0309] Step 1:

[0310] The server connects to the APIs of the information exchange methods (email and short message services) used by the user and periodically retrieves message data. This data is temporarily stored in a database.

[0311] Step 2:

[0312] The server analyzes the stored message data using natural language processing technology. This analysis extracts important information such as task names, deadlines, and related projects, and registers it in the task management database.

[0313] Step 3:

[0314] The server uses an emotion engine to analyze the user's emotional state from the acquired communication data. This analysis is based on the context of the text, the expressions used, and the choice of words.

[0315] Step 4:

[0316] The server considers the user's emotional state, as determined by the emotion engine, to set the priority of registered tasks and the timing of reminders. If the user is experiencing stress, it adjusts task priorities and adds supportive messages as needed.

[0317] Step 5:

[0318] The server sends a notification to the user's device based on the set reminder time. The tone and content of this notification change according to the user's emotional state, providing a more personalized message.

[0319] Step 6:

[0320] Users can check notifications on their devices and open the relevant task management screen to update the task's progress. User feedback is reflected on the server in real time and shared with relevant parties.

[0321] Step 7:

[0322] The server integrates this information and provides analytical results that help improve the user's work performance. This supports the user in working more efficiently.

[0323] (Example 2)

[0324] 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".

[0325] Traditional business management systems have limited information gathering and analysis capabilities, making it difficult to manage tasks while considering the individual circumstances and emotional states of users. As a result, task prioritization and notification methods are uniform, hindering improvements in the user experience. Therefore, there is a need to analyze users' emotional states and manage tasks flexibly and individually based on this analysis.

[0326] 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.

[0327] In this invention, the server includes a mechanism for acquiring information from an information exchange device, a mechanism for analyzing the acquired information and extracting important information, and a mechanism for analyzing the user's emotional state. This makes it possible to register and manage tasks based on the extracted information, while adjusting priorities and notification content according to the user's emotional state.

[0328] An "information exchange device" refers to a means of communication that can acquire or transmit data via electronic messages or short message services.

[0329] A "system" refers to a series of processes or devices designed to achieve a specific function.

[0330] "Acquisition" refers to the process of receiving information from an external source and making that information available for use internally.

[0331] "Analysis" refers to the process of performing necessary processing to evaluate and understand acquired information, and extracting meaningful data.

[0332] "Important information" refers to information essential for registering and managing tasks, and specifically includes task names, deadlines, and priorities.

[0333] "Extraction" refers to the process of selecting specific elements from analyzed information.

[0334] "Registration" refers to the process of saving extracted information to the system and making it accessible later.

[0335] "Notification" refers to an electronic message used to convey work-related information to the user.

[0336] "Emotional state" refers to the psychological state inferred from the content and parameters of a user's communication.

[0337] An "interface" refers to a means or screen display that enables the exchange of information between a user and a system.

[0338] In this invention, a server plays a central role in securely acquiring electronic messages and short-message data from an information exchange device. The acquired data is first temporarily stored in a database. Subsequently, the server analyzes this data using natural language processing technology to extract important information necessary for the business, specifically task names, deadlines, and project information. As natural language processing technology, software such as SpaCy or NLTK can be used.

[0339] The analyzed information is converted into structured data for business registration and management and registered within the system. Furthermore, for sentiment analysis, the server utilizes a sentiment analysis engine. This engine analyzes natural language expressions and other parameters based on the user's communication data to infer the user's emotional state. For example, technologies such as IBM Watson Tone Analyzer could be used as the sentiment analysis engine.

[0340] Based on these analysis results, users can manage their work through a appropriately customized interface. The interface is designed to adjust according to the user's emotional state, thereby improving the user experience.

[0341] As a concrete example, when the server receives an email from a sales representative saying, "Please prepare the presentation materials by next Tuesday," it registers this information as a task. At the same time, the emotion engine can recognize stress and tension from the sales representative's text style and adjust the reminder accordingly. Such a system enables task management that is more appropriate to the situation the user is facing.

[0342] An example of a prompt to input into a generative AI model is: "Explain how to analyze the user's incoming messages and perform appropriate task management while considering their emotional state."

[0343] This invention provides a new method for information acquisition and analysis, and enables flexible and intuitive business management based on user emotions.

[0344] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0345] Step 1:

[0346] The server retrieves electronic messages and short message service data from information exchange devices. Input is message data transmitted via the user-authorized electronic message or short message data API. Output is stored in a database in a temporary storage format. Specifically, it securely retrieves data using OAuth authentication, organizes it in the database according to the message format, and stores it there.

[0347] Step 2:

[0348] The server analyzes stored message data using natural language processing techniques. The input is temporarily stored message data. The output provides business-related information such as task names, deadlines, and project information. Specifically, it uses natural language processing software (e.g., SpaCy, NLTK) to analyze the text and extract necessary keywords and phrases.

[0349] Step 3:

[0350] The server structures business data based on the analyzed information and registers it in the task management system. The input is information analyzed using natural language processing technology. As output, the structured business data is stored in the task management system and becomes accessible to users. Specifically, it creates a new entry in the database using the extracted information and registers the task.

[0351] Step 4:

[0352] The server utilizes an emotion analysis engine to analyze the user's emotional state. The input is the user's communication data. The output is an inference of the user's emotional state. Specifically, it analyzes natural language expressions and keywords to identify the user's emotional state (e.g., stress, tension).

[0353] Step 5:

[0354] The server prioritizes tasks and adjusts notifications based on emotional states. Inputs include analyzed emotional states and structured work data. Outputs include emotionally-considered priorities and adjusted notifications. Specifically, it adjusts actual task deadlines and priorities and customizes how users are reminded.

[0355] Step 6:

[0356] The server provides the user with an interface tailored to their emotional state. The input is the user's emotional state. The output is a customized user interface. Specifically, it adjusts the system's visuals and message tone to optimize the user experience.

[0357] (Application Example 2)

[0358] 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."

[0359] In modern households and for individuals, efficiently managing multiple activities and schedules is difficult. Furthermore, flexible activity adjustments that take into account the user's emotions are crucial for reducing their psychological burden. However, existing systems and methods fail to adequately meet these requirements, making optimal management tailored to individual circumstances challenging.

[0360] 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.

[0361] In this invention, the server includes means for acquiring information, means for analyzing the acquired information and extracting important data, and means for providing interaction means to support activities in the physical environment. This enables efficient management of household and personal activities and flexible adjustments according to the user's emotional state.

[0362] "Information acquisition means" refers to a function for acquiring data from information exchange means.

[0363] "Means for analyzing acquired information and extracting important data" refers to a function that processes acquired information and performs operations to select particularly important parts.

[0364] "Means for registering and managing activities" refers to functions for organizing and tracking activities based on extracted data.

[0365] "Means for generating and sending notifications" refers to functions that inform users of information related to their activities.

[0366] "Emotional analysis technology" is a technology that analyzes a user's input and communication to infer their emotional state.

[0367] "Interaction means" are means of facilitating interaction with users in a physical environment.

[0368] The invention will now be described in terms of its implementation. This system is designed to efficiently manage household and personal activities and to enable flexible responses that respond to the user's emotions. The server retrieves information through email and short message service APIs, temporarily stores this data in a database, and analyzes it using natural language processing technology.

[0369] The server uses open-source natural language processing libraries to extract task names, deadlines, and activity-related information, and registers this as structured data. For example, it uses NLTK to analyze key information from messages. For sentiment analysis, it is possible to infer the emotional state from the user's messages using an analysis tool called EmotionAnalyzer. Based on the user's emotions, activity priorities can be adjusted, and the content and timing of notifications can be optimized.

[0370] The device functions as a smartphone or home robot, enabling interaction with the user. This allows for support of activities in the physical environment and the provision of a customized interface tailored to the user's current state. For example, if the system detects that the user is experiencing stress, it can provide notifications in a gentler tone. Such a system would allow users to reduce their psychological burden while effectively pursuing their plans.

[0371] An example of a prompt message is: "Adjust the task management system for the home robot assistant using sentiment analysis. If the user is stressed, label it and adjust the notifications accordingly."

[0372] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0373] Step 1:

[0374] The server periodically retrieves emails and short message communications via an API (Application Programming Interface). The input is the raw message data retrieved from the API, while the output is the message data temporarily stored in a database.

[0375] Step 2:

[0376] The server analyzes message data stored in the database using natural language processing techniques. The input is the stored message data, and the output is extracted important information such as task names, deadlines, and project information. This process utilizes natural language processing libraries such as NLTK to perform text analysis.

[0377] Step 3:

[0378] The server uses EmotionAnalyzer to infer the emotional state of the analyzed message. The input is the text information extracted in step 2, and the output is an emotional score or emotional label. Based on the analysis results, the server understands the user's current mental state.

[0379] Step 4:

[0380] The server determines task priorities and reminder content based on the extracted task information and emotional state, and generates notifications at the optimal time. The input is the task information and emotional score obtained in the previous step, and the output is the generated notification message. The server uses this information to prepare tailored notifications for the user.

[0381] Step 5:

[0382] The device sends generated notifications to the user in an appropriate format. The input is the notification message prepared by the server, and the output is provided to the user as a notification via display or audio. The device can adjust the notification method according to the user's emotions and context.

[0383] 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.

[0384] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0385] 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.

[0386] [Third Embodiment]

[0387] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0388] 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.

[0389] 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).

[0390] 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.

[0391] 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.

[0392] 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).

[0393] 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.

[0394] 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.

[0395] 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.

[0396] 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.

[0397] 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.

[0398] 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".

[0399] The present invention is implemented as a system that acquires data from information exchange means, analyzes it to extract important information, and then registers, manages, notifies, and reports on business operations based on this information. Specific embodiments for carrying out the invention are described below.

[0400] The server first obtains data from information exchange channels. These channels include email, micromessaging services, and other communication platforms. By granting the user access to these tools, the server can automatically retrieve the relevant data.

[0401] The server then analyzes the acquired data. Using natural language processing and filtering techniques, it extracts important business-related information from the data, clarifying task names, deadlines, and related project information. Based on these analysis results, it generates business processes and registers them in the task management system.

[0402] Once a task is registered, the server prepares the associated reminder function. Reminders are automatically sent as the task's due date approaches, using the method selected by the user (e.g., push notification or email). The server also receives user feedback and progress updates through various interfaces to keep the work status up-to-date.

[0403] As a concrete example, consider an email received by a sales representative containing the instruction, "Propose a plan to the customer by next Monday." The server analyzes the email containing this instruction and registers the task "Customer Proposal" in the task management system with a Monday deadline. The day before the deadline, the server sends a push notification to the user's device prompting them to check the progress of the proposal preparation. The user receives the reminder, opens the task management screen, updates the progress, or requests assistance from team members as needed.

[0404] In this way, the present invention supports users' work management by improving work efficiency and preventing communication breakdowns.

[0405] The following describes the processing flow.

[0406] Step 1:

[0407] The server connects to the APIs of each information exchange method permitted by the user and periodically retrieves messages and email data. During this process, the data is temporarily stored in a database.

[0408] Step 2:

[0409] The server analyzes the acquired data. Using natural language processing techniques, it extracts important information such as task names, deadlines, and related project information from the text and organizes it as structured data.

[0410] Step 3:

[0411] The server generates new tasks based on the analysis results and registers them in the task management database. During registration, priority and due dates are set for the tasks, and they are categorized according to their related projects.

[0412] Step 4:

[0413] The server schedules reminders based on registered tasks. It takes into account deadlines and priorities to ensure that notifications are sent to users at the appropriate time.

[0414] Step 5:

[0415] When it's time for a reminder, the server sends a reminder to the user's device via push notification or email.

[0416] Step 6:

[0417] Users can review received reminders and open the task management screen as needed. On this screen, users can update task progress and perform actions such as completing tasks or changing deadlines.

[0418] Step 7:

[0419] The server updates the task status based on user feedback. This update information is shared in real time with other relevant systems and project members.

[0420] (Example 1)

[0421] 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."

[0422] In managing business tasks, a common problem is reduced work efficiency due to overlooking important information or failing to properly manage deadlines. Traditional systems require manual information extraction and task management, placing a heavy burden on users. Therefore, there is a need for a system that can automatically collect and analyze information and manage tasks efficiently.

[0423] 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.

[0424] In this invention, the server includes means for acquiring data from information exchange means, means for analyzing and extracting important business information using natural language processing technology, and means for registering and managing tasks in a task management system based on the extracted information. This enables automatic extraction of business information and efficient task management.

[0425] An "information exchange method" is a communication interface that allows data to be sent and received via platforms such as email or short message services.

[0426] "Means of acquiring data" refers to the processes and technologies for collecting necessary information from information exchange channels, including technologies such as APIs and database connections.

[0427] "Natural language processing technology" refers to techniques for analyzing text data and extracting useful information, and includes morphological analysis, grammatical analysis, and semantic analysis.

[0428] A "task management system" is information management software used to manage individual tasks and projects, allowing for task creation, assignment, tracking, and reporting.

[0429] "Means for generating notifications and setting up alert functions on devices" refers to technologies for automatically issuing alerts to users based on deadlines or task status, and includes push notifications and email notifications.

[0430] An "interactive window for updating and reporting progress" is an interface that allows users to record and report the progress of their work, enabling real-time information sharing.

[0431] A "generative AI model" is an artificial intelligence technology that learns from large amounts of data and makes judgments and predictions for specific tasks.

[0432] This invention is implemented as a system that acquires data from information exchange means, analyzes it to extract important information, and then registers, manages, notifies, and reports on business operations based on this information. The following describes in detail how the invention can be implemented.

[0433] The server first obtains data through an information exchange mechanism. This mechanism can include email services or short message services. Specifically, the server uses a communication protocol to fetch messages and emails via an API and stores them in a database.

[0434] The acquired data is then analyzed on the server using natural language processing (NLTK) techniques. These techniques include Python libraries such as NLTK and spaCy. The server tokenizes the text and extracts important business information (e.g., task name, due date) through contextual understanding.

[0435] The server uses this extracted information to register tasks in the task management system. By creating tasks using management software like Jira and automatically registering that information in the system, users can monitor the task status in real time.

[0436] Furthermore, the server has a function that automatically sends notifications to the device when the deadline for registered tasks approaches. These notifications are delivered to the user's device as push notifications using Firebase Cloud Messaging.

[0437] Upon receiving this notification, users can access the issue management system via their device to update their progress. Furthermore, if users provide feedback or add information using the interface, that information is sent to all clients via the server, ensuring everyone shares the latest information.

[0438] As a concrete example, consider a scenario where a sales representative receives an email instructing them to "submit the proposal by next Monday." The server analyzes this email and registers the task "Proposal Creation" in the task management system with a Monday deadline. The day before the deadline, the server sends a push notification to the user's terminal, prompting them to check the progress of their proposal.

[0439] An example of a prompt message would be: "Analyze the work instructions from the following email, extract the task name and due date, and register them in the task management system."

[0440] Thus, the present invention aims to improve business efficiency through collaboration between servers, terminals, and users.

[0441] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0442] Step 1:

[0443] The server retrieves data from information exchange channels. It uses APIs to obtain raw data from email services and short message services authorized by the user. The input for this step is raw text data such as emails and messages, which is stored in a database to prepare for subsequent analysis processes.

[0444] Step 2:

[0445] The server analyzes the acquired data using natural language processing techniques. Using the stored text data as input, it applies Python's NLTK and spaCy libraries to tokenize the text and partially label it. Here, important business information such as task names and due dates is extracted. The output is task information in a structured format.

[0446] Step 3:

[0447] The server registers the extracted task information into the issue tracking system. The input for this step is the analyzed task information, and using an API such as Jira, the server adds the issue to the system along with the specified due date and assignee information. The output is the newly registered task in the issue tracking system.

[0448] Step 4:

[0449] The server sets reminders related to tasks. It receives task information registered as input and sets reminders via Firebase Cloud Messaging. Push notifications are sent to the device at a time or date specified by the user. The output is the notification information for which the reminder has been set.

[0450] Step 5:

[0451] Users receive notifications and access the task management system via their devices. Input consists of notification information received from the server, which triggers them to check or update task progress. Users update the progress and add comments and new information as needed. Output is the latest progress information shared within the system.

[0452] This series of steps allows the system to manage business tasks automatically and efficiently, reducing the burden on users.

[0453] (Application Example 1)

[0454] 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."

[0455] In today's information society, the widespread adoption of electronic payments generates a vast amount of transaction data, but efficiently identifying and managing important transactions within this data is not easy. Therefore, there is a need to enable safe and efficient transaction management by quickly identifying unusual or high-value transactions based on specific conditions and providing appropriate notifications.

[0456] 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.

[0457] In this invention, the server includes means for acquiring data from information exchange means, means for analyzing the acquired data and extracting important information, and means for monitoring transaction data and identifying high-value or abnormal transactions based on specific conditions. This makes it possible to respond quickly to identified transactions and provide appropriate notifications to users.

[0458] "Information exchange means" refers to communication methods used to collect data, including email and short message services.

[0459] "Means of acquiring data" refers to the function of receiving necessary data from information exchange means.

[0460] "Means for analyzing data and extracting important information" refers to a function that analyzes received data, identifies the necessary information, and extracts it.

[0461] "Means for registering and managing tasks" refers to a function that records tasks based on extracted information and monitors their progress.

[0462] "Means for generating and sending notifications" refers to functions for sending alerts and reminders to users based on work-related information.

[0463] "Means of providing an interface" refers to user interfaces and communication methods that users can use to change or report the status of their work.

[0464] "Means of monitoring transaction data and identifying high-value or unusual transactions based on specific conditions" refers to a function that monitors transaction information in real time and automatically detects transactions that meet set criteria.

[0465] "Communication methods" refer to technologies and protocols for transmitting data to remote locations, but here they are specifically used for sending notifications.

[0466] The system implementing this invention consists of a server, a user terminal, and network communication means. In this system, the server acquires data from the information exchange means, analyzes it, and extracts important information. The acquired data is analyzed using natural language processing technology to extract necessary information related to the business.

[0467] The analyzed information is registered within the system through task registration and management mechanisms. This clarifies the tasks to be handled, allowing users to proceed with their work efficiently. Notifications are generated from the server and sent to the user via a method selected by the user (e.g., email or push notification).

[0468] Furthermore, user terminals are provided with an interface from which users can check and modify the status of their work. By providing feedback to the system, the progress of work is updated and reported as needed.

[0469] Specifically, the transaction data monitoring mechanism involves a server monitoring transaction data in real time and identifying high-value or unusual transactions based on specific conditions. The communication mechanism allows the server to quickly send notifications to users when these transactions occur.

[0470] As a concrete example, when an electronic payment for a high-value item is made at a physical store, this information is sent to a server and analyzed. As a result, the server determines it to be an abnormal transaction and immediately sends a notification to the user. This allows users to quickly detect signs of fraudulent transactions and take appropriate action.

[0471] An example of a prompt might be, "Write a Python program that identifies high-value transactions and sends a notification to the user." This prompt can be used to further improve or train the system using a generative AI model.

[0472] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0473] Step 1:

[0474] The server acquires data from emails and short messages via information exchange methods. Inputs include emails and communication data. Outputs the dataset to be analyzed. This allows the server to collect information that will serve as the basis for data analysis in the next step.

[0475] Step 2:

[0476] The server analyzes the acquired data using natural language processing techniques and extracts important information. The input is the dataset obtained in step 1. The output is information related to the identified business (e.g., transaction amount, customer information, etc.). This process makes it possible to structure meaningful text information contained within the data.

[0477] Step 3:

[0478] The server registers the tasks in the task management system based on the extracted information. The input is the information about the tasks generated in step 2. As output, specific task items are added to the task management system. In terms of specific operation, the server makes the registered tasks available for users to review later.

[0479] Step 4:

[0480] The server continuously monitors transaction data in real time to automatically detect high-value or unusual transactions. The input is continuously updated transaction data. The output is transaction information that meets specific criteria. The server identifies transactions that match these criteria and processes them promptly.

[0481] Step 5:

[0482] The server sends notifications to the user regarding identified transactions. The input is the transaction information identified in step 4. The output is the notification sent to the user's device or email. Specifically, the server sends alerts in a user-specified manner to support immediate action.

[0483] Step 6:

[0484] Users check notifications sent via their terminals and, if necessary, open the task management interface to check or update the progress of their tasks. Input is notification information sent from the server. Output is the updated task progress. This allows users to easily manage their tasks.

[0485] 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.

[0486] This invention is a system that acquires data from information exchange means, analyzes it to extract important information, and registers and manages tasks based on that information. Furthermore, by incorporating an emotion engine that analyzes user emotions, it achieves more efficient and personalized task management.

[0487] The server periodically retrieves messages from email and micromessaging services via APIs of information exchange methods permitted by the user. This data is temporarily stored in a database. Next, the server analyzes this data and uses natural language processing techniques to extract task names, deadlines, project information, etc., and registers it as structured business data.

[0488] Furthermore, the emotion engine analyzes user communication data and infers the user's emotional state from natural language expressions and other parameters. This emotional state is taken into consideration when setting task priorities and adjusting notification content. In addition, the user experience is improved by providing a customized interface that responds to the user's emotions.

[0489] As a concrete example, the server analyzes an email received by a sales representative stating, "Please prepare the presentation materials by next Tuesday," and registers it as a task. Simultaneously, if the emotion engine detects signs of stress or tension from the sales representative's text style, the server adjusts the timing and method of the reminder, taking into account the task's priority. For example, it might use a gentler notification language to reduce user stress.

[0490] Thus, by utilizing an emotion engine, the present invention enables flexible responses to the user's situation, making more intuitive and effective business management possible.

[0491] The following describes the processing flow.

[0492] Step 1:

[0493] The server connects to the APIs of the information exchange methods (email and short message services) used by the user and periodically retrieves message data. This data is temporarily stored in a database.

[0494] Step 2:

[0495] The server analyzes the stored message data using natural language processing technology. This analysis extracts important information such as task names, deadlines, and related projects, and registers it in the task management database.

[0496] Step 3:

[0497] The server uses an emotion engine to analyze the user's emotional state from the acquired communication data. This analysis is based on the context of the text, the expressions used, and the choice of words.

[0498] Step 4:

[0499] The server considers the user's emotional state, as determined by the emotion engine, to set the priority of registered tasks and the timing of reminders. If the user is experiencing stress, it adjusts task priorities and adds supportive messages as needed.

[0500] Step 5:

[0501] The server sends a notification to the user's device based on the set reminder time. The tone and content of this notification change according to the user's emotional state, providing a more personalized message.

[0502] Step 6:

[0503] Users can check notifications on their devices and open the relevant task management screen to update the task's progress. User feedback is reflected on the server in real time and shared with relevant parties.

[0504] Step 7:

[0505] The server integrates this information and provides analytical results that help improve the user's work performance. This supports the user in working more efficiently.

[0506] (Example 2)

[0507] 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."

[0508] Traditional business management systems have limited information gathering and analysis capabilities, making it difficult to manage tasks while considering the individual circumstances and emotional states of users. As a result, task prioritization and notification methods are uniform, hindering improvements in the user experience. Therefore, there is a need to analyze users' emotional states and manage tasks flexibly and individually based on this analysis.

[0509] 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.

[0510] In this invention, the server includes a mechanism for acquiring information from an information exchange device, a mechanism for analyzing the acquired information and extracting important information, and a mechanism for analyzing the user's emotional state. This makes it possible to register and manage tasks based on the extracted information, while adjusting priorities and notification content according to the user's emotional state.

[0511] An "information exchange device" refers to a means of communication that can acquire or transmit data via electronic messages or short message services.

[0512] A "system" refers to a series of processes or devices designed to achieve a specific function.

[0513] "Acquisition" refers to the process of receiving information from an external source and making that information available for use internally.

[0514] "Analysis" refers to the process of performing necessary processing to evaluate and understand acquired information, and extracting meaningful data.

[0515] "Important information" refers to information essential for registering and managing tasks, and specifically includes task names, deadlines, and priorities.

[0516] "Extraction" refers to the process of selecting specific elements from analyzed information.

[0517] "Registration" refers to the process of saving extracted information to the system and making it accessible later.

[0518] "Notification" refers to an electronic message used to convey work-related information to the user.

[0519] "Emotional state" refers to the psychological state inferred from the content and parameters of a user's communication.

[0520] An "interface" refers to a means or screen display that enables the exchange of information between a user and a system.

[0521] In this invention, a server plays a central role in securely acquiring electronic messages and short-message data from an information exchange device. The acquired data is first temporarily stored in a database. Subsequently, the server analyzes this data using natural language processing technology to extract important information necessary for the business, specifically task names, deadlines, and project information. As natural language processing technology, software such as SpaCy or NLTK can be used.

[0522] The analyzed information is converted into structured data for business registration and management and registered within the system. Furthermore, for sentiment analysis, the server utilizes a sentiment analysis engine. This engine analyzes natural language expressions and other parameters based on the user's communication data to infer the user's emotional state. For example, technologies such as IBM Watson Tone Analyzer could be used as the sentiment analysis engine.

[0523] Based on these analysis results, users can manage their work through a appropriately customized interface. The interface is designed to adjust according to the user's emotional state, thereby improving the user experience.

[0524] As a concrete example, when the server receives an email from a sales representative saying, "Please prepare the presentation materials by next Tuesday," it registers this information as a task. At the same time, the emotion engine can recognize stress and tension from the sales representative's text style and adjust the reminder accordingly. Such a system enables task management that is more appropriate to the situation the user is facing.

[0525] An example of a prompt to input into a generative AI model is: "Explain how to analyze the user's incoming messages and perform appropriate task management while considering their emotional state."

[0526] This invention provides a new method for information acquisition and analysis, and enables flexible and intuitive business management based on user emotions.

[0527] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0528] Step 1:

[0529] The server retrieves electronic messages and short message service data from information exchange devices. Input is message data transmitted via the user-authorized electronic message or short message data API. Output is stored in a database in a temporary storage format. Specifically, it securely retrieves data using OAuth authentication, organizes it in the database according to the message format, and stores it there.

[0530] Step 2:

[0531] The server analyzes stored message data using natural language processing techniques. The input is temporarily stored message data. The output provides business-related information such as task names, deadlines, and project information. Specifically, it uses natural language processing software (e.g., SpaCy, NLTK) to analyze the text and extract necessary keywords and phrases.

[0532] Step 3:

[0533] The server structures business data based on the analyzed information and registers it in the task management system. The input is information analyzed using natural language processing technology. As output, the structured business data is stored in the task management system and becomes accessible to users. Specifically, it creates a new entry in the database using the extracted information and registers the task.

[0534] Step 4:

[0535] The server utilizes an emotion analysis engine to analyze the user's emotional state. The input is the user's communication data. The output is an inference of the user's emotional state. Specifically, it analyzes natural language expressions and keywords to identify the user's emotional state (e.g., stress, tension).

[0536] Step 5:

[0537] The server prioritizes tasks and adjusts notifications based on emotional states. Inputs include analyzed emotional states and structured work data. Outputs include emotionally-considered priorities and adjusted notifications. Specifically, it adjusts actual task deadlines and priorities and customizes how users are reminded.

[0538] Step 6:

[0539] The server provides the user with an interface tailored to their emotional state. The input is the user's emotional state. The output is a customized user interface. Specifically, it adjusts the system's visuals and message tone to optimize the user experience.

[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 modern households and for individuals, efficiently managing multiple activities and schedules is difficult. Furthermore, flexible activity adjustments that take into account the user's emotions are crucial for reducing their psychological burden. However, existing systems and methods fail to adequately meet these requirements, making optimal management tailored to individual circumstances challenging.

[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 acquiring information, means for analyzing the acquired information and extracting important data, and means for providing interaction means to support activities in the physical environment. This enables efficient management of household and personal activities and flexible adjustments according to the user's emotional state.

[0545] "Information acquisition means" refers to a function for acquiring data from information exchange means.

[0546] "Means for analyzing acquired information and extracting important data" refers to a function that processes acquired information and performs operations to select particularly important parts.

[0547] "Means for registering and managing activities" refers to functions for organizing and tracking activities based on extracted data.

[0548] "Means for generating and sending notifications" refers to functions that inform users of information related to their activities.

[0549] "Emotional analysis technology" is a technology that analyzes a user's input and communication to infer their emotional state.

[0550] "Interaction means" are means of facilitating interaction with users in a physical environment.

[0551] The invention will now be described in terms of its implementation. This system is designed to efficiently manage household and personal activities and to enable flexible responses that respond to the user's emotions. The server retrieves information through email and short message service APIs, temporarily stores this data in a database, and analyzes it using natural language processing technology.

[0552] The server uses open-source natural language processing libraries to extract task names, deadlines, and activity-related information, and registers this as structured data. For example, it uses NLTK to analyze key information from messages. For sentiment analysis, it is possible to infer the emotional state from the user's messages using an analysis tool called EmotionAnalyzer. Based on the user's emotions, activity priorities can be adjusted, and the content and timing of notifications can be optimized.

[0553] The device functions as a smartphone or home robot, enabling interaction with the user. This allows for support of activities in the physical environment and the provision of a customized interface tailored to the user's current state. For example, if the system detects that the user is experiencing stress, it can provide notifications in a gentler tone. Such a system would allow users to reduce their psychological burden while effectively pursuing their plans.

[0554] An example of a prompt message is: "Adjust the task management system for the home robot assistant using sentiment analysis. If the user is stressed, label it and adjust the notifications accordingly."

[0555] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0556] Step 1:

[0557] The server periodically retrieves emails and short message communications via an API (Application Programming Interface). The input is the raw message data retrieved from the API, while the output is the message data temporarily stored in a database.

[0558] Step 2:

[0559] The server analyzes message data stored in the database using natural language processing techniques. The input is the stored message data, and the output is extracted important information such as task names, deadlines, and project information. This process utilizes natural language processing libraries such as NLTK to perform text analysis.

[0560] Step 3:

[0561] The server uses EmotionAnalyzer to infer the emotional state of the analyzed message. The input is the text information extracted in step 2, and the output is an emotional score or emotional label. Based on the analysis results, the server understands the user's current mental state.

[0562] Step 4:

[0563] The server determines task priorities and reminder content based on the extracted task information and emotional state, and generates notifications at the optimal time. The input is the task information and emotional score obtained in the previous step, and the output is the generated notification message. The server uses this information to prepare tailored notifications for the user.

[0564] Step 5:

[0565] The device sends generated notifications to the user in an appropriate format. The input is the notification message prepared by the server, and the output is provided to the user as a notification via display or audio. The device can adjust the notification method according to the user's emotions and context.

[0566] 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.

[0567] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0568] 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.

[0569] [Fourth Embodiment]

[0570] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0571] 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.

[0572] 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).

[0573] 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.

[0574] 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.

[0575] 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).

[0576] 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.

[0577] 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.

[0578] 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.

[0579] 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.

[0580] 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.

[0581] 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.

[0582] 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".

[0583] The present invention is implemented as a system that acquires data from information exchange means, analyzes it to extract important information, and then registers, manages, notifies, and reports on business operations based on this information. Specific embodiments for carrying out the invention are described below.

[0584] The server first obtains data from information exchange channels. These channels include email, micromessaging services, and other communication platforms. By granting the user access to these tools, the server can automatically retrieve the relevant data.

[0585] The server then analyzes the acquired data. Using natural language processing and filtering techniques, it extracts important business-related information from the data, clarifying task names, deadlines, and related project information. Based on these analysis results, it generates business processes and registers them in the task management system.

[0586] Once a task is registered, the server prepares the associated reminder function. Reminders are automatically sent as the task's due date approaches, using the method selected by the user (e.g., push notification or email). The server also receives user feedback and progress updates through various interfaces to keep the work status up-to-date.

[0587] As a concrete example, consider an email received by a sales representative containing the instruction, "Propose a plan to the customer by next Monday." The server analyzes the email containing this instruction and registers the task "Customer Proposal" in the task management system with a Monday deadline. The day before the deadline, the server sends a push notification to the user's device prompting them to check the progress of the proposal preparation. The user receives the reminder, opens the task management screen, updates the progress, or requests assistance from team members as needed.

[0588] In this way, the present invention supports users' work management by improving work efficiency and preventing communication breakdowns.

[0589] The following describes the processing flow.

[0590] Step 1:

[0591] The server connects to the APIs of each information exchange method permitted by the user and periodically retrieves messages and email data. During this process, the data is temporarily stored in a database.

[0592] Step 2:

[0593] The server analyzes the acquired data. Using natural language processing techniques, it extracts important information such as task names, deadlines, and related project information from the text and organizes it as structured data.

[0594] Step 3:

[0595] The server generates new tasks based on the analysis results and registers them in the task management database. During registration, priority and due dates are set for the tasks, and they are categorized according to their related projects.

[0596] Step 4:

[0597] The server schedules reminders based on registered tasks. It takes into account deadlines and priorities to ensure that notifications are sent to users at the appropriate time.

[0598] Step 5:

[0599] When it's time for a reminder, the server sends a reminder to the user's device via push notification or email.

[0600] Step 6:

[0601] Users can review received reminders and open the task management screen as needed. On this screen, users can update task progress and perform actions such as completing tasks or changing deadlines.

[0602] Step 7:

[0603] The server updates the task status based on user feedback. This update information is shared in real time with other relevant systems and project members.

[0604] (Example 1)

[0605] 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".

[0606] In managing business tasks, a common problem is reduced work efficiency due to overlooking important information or failing to properly manage deadlines. Traditional systems require manual information extraction and task management, placing a heavy burden on users. Therefore, there is a need for a system that can automatically collect and analyze information and manage tasks efficiently.

[0607] 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.

[0608] In this invention, the server includes means for acquiring data from information exchange means, means for analyzing and extracting important business information using natural language processing technology, and means for registering and managing tasks in a task management system based on the extracted information. This enables automatic extraction of business information and efficient task management.

[0609] An "information exchange method" is a communication interface that allows data to be sent and received via platforms such as email or short message services.

[0610] "Means of acquiring data" refers to the processes and technologies for collecting necessary information from information exchange channels, including technologies such as APIs and database connections.

[0611] "Natural language processing technology" refers to techniques for analyzing text data and extracting useful information, and includes morphological analysis, grammatical analysis, and semantic analysis.

[0612] A "task management system" is information management software used to manage individual tasks and projects, allowing for task creation, assignment, tracking, and reporting.

[0613] "Means for generating notifications and setting up alert functions on devices" refers to technologies for automatically issuing alerts to users based on deadlines or task status, and includes push notifications and email notifications.

[0614] An "interactive window for updating and reporting progress" is an interface that allows users to record and report the progress of their work, enabling real-time information sharing.

[0615] A "generative AI model" is an artificial intelligence technology that learns from large amounts of data and makes judgments and predictions for specific tasks.

[0616] This invention is implemented as a system that acquires data from information exchange means, analyzes it to extract important information, and then registers, manages, notifies, and reports on business operations based on this information. The following describes in detail how the invention can be implemented.

[0617] The server first obtains data through an information exchange mechanism. This mechanism can include email services or short message services. Specifically, the server uses a communication protocol to fetch messages and emails via an API and stores them in a database.

[0618] The acquired data is then analyzed on the server using natural language processing (NLTK) techniques. These techniques include Python libraries such as NLTK and spaCy. The server tokenizes the text and extracts important business information (e.g., task name, due date) through contextual understanding.

[0619] The server uses this extracted information to register tasks in the task management system. By creating tasks using management software like Jira and automatically registering that information in the system, users can monitor the task status in real time.

[0620] Furthermore, the server has a function that automatically sends notifications to the device when the deadline for registered tasks approaches. These notifications are delivered to the user's device as push notifications using Firebase Cloud Messaging.

[0621] Upon receiving this notification, users can access the issue management system via their device to update their progress. Furthermore, if users provide feedback or add information using the interface, that information is sent to all clients via the server, ensuring everyone shares the latest information.

[0622] As a concrete example, consider a scenario where a sales representative receives an email instructing them to "submit the proposal by next Monday." The server analyzes this email and registers the task "Proposal Creation" in the task management system with a Monday deadline. The day before the deadline, the server sends a push notification to the user's terminal, prompting them to check the progress of their proposal.

[0623] An example of a prompt message would be: "Analyze the work instructions from the following email, extract the task name and due date, and register them in the task management system."

[0624] Thus, the present invention aims to improve business efficiency through collaboration between servers, terminals, and users.

[0625] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0626] Step 1:

[0627] The server retrieves data from information exchange channels. It uses APIs to obtain raw data from email services and short message services authorized by the user. The input for this step is raw text data such as emails and messages, which is stored in a database to prepare for subsequent analysis processes.

[0628] Step 2:

[0629] The server analyzes the acquired data using natural language processing techniques. Using the stored text data as input, it applies Python's NLTK and spaCy libraries to tokenize the text and partially label it. Here, important business information such as task names and due dates is extracted. The output is task information in a structured format.

[0630] Step 3:

[0631] The server registers the extracted task information into the issue tracking system. The input for this step is the analyzed task information, and using an API such as Jira, the server adds the issue to the system along with the specified due date and assignee information. The output is the newly registered task in the issue tracking system.

[0632] Step 4:

[0633] The server sets reminders related to tasks. It receives task information registered as input and sets reminders via Firebase Cloud Messaging. Push notifications are sent to the device at a time or date specified by the user. The output is the notification information for which the reminder has been set.

[0634] Step 5:

[0635] Users receive notifications and access the task management system via their devices. Input consists of notification information received from the server, which triggers them to check or update task progress. Users update the progress and add comments and new information as needed. Output is the latest progress information shared within the system.

[0636] This series of steps allows the system to manage business tasks automatically and efficiently, reducing the burden on users.

[0637] (Application Example 1)

[0638] 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".

[0639] In today's information society, the widespread adoption of electronic payments generates a vast amount of transaction data, but efficiently identifying and managing important transactions within this data is not easy. Therefore, there is a need to enable safe and efficient transaction management by quickly identifying unusual or high-value transactions based on specific conditions and providing appropriate notifications.

[0640] 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.

[0641] In this invention, the server includes means for acquiring data from information exchange means, means for analyzing the acquired data and extracting important information, and means for monitoring transaction data and identifying high-value or abnormal transactions based on specific conditions. This makes it possible to respond quickly to identified transactions and provide appropriate notifications to users.

[0642] "Information exchange means" refers to communication methods used to collect data, including email and short message services.

[0643] "Means of acquiring data" refers to the function of receiving necessary data from information exchange means.

[0644] "Means for analyzing data and extracting important information" refers to a function that analyzes received data, identifies the necessary information, and extracts it.

[0645] "Means for registering and managing tasks" refers to a function that records tasks based on extracted information and monitors their progress.

[0646] "Means for generating and sending notifications" refers to functions for sending alerts and reminders to users based on work-related information.

[0647] "Means of providing an interface" refers to user interfaces and communication methods that users can use to change or report the status of their work.

[0648] "Means of monitoring transaction data and identifying high-value or unusual transactions based on specific conditions" refers to a function that monitors transaction information in real time and automatically detects transactions that meet set criteria.

[0649] "Communication methods" refer to technologies and protocols for transmitting data to remote locations, but here they are specifically used for sending notifications.

[0650] The system implementing this invention consists of a server, a user terminal, and network communication means. In this system, the server acquires data from the information exchange means, analyzes it, and extracts important information. The acquired data is analyzed using natural language processing technology to extract necessary information related to the business.

[0651] The analyzed information is registered within the system through task registration and management mechanisms. This clarifies the tasks to be handled, allowing users to proceed with their work efficiently. Notifications are generated from the server and sent to the user via a method selected by the user (e.g., email or push notification).

[0652] Furthermore, user terminals are provided with an interface from which users can check and modify the status of their work. By providing feedback to the system, the progress of work is updated and reported as needed.

[0653] Specifically, the transaction data monitoring mechanism involves a server monitoring transaction data in real time and identifying high-value or unusual transactions based on specific conditions. The communication mechanism allows the server to quickly send notifications to users when these transactions occur.

[0654] As a concrete example, when an electronic payment for a high-value item is made at a physical store, this information is sent to a server and analyzed. As a result, the server determines it to be an abnormal transaction and immediately sends a notification to the user. This allows users to quickly detect signs of fraudulent transactions and take appropriate action.

[0655] An example of a prompt might be, "Write a Python program that identifies high-value transactions and sends a notification to the user." This prompt can be used to further improve or train the system using a generative AI model.

[0656] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0657] Step 1:

[0658] The server acquires data from emails and short messages via information exchange methods. Inputs include emails and communication data. Outputs the dataset to be analyzed. This allows the server to collect information that will serve as the basis for data analysis in the next step.

[0659] Step 2:

[0660] The server analyzes the acquired data using natural language processing techniques and extracts important information. The input is the dataset obtained in step 1. The output is information related to the identified business (e.g., transaction amount, customer information, etc.). This process makes it possible to structure meaningful text information contained within the data.

[0661] Step 3:

[0662] The server registers the tasks in the task management system based on the extracted information. The input is the information about the tasks generated in step 2. As output, specific task items are added to the task management system. In terms of specific operation, the server makes the registered tasks available for users to review later.

[0663] Step 4:

[0664] The server continuously monitors transaction data in real time to automatically detect high-value or unusual transactions. The input is continuously updated transaction data. The output is transaction information that meets specific criteria. The server identifies transactions that match these criteria and processes them promptly.

[0665] Step 5:

[0666] The server sends notifications to the user regarding identified transactions. The input is the transaction information identified in step 4. The output is the notification sent to the user's device or email. Specifically, the server sends alerts in a user-specified manner to support immediate action.

[0667] Step 6:

[0668] Users check notifications sent via their terminals and, if necessary, open the task management interface to check or update the progress of their tasks. Input is notification information sent from the server. Output is the updated task progress. This allows users to easily manage their tasks.

[0669] 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.

[0670] This invention is a system that acquires data from information exchange means, analyzes it to extract important information, and registers and manages tasks based on that information. Furthermore, by incorporating an emotion engine that analyzes user emotions, it achieves more efficient and personalized task management.

[0671] The server periodically retrieves messages from email and micromessaging services via APIs of information exchange methods permitted by the user. This data is temporarily stored in a database. Next, the server analyzes this data and uses natural language processing techniques to extract task names, deadlines, project information, etc., and registers it as structured business data.

[0672] Furthermore, the emotion engine analyzes user communication data and infers the user's emotional state from natural language expressions and other parameters. This emotional state is taken into consideration when setting task priorities and adjusting notification content. In addition, the user experience is improved by providing a customized interface that responds to the user's emotions.

[0673] As a concrete example, the server analyzes an email received by a sales representative stating, "Please prepare the presentation materials by next Tuesday," and registers it as a task. Simultaneously, if the emotion engine detects signs of stress or tension from the sales representative's text style, the server adjusts the timing and method of the reminder, taking into account the task's priority. For example, it might use a gentler notification language to reduce user stress.

[0674] Thus, by utilizing an emotion engine, the present invention enables flexible responses to the user's situation, making more intuitive and effective business management possible.

[0675] The following describes the processing flow.

[0676] Step 1:

[0677] The server connects to the APIs of the information exchange methods (email and short message services) used by the user and periodically retrieves message data. This data is temporarily stored in a database.

[0678] Step 2:

[0679] The server analyzes the stored message data using natural language processing technology. This analysis extracts important information such as task names, deadlines, and related projects, and registers it in the task management database.

[0680] Step 3:

[0681] The server uses an emotion engine to analyze the user's emotional state from the acquired communication data. This analysis is based on the context of the text, the expressions used, and the choice of words.

[0682] Step 4:

[0683] The server considers the user's emotional state, as determined by the emotion engine, to set the priority of registered tasks and the timing of reminders. If the user is experiencing stress, it adjusts task priorities and adds supportive messages as needed.

[0684] Step 5:

[0685] The server sends a notification to the user's device based on the set reminder time. The tone and content of this notification change according to the user's emotional state, providing a more personalized message.

[0686] Step 6:

[0687] Users can check notifications on their devices and open the relevant task management screen to update the task's progress. User feedback is reflected on the server in real time and shared with relevant parties.

[0688] Step 7:

[0689] The server integrates this information and provides analytical results that help improve the user's work performance. This supports the user in working more efficiently.

[0690] (Example 2)

[0691] 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".

[0692] Traditional business management systems have limited information gathering and analysis capabilities, making it difficult to manage tasks while considering the individual circumstances and emotional states of users. As a result, task prioritization and notification methods are uniform, hindering improvements in the user experience. Therefore, there is a need to analyze users' emotional states and manage tasks flexibly and individually based on this analysis.

[0693] 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.

[0694] In this invention, the server includes a mechanism for acquiring information from an information exchange device, a mechanism for analyzing the acquired information and extracting important information, and a mechanism for analyzing the user's emotional state. This makes it possible to register and manage tasks based on the extracted information, while adjusting priorities and notification content according to the user's emotional state.

[0695] An "information exchange device" refers to a means of communication that can acquire or transmit data via electronic messages or short message services.

[0696] A "system" refers to a series of processes or devices designed to achieve a specific function.

[0697] "Acquisition" refers to the process of receiving information from an external source and making that information available for use internally.

[0698] "Analysis" refers to the process of performing necessary processing to evaluate and understand acquired information, and extracting meaningful data.

[0699] "Important information" refers to information essential for registering and managing tasks, and specifically includes task names, deadlines, and priorities.

[0700] "Extraction" refers to the process of selecting specific elements from analyzed information.

[0701] "Registration" refers to the process of saving extracted information to the system and making it accessible later.

[0702] "Notification" refers to an electronic message used to convey work-related information to the user.

[0703] "Emotional state" refers to the psychological state inferred from the content and parameters of a user's communication.

[0704] An "interface" refers to a means or screen display that enables the exchange of information between a user and a system.

[0705] In this invention, a server plays a central role in securely acquiring electronic messages and short-message data from an information exchange device. The acquired data is first temporarily stored in a database. Subsequently, the server analyzes this data using natural language processing technology to extract important information necessary for the business, specifically task names, deadlines, and project information. As natural language processing technology, software such as SpaCy or NLTK can be used.

[0706] The analyzed information is converted into structured data for business registration and management and registered within the system. Furthermore, for sentiment analysis, the server utilizes a sentiment analysis engine. This engine analyzes natural language expressions and other parameters based on the user's communication data to infer the user's emotional state. For example, technologies such as IBM Watson Tone Analyzer could be used as the sentiment analysis engine.

[0707] Based on these analysis results, users can manage their work through a appropriately customized interface. The interface is designed to adjust according to the user's emotional state, thereby improving the user experience.

[0708] As a concrete example, when the server receives an email from a sales representative saying, "Please prepare the presentation materials by next Tuesday," it registers this information as a task. At the same time, the emotion engine can recognize stress and tension from the sales representative's text style and adjust the reminder accordingly. Such a system enables task management that is more appropriate to the situation the user is facing.

[0709] An example of a prompt to input into a generative AI model is: "Explain how to analyze the user's incoming messages and perform appropriate task management while considering their emotional state."

[0710] This invention provides a new method for information acquisition and analysis, and enables flexible and intuitive business management based on user emotions.

[0711] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0712] Step 1:

[0713] The server retrieves electronic messages and short message service data from information exchange devices. Input is message data transmitted via the user-authorized electronic message or short message data API. Output is stored in a database in a temporary storage format. Specifically, it securely retrieves data using OAuth authentication, organizes it in the database according to the message format, and stores it there.

[0714] Step 2:

[0715] The server analyzes stored message data using natural language processing techniques. The input is temporarily stored message data. The output provides business-related information such as task names, deadlines, and project information. Specifically, it uses natural language processing software (e.g., SpaCy, NLTK) to analyze the text and extract necessary keywords and phrases.

[0716] Step 3:

[0717] The server structures business data based on the analyzed information and registers it in the task management system. The input is information analyzed using natural language processing technology. As output, the structured business data is stored in the task management system and becomes accessible to users. Specifically, it creates a new entry in the database using the extracted information and registers the task.

[0718] Step 4:

[0719] The server utilizes an emotion analysis engine to analyze the user's emotional state. The input is the user's communication data. The output is an inference of the user's emotional state. Specifically, it analyzes natural language expressions and keywords to identify the user's emotional state (e.g., stress, tension).

[0720] Step 5:

[0721] The server prioritizes tasks and adjusts notifications based on emotional states. Inputs include analyzed emotional states and structured work data. Outputs include emotionally-considered priorities and adjusted notifications. Specifically, it adjusts actual task deadlines and priorities and customizes how users are reminded.

[0722] Step 6:

[0723] The server provides the user with an interface tailored to their emotional state. The input is the user's emotional state. The output is a customized user interface. Specifically, it adjusts the system's visuals and message tone to optimize the user experience.

[0724] (Application Example 2)

[0725] 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".

[0726] In modern households and for individuals, efficiently managing multiple activities and schedules is difficult. Furthermore, flexible activity adjustments that take into account the user's emotions are crucial for reducing their psychological burden. However, existing systems and methods fail to adequately meet these requirements, making optimal management tailored to individual circumstances challenging.

[0727] 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.

[0728] In this invention, the server includes means for acquiring information, means for analyzing the acquired information and extracting important data, and means for providing interaction means to support activities in the physical environment. This enables efficient management of household and personal activities and flexible adjustments according to the user's emotional state.

[0729] "Information acquisition means" refers to a function for acquiring data from information exchange means.

[0730] "Means for analyzing acquired information and extracting important data" refers to a function that processes acquired information and performs operations to select particularly important parts.

[0731] "Means for registering and managing activities" refers to functions for organizing and tracking activities based on extracted data.

[0732] "Means for generating and sending notifications" refers to functions that inform users of information related to their activities.

[0733] "Emotional analysis technology" is a technology that analyzes a user's input and communication to infer their emotional state.

[0734] "Interaction means" are means of facilitating interaction with users in a physical environment.

[0735] The invention will now be described in terms of its implementation. This system is designed to efficiently manage household and personal activities and to enable flexible responses that respond to the user's emotions. The server retrieves information through email and short message service APIs, temporarily stores this data in a database, and analyzes it using natural language processing technology.

[0736] The server uses open-source natural language processing libraries to extract task names, deadlines, and activity-related information, and registers this as structured data. For example, it uses NLTK to analyze key information from messages. For sentiment analysis, it is possible to infer the emotional state from the user's messages using an analysis tool called EmotionAnalyzer. Based on the user's emotions, activity priorities can be adjusted, and the content and timing of notifications can be optimized.

[0737] The device functions as a smartphone or home robot, enabling interaction with the user. This allows for support of activities in the physical environment and the provision of a customized interface tailored to the user's current state. For example, if the system detects that the user is experiencing stress, it can provide notifications in a gentler tone. Such a system would allow users to reduce their psychological burden while effectively pursuing their plans.

[0738] An example of a prompt message is: "Adjust the task management system for the home robot assistant using sentiment analysis. If the user is stressed, label it and adjust the notifications accordingly."

[0739] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0740] Step 1:

[0741] The server periodically retrieves emails and short message communications via an API (Application Programming Interface). The input is the raw message data retrieved from the API, while the output is the message data temporarily stored in a database.

[0742] Step 2:

[0743] The server analyzes message data stored in the database using natural language processing techniques. The input is the stored message data, and the output is extracted important information such as task names, deadlines, and project information. This process utilizes natural language processing libraries such as NLTK to perform text analysis.

[0744] Step 3:

[0745] The server uses EmotionAnalyzer to infer the emotional state of the analyzed message. The input is the text information extracted in step 2, and the output is an emotional score or emotional label. Based on the analysis results, the server understands the user's current mental state.

[0746] Step 4:

[0747] The server determines task priorities and reminder content based on the extracted task information and emotional state, and generates notifications at the optimal time. The input is the task information and emotional score obtained in the previous step, and the output is the generated notification message. The server uses this information to prepare tailored notifications for the user.

[0748] Step 5:

[0749] The device sends generated notifications to the user in an appropriate format. The input is the notification message prepared by the server, and the output is provided to the user as a notification via display or audio. The device can adjust the notification method according to the user's emotions and context.

[0750] 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.

[0751] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0752] 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.

[0753] 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.

[0754] 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.

[0755] 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.

[0756] 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.

[0757] 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.

[0758] 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."

[0759] 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.

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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.

[0765] 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.

[0766] 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.

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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 to be incorporated by reference.

[0771] The following is further disclosed regarding the embodiments described above.

[0772] (Claim 1)

[0773] Means for obtaining data from information exchange means,

[0774] A means of analyzing acquired data and extracting important information,

[0775] A means of registering and managing tasks based on the extracted information,

[0776] Means for generating and sending notifications related to business operations,

[0777] A means of providing an interface for updating and reporting the status of operations,

[0778] A system that includes this.

[0779] (Claim 2)

[0780] The system according to claim 1, characterized in that the means of information exchange includes email and short message services.

[0781] (Claim 3)

[0782] The system according to claim 1, further comprising means for setting priorities and deadlines for tasks based on analyzed important information.

[0783] "Example 1"

[0784] (Claim 1)

[0785] Means for obtaining data from information exchange means,

[0786] A means of analyzing acquired data and extracting important business information using natural language processing technology,

[0787] A means of generating tasks based on extracted information, and registering and managing those tasks in a task management system,

[0788] A means for generating work-related notifications and setting up a warning function on the terminal,

[0789] A means of providing an interactive channel for updating and reporting on the progress of work,

[0790] A system that includes this.

[0791] (Claim 2)

[0792] The system according to claim 1, characterized in that the information exchange means includes email and short message communication means.

[0793] (Claim 3)

[0794] The system according to claim 1, further comprising means for setting priorities and deadlines for tasks based on important information analyzed using a generative AI model.

[0795] "Application Example 1"

[0796] (Claim 1)

[0797] Means for obtaining data from information exchange means,

[0798] A means of analyzing acquired data and extracting important information,

[0799] A means of registering and managing tasks based on the extracted information,

[0800] Means for generating and sending notifications related to business operations,

[0801] A means of providing an interface for updating and reporting the status of operations,

[0802] A means of monitoring transaction data and identifying high-value or unusual transactions based on specific conditions,

[0803] A means of communication for sending notifications to users regarding identified transactions,

[0804] A system that includes this.

[0805] (Claim 2)

[0806] The system according to claim 1, characterized in that the information exchange means includes email and short message communication means.

[0807] (Claim 3)

[0808] The system according to claim 1, further comprising means for setting priorities and deadlines for tasks based on analyzed important information.

[0809] "Example 2 of combining an emotion engine"

[0810] (Claim 1)

[0811] A mechanism for acquiring information from an information exchange device,

[0812] A system that analyzes acquired information and extracts important information,

[0813] A system for registering and managing tasks based on extracted information,

[0814] A mechanism for generating and sending notifications related to the task,

[0815] A mechanism for analyzing the user's emotional state,

[0816] A system that prioritizes tasks and adjusts notification content based on emotional state,

[0817] A mechanism that provides an interface that responds to emotional states,

[0818] A system that includes this.

[0819] (Claim 2)

[0820] The system according to claim 1, characterized in that the information exchange device includes electronic messaging and short message communication services.

[0821] (Claim 3)

[0822] The system according to claim 1, further comprising a mechanism for setting work priorities and deadlines based on analyzed key information and the user's emotional state.

[0823] "Application example 2 when combining with an emotional engine"

[0824] (Claim 1)

[0825] Means of obtaining information,

[0826] A means of analyzing acquired information and extracting important data,

[0827] A means of registering and managing activities based on extracted data,

[0828] Means for generating and sending notifications related to the activity,

[0829] A means of understanding the user's emotional state using emotion analysis technology and adjusting the content of notifications based on that understanding,

[0830] Means for providing interaction methods to support activities in a physical environment,

[0831] A system that includes this.

[0832] (Claim 2)

[0833] The system according to claim 1, characterized in that the information exchange means includes electronic communication and short message services.

[0834] (Claim 3)

[0835] The system according to claim 1, further comprising means for setting priorities and deadlines for activities based on analyzed key data. [Explanation of Symbols]

[0836] 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

1. Means for obtaining data from information exchange means, A means of analyzing acquired data and extracting important information, A means of registering and managing tasks based on the extracted information, Means for generating and sending notifications related to business operations, A means of providing an interface for updating and reporting the status of operations, A system that includes this.

2. The system according to claim 1, characterized in that the means for exchanging information includes email and short message services.

3. The system according to claim 1, further comprising means for setting priorities and deadlines for tasks based on analyzed important information.

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