System

Abstract

A system is provided.SOLUTION: The system includes a means for automatically determining a category by analyzing the text of a mail, a means for acquiring the number of destinations of the mail, a means for extracting the first part of the text of the mail to generate a summary sentence, a means for inserting the generated summary into the head of the text of the mail, and a means for transmitting the mail text with the summary.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] There is a problem with business emails in that it is difficult for recipients to grasp the contents of the emails they receive at a glance and quickly determine their importance. This reduces work efficiency, especially when processing multiple emails, as they must check the contents one by one. Furthermore, if the sender is unable to succinctly summarize the important points in the email they send, there is also the issue of not properly conveying the necessary information to the recipient. [Means for solving the problem]

[0005] To solve the above problems, the present invention proposes a system that provides a means for automatically determining the category of an email by analyzing the email body, a means for acquiring the number of recipients of the email, a means for extracting the first part of the email body to generate a summary, a means for inserting the generated summary at the beginning of the email body, and a means for sending the email body with the summary. This system allows recipients to quickly determine the content and importance of an email before opening it, improving work efficiency. Furthermore, the automatically generated summary allows senders to clearly convey the main points of their message.

[0006] "Means for automatically determining the category by analyzing the body of the email" is a function that analyzes the content of the email to be sent and classifies the email into one of the categories such as "Contact," "Task," or "Other" based on that content.

[0007] The "means for acquiring the number of recipients of an email" is a function for acquiring the number of recipients specified when sending an email, and generating a summary of the email using that information.

[0008] "Means for extracting the first part of the email body and generating a summary" refers to a function that extracts the first part of the email body (for example, the first 200 characters) and uses that part to generate a summary of the email.

[0009] The "means for inserting the generated summary at the beginning of the email body" is a function for automatically adding the summary generated by analysis and extraction to the beginning of the email body.

[0010] The "means for sending the email body with a summary" is a function for sending the email body with the summary inserted to the recipient. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2]1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0012] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0013] First, the terms used in the following description will be explained.

[0014] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0015] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0016] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0017] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0018] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0019] [First embodiment]

[0020] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0021] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0022] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0023] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0024] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0025] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0026] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0027] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0029] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0030] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0031] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0032] An embodiment of the present invention will be described below, which concerns a system that analyzes the body of an email, automatically determines the category, acquires the number of recipients, extracts the first part of the email body, generates a summary, generates a summary based on this information, and sends the email body with the summary inserted at the beginning of the email body.

[0033] Server-side processing

[0034] The server performs the following process each time a new email is sent:

[0035] 1. Email Analysis

[0036] The server analyzes the content of the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). This analysis process may use natural language processing (NLP) technology.

[0037] 2. Obtaining the number of senders

[0038] The server obtains the number of recipients listed in the To, CC, and BCC fields of the email and records this number as the number of recipients.

[0039] 3. Summary Generation

[0040] The server extracts the first 200 characters of the email body and sets it as a summary, which is used to succinctly express the important content of the email.

[0041] 4. Generating a summary

[0042] The server generates a "summary of this email" by combining the category, number of recipients, and summary text based on the analysis results.

[0043] Terminal side processing

[0044] The terminal performs the following process when the user sends an email.

[0045] 1. Email Request

[0046] When a user enters the email body on the email composition screen and presses the send button, the device sends an email analysis request to the server via the extension, which includes the email body, subject, and recipient information.

[0047] 2. Receiving a response from the server

[0048] The terminal receives summary information returned from the server, which includes the email category, the number of senders, and a summary.

[0049] 3. Update the email body

[0050] The terminal adds the received summary information to the beginning of the mail body, and generates a new mail body with the summary.

[0051] 4. Send email

[0052] Finally, the terminal sends the new mail body with the summary to the user's intended recipient.

[0053] User operations

[0054] The user performs the following operations:

[0055] 1. Create an email

[0056] The user opens the Gmail email composition screen as usual and enters the recipient, subject, and body of the email.

[0057] 2. Send email

[0058] When the user hits the send button, a summary is automatically generated and inserted at the beginning of the email body, after which the email is sent to its destination.

[0059] Explanation with a concrete example

[0060] For example, suppose a user creates an email like this:

[0061] Subject: Regarding deadline extension

[0062] Thank you for your continued support. This is Suzuki from the company.

[0063] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0064] When this email is sent, the server analyzes the text, determines the category as "Contact," and gets the number of recipients as 1. It generates a summary by extracting the first 200 characters and creates the following summary:

[0065] Summary of this email

[0066] Category: Contact

[0067] Number of senders: 1

[0068] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0069] This summary will be inserted at the beginning of the email body, and will look like this:

[0070] Summary of this email

[0071] Category: Contact

[0072] Number of senders: 1

[0073] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0074] Subject: Regarding deadline extension

[0075] Thank you for your continued support. This is Suzuki from the company.

[0076] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0077] Finally, the user can send a properly structured email without any special operations, making it easier for the recipient to understand the content. In this way, the present invention provides a system that helps the recipient of the email quickly understand the content and improves work efficiency.

[0078] The processing flow will be explained below.

[0079] Step 1:

[0080] The user opens the email composition screen, enters the recipient, subject, and body of the email, and performs the usual email composition operation.

[0081] Step 2:

[0082] The user clicks the "Send" button. At this moment, the device starts pre-processing for sending the email.

[0083] Step 3:

[0084] The terminal's extension function is launched and acquires the body, subject, and recipient information of the email currently being composed.

[0085] Step 4:

[0086] The terminal generates a request to send the acquired email body, subject, and destination information to the server. The request includes the email body text and destination information.

[0087] Step 5:

[0088] The server receives the request and begins parsing the email body.

[0089] Step 6:

[0090] The server analyzes the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). The category is determined, for example, as follows:

[0091] "if (emailBody.includes('Tasks')) { category = 'Tasks';}"

[0092] "else if (emailBody.includes('Contact')) { category = 'Contact';}"

[0093] "else { category = 'Other';}"

[0094] Step 7:

[0095] The server obtains the number of recipients based on the destination information, which can be easily obtained from the email header information.

[0096] Step 8:

[0097] The server extracts the first 200 characters of the email body and generates a summary that summarizes the important parts of the email body. For example, it is extracted as "let summaryText = emailBody.substring(0, 200);".

[0098] Step 9:

[0099] The server generates a summary by combining the category, the number of recipients, and the summary text. The generated summary will have the following format:

[0100] "Summary of this email\nCategory: ${category}\nNumber of recipients: ${recipientCount}\nSummary: ${summaryText}"

[0101] Step 10:

[0102] The server returns the generated summary to the terminal.

[0103] Step 11:

[0104] The terminal receives the response from the server and obtains the summary information.

[0105] Step 12:

[0106] The summary information received by the terminal is inserted at the beginning of the email body. The new email body will look like this:

[0107] "let updatedEmailBody = ${summary}\n\n${emailBody}"

[0108] Step 13:

[0109] The terminal generates a new email body with a summary and resumes the email sending process.

[0110] Step 14:

[0111] The device sends the updated email body to the recipient, and the email is sent.

[0112] Example 1

[0113] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0114] Efficient communication via e-mail is important in many business processes. However, when the body of an e-mail is lengthy, it is difficult for the recipient to quickly grasp the important information. This results in reduced work efficiency and slower decision-making. Furthermore, if the e-mail category is not properly determined, it can be difficult to organize and search for information. Furthermore, the number of e-mail recipients is also important information, and not knowing this information makes it difficult to respond appropriately.

[0115] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0116] In this invention, the server includes means for automatically analyzing the email body to determine its category, means for acquiring the number of recipients of the email, means for extracting the first part of the email body to generate a summary, means for inserting the generated summary at the beginning of the email body, means for transmitting the email body with the summary, means for determining the category based on keywords using natural language processing technology, means for sending an email analysis request to the server, and means for receiving summary information from the server and updating the email body. This allows email recipients to quickly grasp important information and take appropriate action. Automating email category determination and recording the number of recipients facilitates information organization and search, improving business efficiency.

[0117] "Means for automatically determining the category by analyzing the body of an email" refers to technology that analyzes the content of an email and automatically identifies the type and purpose of the email based on specific keywords and patterns.

[0118] "Means for obtaining the number of recipients of an email" refers to a method for calculating the total number of recipients from the destination information of an email and recording that information.

[0119] "Means for extracting the first part of the email body and generating a summary" refers to a technology that extracts text within a specified number of characters from the email body and uses that text as the summary of the email.

[0120] "Means for inserting the generated summary at the beginning of the email body" refers to a technology or method for adding the generated summary to the beginning of the original email content.

[0121] "Means for sending an email body with a summary" refers to a technique for delivering an email to a designated recipient after a summary has been added.

[0122] "Means for determining categories based on keywords using natural language processing technology" refers to a method of using natural language processing (NLP) algorithms to extract important keywords from the text in an email and determine the type of email based on that.

[0123] "Means for sending an email analysis request to a server" refers to a technology for sending the email body and related information to a server in order to analyze the content of an email created by a user.

[0124] "Means for receiving summary information from a server and updating the email body" refers to a technology or method for receiving summary information returned from a server and using it to update the original email content.

[0125] An embodiment of the present invention will be described below. This invention provides a system that analyzes the body of an email, automatically determines the category, obtains the number of recipients, generates an outline of the email body, creates a summary, and inserts it at the beginning of the email. This system enables email recipients to quickly grasp information and improve work efficiency.

[0126] Server-side processing

[0127] The server processes each email sent using Python software, with natural language processing (NLP) techniques such as NLTK and spaCy used for automated email analysis.

[0128] 1. Email analysis: The server analyzes the body of the received email and determines the category based on specific keywords. For example, emails containing keywords such as "contact" or "task" are classified into specific categories.

[0129] 2. Get the number of recipients: The server gets the number of recipients in the To, CC, and BCC fields of the email using Python's built-in library.

[0130] 3. Summary generation: The server extracts the first 200 characters of the email body and sets them as a summary, which succinctly expresses the important content of the email.

[0131] 4. Summary generation: The server generates a summary by combining the analyzed categories, the number of senders, and a summary. This summary is inserted at the beginning of the email.

[0132] Terminal side processing

[0133] The device mainly processes emails sent by users. The device's extended functionality uses JavaScript (registered trademark) and the Gmail API.

[0134] 1. Email sending request: When a user presses the send button on the email composition screen, the device sends an email analysis request to the server. This request includes the email body, subject, and recipient information.

[0135] 2. Receiving a response from the server: The terminal receives summary information returned from the server, which includes the email category, the number of senders, and a summary.

[0136] 3. Update the email body: The terminal adds the summary information to the beginning of the email body and generates a new email body with the summary.

[0137] 4. Send email: The device finally sends the updated email body to the specified recipient.

[0138] User operations

[0139] The user opens an email creation screen such as Gmail as usual, enters the recipient, subject, and body of the email, and when they press the send button, the email is automatically analyzed and a summary is generated and inserted.

[0140] Specific examples

[0141] For example, consider the case where a user creates an email with the following content:

[0142] Subject: Regarding deadline extension

[0143] Thank you for your continued support. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0144] The server analyzes this email, determines that it is in the "Contact" category, and sets the number of recipients to 1. It extracts the first 200 characters of the email body and generates the following summary:

[0145] Summary of this email

[0146] Category: Contact

[0147] Number of senders: 1

[0148] Summary: Thank you for your continued support. I would like to extend the deadline for this project due to the following reasons...

[0149] This summary is inserted at the beginning of the email body and is finally sent to the recipient.

[0150] Prompt Sentence Examples

[0151] """A new email has been created. Please parse the body of the email below to generate a category and summary."""

[0152] This system allows users to quickly convey important information to recipients without performing any special operations, improving work efficiency and enabling faster decision-making.

[0153] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0154] Server-side processing

[0155] Step 1: Email Analysis

[0156] The server analyzes the body of each new email sent. It receives the body of the email to be sent as input and uses natural language processing (NLP) techniques to extract specific keywords. For example, it extracts keywords such as "project" and "contact," and automatically classifies the email as a "business contact" based on these keywords. This is done using Python and NLP libraries such as NLTK and spaCy.

[0157] Input: Email body

[0158] Output: Email category (e.g. "Business Notice")

[0159] Specific operation: The server runs a Python script to extract keywords from the email body and determine the category.

[0160] Step 2: Get the number of senders

[0161] The server obtains the number of recipients listed in the To, CC, and BCC fields of the email. It receives the email header information as input and calculates the number of recipients using Python's built-in library. For example, if there are three To, two CC, and one BCC recipients, the server obtains a total of six recipients.

[0162] Input: Email header information

[0163] Output: Number of recipients (e.g. 6)

[0164] Specific operation: The server analyzes the header information of the received email and compiles a list of recipients.

[0165] Step 3: Generate a summary

[0166] The server extracts the first 200 characters of the email body and sets it as a summary. It receives the email body as input and performs string manipulation to extract the first 200 characters. This generates a summary that succinctly conveys the important content of the email.

[0167] Input: Email body

[0168] Output: Summary (e.g. "Thank you for your continued support. The deadline for this project is...")

[0169] Specific operation: The server uses a Python script to extract the first 200 characters of the email body and generate a summary.

[0170] Step 4: Generate a summary

[0171] The server generates a summary by combining the category based on the analysis results, the number of senders, and the summary. As input, it receives the determined category, the number of senders, and the generated summary, and inserts these into a standard format to generate the summary.

[0172] Input: Category, number of recipients, summary

[0173] Output: Summary (Example: "Summary of this email\nCategory: Business communication\nNumber of recipients: 6\nSummary: Thank you for your continued support...")

[0174] What it does: The server runs a Python script that generates a summary by inserting the category, number of senders, and summary text into a format.

[0175] Terminal side processing

[0176] Step 1: Email Sending Request

[0177] When a user enters the email body on the email composition screen and presses the send button, the device sends an email analysis request to the server. The device takes the email body, subject, and recipient information entered by the user as input, generates an HTTP request using JavaScript and the Gmail API, and sends it to the server.

[0178] Input: Email body, subject, recipient information

[0179] Output: Sending an email parsing request

[0180] Specific operation: The device executes JavaScript and sends the email information to the server as an HTTP request.

[0181] Step 2: Receiving a response from the server

[0182] The terminal receives the summary information returned from the server. As input, it receives the HTTP response from the server and parses it using JavaScript. The summary information includes the email category, the number of senders, and a summary.

[0183] Input: HTTP response from the server

[0184] Output: Receive summary information

[0185] Specific operation: The terminal receives the HTTP response and extracts summary information using JavaScript.

[0186] Step 3: Update the email body

[0187] The terminal adds the summary information to the beginning of the email body and generates a new email body. As input, it receives the received summary information and the original email body, performs string manipulation, and adds the summary to the beginning.

[0188] Input: Summary information, original email body

[0189] Output: New email body

[0190] Specific operation: The device uses JavaScript to add summary information to the beginning of the original email body.

[0191] Step 4: Send email

[0192] The terminal finally sends the new email body with the summary to the specified recipient. As input, it takes the new email body and email destination information and sends it using the Gmail API.

[0193] Input: New email body, email recipient information

[0194] Output: Send email

[0195] Specific operation: The device uses the Gmail API to send the new email body to the recipient.

[0196] User operations

[0197] Step 1: Create an email

[0198] The user opens the email creation screen as usual and enters the recipient, subject, and body of the email. The terminal receives the email creation information manually entered by the user as input and manages it.

[0199] Input: User email creation information

[0200] Output: Save email information

[0201] Specific operation: The user enters email information using an email composition screen such as Gmail.

[0202] (Application example 1)

[0203] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0204] When an email contains a large amount of information, it is difficult for the recipient to quickly understand the content. Furthermore, as the number of customer response emails and notifications increases in virtual stores, there is a need for a method to efficiently manage these emails and quickly convey important information to recipients. To solve this problem, it is necessary to automate email analysis and automatically generate summaries using a generative AI model. Furthermore, when generating summaries, a function is also needed to automatically insert the generated summaries into the email body.

[0205] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0206] In this invention, the server includes means for analyzing the email body and automatically determining the category, means for acquiring the number of recipients of the email, means for extracting the first part of the email body and generating a summary, means for inserting the generated summary at the beginning of the email body, means for sending the email body with the summary, means for analyzing emails and notifications for customer service in the virtual store and generating summaries, and means for using a generation AI model and prompt text when generating summaries. This enables efficient management of emails and notifications for customer service in the virtual store and enables recipients to quickly grasp important information.

[0207] "Means for automatically determining the category by analyzing the body of the email" is a function that interprets the content of the email and automatically identifies its category based on specific keywords or patterns.

[0208] "Means for obtaining the number of recipients of an email" is a function that automatically calculates and obtains the number of recipients listed in the To, CC, and BCC fields of an email.

[0209] The "means for extracting the first part of the email body and generating a summary" is a function that extracts a certain portion of the first part of the email body and uses that portion to generate a summary as a short sentence.

[0210] The "means for inserting the generated summary at the beginning of the email body" is a function for adding an automatically generated summary to the beginning of the email body and inserting it at the beginning of the email body.

[0211] The "means for sending the email body with the summary" is a function for finally sending the improved email with the summary inserted to the specified recipient.

[0212] "Means for analyzing emails and notifications related to customer service in a virtual store and generating summaries" is a function that analyzes emails and notifications related to the operation of a virtual store and automatically generates summaries that summarize their contents in a concise and easy-to-understand format.

[0213] "Means for using a generative AI model and prompt sentences when generating summaries" refers to a function that utilizes a generative AI model when generating summaries and performs effective natural language generation using optimal prompt sentences.

[0214] MODE FOR CARRYING OUT THE INVENTION

[0215] overview

[0216] This invention provides a system for efficiently and quickly processing customer correspondence emails and notifications in a virtual store. In particular, the system analyzes the text of the email, automatically classifies it into an appropriate category, generates a summary, and inserts the generated summary at the beginning of the email text before sending it, allowing the recipient to quickly grasp important information.

[0217] Server-side processing

[0218] Each time a new email is sent, the server performs the following process. First, the server analyzes the email body and automatically assigns it to a specified category. This process is performed using natural language processing (NLP) technology, based on specific keywords and phrases. Next, the server obtains the number of recipients from the email's recipient list and records that number. After that, it extracts the first part of the email body (for example, the first 200 characters) and sets it as the summary. Finally, it combines the category, number of recipients, and summary to generate a summary, which is then inserted at the beginning of the email body.

[0219] Terminal side processing

[0220] When a user sends an email, the device first sends an email sending request to the server. This request includes the email body, subject, and recipient information. The server receives the request, performs the server-side processing described above to generate a summary, and returns it to the device. The device then adds the received summary information to the beginning of the email body to generate a new email body with the summary. When the user finally presses the send button, the device sends the email body with the summary to the specified recipient.

[0221] Program processing

[0222] This system is implemented using a Python program. Specifically, it uses a natural language processing library (e.g., scikit-learn) to analyze the email body and determine the category. It also uses a generative AI model to generate summaries and efficiently generate natural language using optimal prompts. The SMTP protocol is used to send emails, utilizing the Python smtplib library.

[0223] Hardware / Software used

[0224] Hardware: Standard servers or cloud-based servers (e.g., AWS® or Google® Cloud)

[0225] Software: Python, natural language processing library (scikit-learn), SMTP library (smtplib)

[0226] Specific examples

[0227] For example, if the support team for a hypothetical store, "XYZ Store," sends an email with the following content:

[0228] text

[0229] Subject: Enquiry about new features in XYZ Store

[0230] Body: Thank you for your support. This is customer support from XYZ Store. We'll respond to your inquiry about new features shortly...

[0231] The system automatically inserts the following summary:

[0232] text

[0233] Summary of this email

[0234] Category: Inquiry

[0235] Number of senders: 1

[0236] Summary: Hello, this is customer support for XYZ Store. We'll get back to you shortly with any questions you may have about new features...

[0237] Prompt Sentence Examples

[0238] An example prompt for a generative AI model is:

[0239] text

[0240] Analyze the content of the email below and generate the category, number of recipients, and summary.

[0241] ---

[0242] Subject: {subject}

[0243] Body: {body}

[0244] This system streamlines customer-facing emails and notifications in virtual stores, allowing recipients to quickly grasp important information.

[0245] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0246] Program processing steps

[0247] Step 1: Email Sending Request

[0248] When the user enters the email body on the email creation screen and presses the send button, the device sends a send request including the email body, subject, and recipient information to the server.

[0249] Input: Email body, subject, recipient information

[0250] Output: Email parsing request to the server

[0251] Specific operation: When the user completes the input and presses the send button, the terminal compiles this data and sends it to the server as an HTTP request.

[0252] Step 2: Email Analysis

[0253] The server analyzes the body of the received email and automatically determines the category based on specific keywords and phrases, using natural language processing technology.

[0254] Input: Email body

[0255] Output: Email Category

[0256] Specific operation: The server analyzes the email body using a natural language processing model (such as scikit-learn) and determines the category based on the frequency of word occurrence and context.

[0257] Step 3: Get the number of senders

[0258] The server obtains the number of recipients from the email address list and records that number.

[0259] Input: To information, CC information, BCC information

[0260] Output: Number of recipients

[0261] Specific operation: The server analyzes the recipient list, totals the number of email addresses contained in each list, and obtains the number of recipients.

[0262] Step 4: Generate a summary

[0263] The server extracts the first 200 characters of the email body and sets them as the summary.

[0264] Input: Email body

[0265] Output: Summary

[0266] What it does: The server extracts the first 200 characters from the email body and generates a concise summary.

[0267] Step 5: Generate a summary

[0268] The server generates a summary by combining the category, number of senders, and summary text.

[0269] Input: Email category, number of recipients, summary

[0270] Output: Summary

[0271] Specific operation: The server integrates each piece of data and creates a text in the format of "Summary of this email."

[0272] Step 6: Inserting a summary

[0273] The server inserts the generated summary at the beginning of the email body.

[0274] Input: Email body, summary

[0275] Output: Email body with summary

[0276] Specific behavior: The server adds a summary in text format before the original email body.

[0277] Step 7: Return summary information

[0278] The server returns the email body with the summary to the terminal.

[0279] Input: Email body with summary

[0280] Output: Data sent to the terminal

[0281] Specific operation: The server sends the email body with the summary to the terminal as an HTTP response.

[0282] Step 8: Update the email body

[0283] The terminal updates the mail body based on the received summary information and generates a new mail body with the summary.

[0284] Input: Email body with summary

[0285] Output: Updated email body

[0286] Specific operation: The device creates a new email body based on the received data and completes preparations to send the email.

[0287] Step 9: Send email

[0288] Finally, the terminal sends the new mail body with the summary to the user's intended recipient.

[0289] Input: Updated email body, recipient information

[0290] Output: Email sent

[0291] Specific operation: The terminal uses the SMTP protocol to send an email with a summary to the specified recipient.

[0292] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0293] An embodiment of the present invention will be described. This embodiment provides a system that analyzes an email body, automatically determines its category, and further recognizes the user's emotions and reflects that information in a summary. This system acquires the number of recipients of the email, extracts the first part of the email body to generate a summary, inserts the generated summary at the beginning of the email body, and sends the email body with the summary. It can also analyze the user's emotions using an emotion engine, further subdivide the email category, and add emotional information to the summary.

[0294] Server-side processing

[0295] The server performs the following process each time a new email is sent:

[0296] 1. Email Analysis

[0297] The server analyzes the content of the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). Furthermore, it uses an emotion engine to extract the user's emotions (e.g., joy, anger, sadness, etc.) from the body of the email.

[0298] 2. Obtaining the number of senders

[0299] The server obtains the number of recipients listed in the To, CC, and BCC fields of the email and records this number as the number of recipients.

[0300] 3. Summary Generation

[0301] The server extracts the first 200 characters of the email body and sets it as a summary, which is used to succinctly express the important content of the email.

[0302] 4. Generating a summary

[0303] The server generates a "summary of this email" by combining the category based on the analysis results, the number of recipients, the summary text, and the emotional information extracted from the emotion engine.

[0304] Terminal side processing

[0305] The terminal performs the following process when the user sends an email.

[0306] 1. Email Request

[0307] When a user enters the email body on the email composition screen and presses the send button, the device sends an email analysis request to the server via the extension, which includes the email body, subject, and recipient information.

[0308] 2. Receiving a response from the server

[0309] The terminal receives summary information returned from the server, which includes the email category, the number of recipients, a summary, and the user's emotional information.

[0310] 3. Update the email body

[0311] The terminal adds the received summary information to the beginning of the mail body, and generates a new mail body with the summary.

[0312] 4. Send email

[0313] Finally, the terminal sends the new mail body with the summary to the user's intended recipient.

[0314] User operations

[0315] The user performs the following operations:

[0316] 1. Create an email

[0317] The user opens the email composition screen as usual and enters the recipient, subject, and body of the email.

[0318] 2. Send email

[0319] When the user presses the send button, a summary and emotional information are automatically generated and inserted at the beginning of the email body, after which the email is sent to the recipient.

[0320] Explanation with a concrete example

[0321] For example, suppose a user creates an email like this:

[0322] Subject: Regarding deadline extension

[0323] Thank you for your continued support. This is Suzuki from the company.

[0324] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0325] When this email is sent, the server analyzes the text and determines the category as "Contact," and uses the emotion engine to recognize the emotion as "Impatience." The server then obtains the number of recipients as 1. It generates a summary by extracting the first 200 characters and creates the following summary:

[0326] Summary of this email

[0327] Category: Contact

[0328] Number of senders: 1

[0329] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0330] Emotion: Impatience

[0331] This summary will be inserted at the beginning of the email body, and will look like this:

[0332] Summary of this email

[0333] Category: Contact

[0334] Number of senders: 1

[0335] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0336] Emotion: Impatience

[0337] Subject: Regarding deadline extension

[0338] Thank you for your continued support. This is Suzuki from the company.

[0339] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0340] Ultimately, users can send emails that are properly structured and contain emotional information without any special operations, making it easier for recipients to understand the content. In this way, the present invention provides a system that helps email recipients quickly assess the content and improves work efficiency.

[0341] The processing flow will be explained below.

[0342] Step 1:

[0343] The user opens the email creation screen and enters the recipient, subject, and body of the email. This is the normal email creation process.

[0344] Step 2:

[0345] The user clicks the "Send" button. At this moment, the device starts pre-processing for sending the email.

[0346] Step 3:

[0347] The terminal's extension function is launched and acquires the body, subject, and recipient information of the email currently being composed.

[0348] Step 4:

[0349] The terminal generates a request to send the acquired email body, subject, and destination information to the server. The request includes the email body text and destination information.

[0350] Step 5:

[0351] The server receives the request and begins parsing the email body.

[0352] Step 6:

[0353] The server analyzes the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). The category is determined, for example, as follows:

[0354] "if (emailBody.includes('Tasks')) { category = 'Tasks';}"

[0355] "else if (emailBody.includes('Contact')) { category = 'Contact';}"

[0356] "else { category = 'Other';}"

[0357] Step 7:

[0358] The server uses an emotion engine to recognize the user's emotions from the email body. For example, it uses natural language processing technology to analyze emotion-related words and context in the body of the email. The recognized emotions are specifically classified as "joy," "anger," "sadness," etc.

[0359] Step 8:

[0360] The server obtains the number of recipients based on the destination information, which can be easily obtained from the email header information.

[0361] Step 9:

[0362] The server extracts the first 200 characters of the email body and generates a summary that summarizes the important parts of the email body. For example, it is extracted as "let summaryText = emailBody.substring(0, 200);".

[0363] Step 10:

[0364] The server generates a summary by combining the category based on the analysis results, the number of senders, the summary text, and the emotion information extracted from the emotion engine. The generated summary has the following format:

[0365] "Summary of this email\nCategory: ${category}\nNumber of recipients: ${recipientCount}\nSummary: ${summaryText}\nEmotion: ${emotion}"

[0366] Step 11:

[0367] The server returns the generated summary to the terminal.

[0368] Step 12:

[0369] The terminal receives the response from the server and obtains the summary information.

[0370] Step 13:

[0371] The summary information received by the terminal is inserted at the beginning of the email body. The new email body will look like this:

[0372] "let updatedEmailBody = ${summary}\n\n${emailBody}"

[0373] Step 14:

[0374] The terminal generates a new email body with a summary and resumes the email sending process.

[0375] Step 15:

[0376] The device sends the updated email body to the recipient, and the email is sent.

[0377] Example 2

[0378] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0379] In recent years, the use of email has increased, and recipients are being asked to process large volumes of emails effectively. However, many emails are lengthy, making it difficult to grasp important information and understand the emotional nuances at a glance. Therefore, there is a need for a method that allows recipients to quickly understand the content of emails and respond appropriately. Conventional email systems do not adequately provide automatic functions for categorizing emails or determining their emotional content, and this lack is particularly evident in business situations.

[0380] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0381] In this invention, the server includes means for automatically determining the category and emotional information by analyzing the email body, means for acquiring the number of recipients of the email, means for extracting the first part of the email body to generate a summary, means for inserting the generated summary at the beginning of the email body, and means for sending the email body with the summary. This allows the content of the email to be presented in a concise and easy-to-understand format, enabling the recipient to quickly understand the main information and emotional nuances.

[0382] "Means for automatically determining category and emotion information by analyzing the body of an email" refers to a device or program that has the function of analyzing the content of an email and automatically identifying the category and emotion from the content using a text analysis engine or an emotion analysis engine.

[0383] The "means for acquiring the number of recipients of an e-mail" is a device or program that has the function of counting the number of recipients from an e-mail destination list and collecting that information.

[0384] The "means for extracting the first part of the email body and generating a summary" refers to a device or program that has the function of extracting a certain number of first characters from the email body and summarizing them as a concise summary.

[0385] The "means for inserting the generated summary at the beginning of the email body" refers to a device or program that has the function of adding the generated summary or analysis results to the beginning of the email body and creating an updated email body.

[0386] The "means for sending a mail body with a summary" is a device or program that has the function of sending an email containing an updated mail body to a specified recipient.

[0387] This section describes an embodiment of the present invention. This embodiment provides a system that analyzes the text of an email, automatically determines the category and emotional information, and generates an outline that reflects the results in a summary. This system is composed of a server and a terminal.

[0388] Each time an email is sent, the server performs the following process. First, the server analyzes the email body. Specifically, it uses a text analysis engine (e.g., Google Cloud Natural Language API) to analyze the body and determine the email category based on specific keywords and context. At the same time, it uses an emotion engine (e.g., IBM Watson®, Microsoft® Azure® Emotion API) to extract the user's emotional information (joy, anger, sadness, etc.) from the body of the email.

[0389] Next, the server extracts the number of recipients from the To, CC, and BCC fields of the email. This is recorded as the number of recipients of the email. The server then extracts the first 200 characters of the email body and uses this as a summary. This summary is used to concisely express the important content of the email.

[0390] The server then generates a summary based on the analysis results, combining the category, number of recipients, summary text, and sentiment information. This summary is saved as a "summary of this email."

[0391] When the user presses the send button, the terminal sends an email analysis request to the server. This request includes the email body, subject, and recipient information. After receiving a response from the server, the terminal adds the summary information to the beginning of the email body to generate a new email body with the summary. Finally, the terminal sends the email with the summary to the recipient specified by the user.

[0392] Users simply enter the recipient, subject, and message body on the email composition screen as usual and press the send button. This action sends a properly structured email that includes a summary and emotional information without requiring any special operations.

[0393] For example, if a user creates an email like this:

[0394] Subject: Regarding deadline extension

[0395] Thank you for your continued support. This is Suzuki from the company.

[0396] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0397] The server analyzes the text and determines the category as "Contact," and uses the emotion engine to identify the emotion as "Impatience." The server then obtains the number of recipients as 1. The server extracts the first 200 characters to generate a summary, creating the following:

[0398] Summary of this email

[0399] Category: Contact

[0400] Number of senders: 1

[0401] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0402] Emotion: Impatience

[0403] This summary will be inserted at the beginning of the email body, and will look like this:

[0404] Summary of this email

[0405] Category: Contact

[0406] Number of senders: 1

[0407] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0408] Emotion: Impatience

[0409] Subject: Regarding deadline extension

[0410] Thank you for your continued support. This is Suzuki from the company.

[0411] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0412] In this way, the present invention provides a system that helps the recipient of the mail to quickly judge the content and improves business efficiency.

[0413] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0414] Server-side processing

[0415] Step 1: Email Analysis

[0416] The server takes as input the body of the email the user is about to send. It uses a text analysis engine (e.g., Google Cloud Natural Language API) to analyze the body of the email and extract specific keywords and context. Based on this analysis, it determines the email category (e.g., "contact" or "task"). It also uses an emotion engine (e.g., IBM Watson or Microsoft Azure Emotion API) to extract the user's emotional information (e.g., joy, anger, sadness) from the body of the email. As a result of this data processing and calculation, it outputs category information and emotional information.

[0417] Step 2: Get the number of senders

[0418] The server takes the email's To, CC, and BCC fields as input. It counts the number of recipients from these fields and outputs that information as the number of recipients. This step simply counts the email addresses listed in each field.

[0419] Step 3: Generate a summary

[0420] The server takes the first part of the email body (e.g., the first 200 characters) as input. It extracts this part of the body and sets it as the summary. It outputs the extracted part as the summary.

[0421] Step 4: Generate a summary

[0422] The server inputs the category information, emotion information, number of recipients, and summary obtained in steps 1, 2, and 3. It combines these to generate and output a "summary of this email."

[0423] Terminal side processing

[0424] Step 1: Email Sending Request

[0425] The user enters the body, subject, and recipient information on the email creation screen and presses the send button. The terminal receives this information as input and sends it to the server as an email analysis request. Specifically, the terminal sends the body, subject, and recipient information of the email to the server.

[0426] Step 2: Receiving a response from the server

[0427] The terminal receives summary information returned from the server as input. This summary information includes category information, emotion information, the number of senders, and a summary. This information is then output as material for generating a new email body.

[0428] Step 3: Update the email body

[0429] The terminal takes the summary information received in step 2 and the original email body as input. It adds the summary information to the beginning of the email body to generate a new email body. This operation outputs the email body with the summary.

[0430] Step 4: Send email

[0431] The user sends the new email body with the summary to the intended recipient. This step involves sending the updated email body using the standard email sending process.

[0432] User operations

[0433] Step 1: Create an email

[0434] The user opens a mail composition screen as usual and enters the recipient, subject, and body of the message. This information becomes the input data for subsequent processing steps.

[0435] Step 2: Send an email

[0436] When the user presses the send button, the device automatically generates a summary and emotional information and inserts them at the beginning of the email body.The device then sends the email to the server.This operation ensures that the email, including the summary and emotional information, is delivered to the recipient.

[0437] Through the above processing steps, the present invention is a system that presents the contents of an email in a concise and easy-to-understand format, allowing the recipient to quickly understand the main information and emotional nuances.

[0438] (Application example 2)

[0439] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0440] In conventional email systems, it was difficult for recipients to quickly and accurately understand the contents of emails, increasing the likelihood of missing important information. Furthermore, because emails did not contain emotional information, it was difficult for recipients to understand the sender's intentions and emotions. Furthermore, there was a lack of effective ways to communicate promotional and campaign information to users in physical stores.

[0441] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically determining the category by analyzing the email body, means for acquiring the number of recipients of the email, means for extracting the first part of the email body and generating a summary, means for inserting the generated summary at the beginning of the email body, means for sending the email body with the summary, and means for recognizing the emotion of the email and reflecting that information in the summary. This allows the recipient to quickly and accurately understand the content of the email and the sender's intentions and emotions. It also makes it possible to effectively communicate information about promotions and campaigns at physical stores to users.

[0442] "Means for automatically determining the category by analyzing the body of the email" is a function that analyzes the content of the email and classifies the email into an appropriate category based on that content.

[0443] The "means for obtaining the number of recipients of an email" is a function for obtaining the number of recipients listed in the To, CC, and BCC fields of an email.

[0444] The "means for extracting the first part of the email body and generating a summary" is a function that extracts a certain portion of the first part of the email body and generates a short sentence based on that portion to express the summary of the email.

[0445] "Means for inserting the generated summary at the beginning of the email body" is a function for adding the generated summary text and category information to the beginning of the email body.

[0446] The "means for sending an email body with a summary" is a function for sending an email body with a summary attached to the recipient.

[0447] "Means of recognizing the emotion of an email and reflecting that information in the summary" is a function that analyzes the email body to recognize the emotion of the sender and adds that emotional information to the summary.

[0448] "Judgment based on specific keywords" is a method of classifying and evaluating emails based on specific keywords in the email body.

[0449] "Obtaining a positive or negative sentiment score" is a method of quantitatively evaluating the sentiment of the email body and scoring it as positive or negative.

[0450] System program generation

[0451] The server analyzes the email body and automatically determines the category. This analysis uses Natural Language Processing (NLP) technology, performing specific keyword analysis and sentiment analysis to obtain a positive or negative sentiment score. It also obtains the number of recipients of the email and extracts the first 200 characters of the email body to generate a summary.

[0452] Processing Description

[0453] The server-side program operates as follows:

[0454] Email Analysis

[0455] The server analyzes the body of the received email. The analysis uses Python NLP libraries (e.g., NLTK, TextBlob). This detects specific keywords in the email and automatically determines the category. TextBlob is also used to analyze the sentiment within the email and obtain a positive or negative sentiment score.

[0456] Get the number of senders

[0457] The server gets the number of recipients listed in the To, CC, and BCC fields of the email. This information is extracted from the send request.

[0458] Summary generation

[0459] The server extracts the first 200 characters of the email body and generates a summary based on that, which succinctly summarizes the email's key content.

[0460] Summary generation and insertion

[0461] The generated summary, category information, sentiment score, and number of recipients information are combined to generate a final summary, which is inserted at the beginning of the email body.

[0462] Send email

[0463] Send the email body with the final summary to the recipient.

[0464] Terminal side processing

[0465] When a user composes an email as usual and presses the send button, the program on the terminal sends an email analysis request to the server via the extension. The program receives the summary information returned from the server and inserts it at the beginning of the email body.

[0466] Specific examples

[0467] If a user composes an email like this:

[0468] Subject: Sale Announcement

[0469] Dear Customer,

[0470] This weekend, we're having a special sale in our store. Come and take advantage of 20% off all products. More details below...

[0471] The server analyzes the email body, determines the category as "Promotion", calculates the sentiment score as "Positive", and obtains the number of recipients as 1. It generates a summary by extracting the first 200 characters and generates the following:

[0472] Summary of this email

[0473] Category: Promotion

[0474] Number of senders: 1

[0475] Summary: Dear customers, we are holding a special sale in our store this weekend. Please come and take advantage of this opportunity to get 20% off all products. Further details are as follows...

[0476] Emotion: Positive

[0477] This summary will be inserted at the beginning of the email body and will look something like this:

[0478] Summary of this email

[0479] Category: Promotion

[0480] Number of senders: 1

[0481] Summary: Dear customers, we are holding a special sale in our store this weekend. Please come and take advantage of this opportunity to get 20% off all products. Further details are as follows...

[0482] Emotion: Positive

[0483] Subject: Sale Announcement

[0484] Dear Customer,

[0485] This weekend, we're having a special sale in our store. Come and take advantage of 20% off all products. More details below...

[0486] Example prompts to input to a generative AI model:

[0487] "Please analyze the content of this email, determine its category, recognize its sentiment, and create a summary."

[0488] Example of email content:

[0489] "Dear customers, we are having a special sale in our store this weekend. We are offering 20% ​​off all products, so please come and visit us. More details below..."

[0490] Hardware and software used

[0491] The hardware used is a smartphone, and the software uses Python, NLP libraries (NLTK, TextBlob), and smartphone application development frameworks (e.g., React Native, Swift, Kotlin).

[0492] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0493] Step 1:

[0494] The user creates an email. The recipient, subject, and body of the email are entered on the email creation screen. The input includes the email body and recipient information. When the user presses the send button, the device sends an email analysis request to the server.

[0495] Step 2:

[0496] The server receives an email analysis request, which includes the email body, subject, and recipient information. The server analyzes the content to identify email categories and sentiment. This process uses NLP libraries such as Python's NLTK or TextBlob to extract specific keywords and sentiment scores.

[0497] Input: Email body, subject, recipient information

[0498] Output: Email category, sentiment score

[0499] Step 3:

[0500] The server obtains the number of recipients of the email. It counts the number of recipients listed in the To, CC, and BCC fields. This generates the number of recipients information.

[0501] Input: To, CC, BCC information

[0502] Output: Number of recipients

[0503] Step 4:

[0504] The server extracts the first 200 characters of the email body and generates a summary based on them. This summary is generated to concisely express the important content of the email.

[0505] Input: Email body

[0506] Output: Summary

[0507] Step 5:

[0508] The server combines the email category, sentiment score, number of recipients, and the generated summary to generate a summary, which is then added to the beginning of the email body.

[0509] Input: Email category, sentiment score, number of recipients, summary

[0510] Output: Summary

[0511] Step 6:

[0512] The server inserts the generated summary at the beginning of the email body, thus creating a new email body with the summary.

[0513] Input: Summary, email body

[0514] Output: Email body with summary

[0515] Step 7:

[0516] The server sends the email body with the summary to the terminal. The terminal receives this information and displays the email in a format with the summary added to the beginning of the email body.

[0517] Input: Email body with summary

[0518] Output: Send to terminal

[0519] Step 8:

[0520] The terminal transmits the email body with the summary to the recipient, so that the recipient can receive the email with the summary.

[0521] Input: Email body with summary

[0522] Output: Send to recipient

[0523] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0524] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0525] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0526] [Second embodiment]

[0527] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0528] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0529] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0530] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0531] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0532] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0533] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0534] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0535] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[0536] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0537] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0538] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0539] An embodiment of the present invention will be described below, which concerns a system that analyzes the body of an email, automatically determines the category, acquires the number of recipients, extracts the first part of the email body, generates a summary, generates a summary based on this information, and sends the email body with the summary inserted at the beginning of the email body.

[0540] Server-side processing

[0541] The server performs the following process each time a new email is sent:

[0542] 1. Email Analysis

[0543] The server analyzes the content of the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). This analysis process may use natural language processing (NLP) technology.

[0544] 2. Obtaining the number of senders

[0545] The server obtains the number of recipients listed in the To, CC, and BCC fields of the email and records this number as the number of recipients.

[0546] 3. Summary Generation

[0547] The server extracts the first 200 characters of the email body and sets it as a summary, which is used to succinctly express the important content of the email.

[0548] 4. Generating a summary

[0549] The server generates a "summary of this email" by combining the category, number of recipients, and summary text based on the analysis results.

[0550] Terminal side processing

[0551] The terminal performs the following process when the user sends an email.

[0552] 1. Email Request

[0553] When a user enters the email body on the email composition screen and presses the send button, the device sends an email analysis request to the server via the extension, which includes the email body, subject, and recipient information.

[0554] 2. Receiving a response from the server

[0555] The terminal receives summary information returned from the server, which includes the email category, the number of senders, and a summary.

[0556] 3. Update the email body

[0557] The terminal adds the received summary information to the beginning of the mail body, and generates a new mail body with the summary.

[0558] 4. Send email

[0559] Finally, the terminal sends the new mail body with the summary to the user's intended recipient.

[0560] User operations

[0561] The user performs the following operations:

[0562] 1. Create an email

[0563] The user opens the Gmail email composition screen as usual and enters the recipient, subject, and body of the email.

[0564] 2. Send email

[0565] When the user hits the send button, a summary is automatically generated and inserted at the beginning of the email body, after which the email is sent to its destination.

[0566] Explanation with a concrete example

[0567] For example, suppose a user creates an email like this:

[0568] Subject: Regarding deadline extension

[0569] Thank you for your continued support. This is Suzuki from the company.

[0570] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0571] When this email is sent, the server analyzes the text, determines the category as "Contact," and gets the number of recipients as 1. It generates a summary by extracting the first 200 characters and creates the following summary:

[0572] Summary of this email

[0573] Category: Contact

[0574] Number of senders: 1

[0575] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0576] This summary will be inserted at the beginning of the email body, and will look like this:

[0577] Summary of this email

[0578] Category: Contact

[0579] Number of senders: 1

[0580] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0581] Subject: Regarding deadline extension

[0582] Thank you for your continued support. This is Suzuki from the company.

[0583] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0584] Finally, the user can send a properly structured email without any special operations, making it easier for the recipient to understand the content. In this way, the present invention provides a system that helps the recipient of the email quickly understand the content and improves work efficiency.

[0585] The processing flow will be explained below.

[0586] Step 1:

[0587] The user opens the email composition screen, enters the recipient, subject, and body of the email, and performs the usual email composition operation.

[0588] Step 2:

[0589] The user clicks the "Send" button. At this moment, the device starts pre-processing for sending the email.

[0590] Step 3:

[0591] The terminal's extension function is launched and acquires the body, subject, and recipient information of the email currently being composed.

[0592] Step 4:

[0593] The terminal generates a request to send the acquired email body, subject, and destination information to the server. The request includes the email body text and destination information.

[0594] Step 5:

[0595] The server receives the request and begins parsing the email body.

[0596] Step 6:

[0597] The server analyzes the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). The category is determined, for example, as follows:

[0598] "if (emailBody.includes('Tasks')) { category = 'Tasks';}"

[0599] "else if (emailBody.includes('Contact')) { category = 'Contact';}"

[0600] "else { category = 'Other';}"

[0601] Step 7:

[0602] The server obtains the number of recipients based on the destination information, which can be easily obtained from the email header information.

[0603] Step 8:

[0604] The server extracts the first 200 characters of the email body and generates a summary that summarizes the important parts of the email body. For example, it is extracted as "let summaryText = emailBody.substring(0, 200);".

[0605] Step 9:

[0606] The server generates a summary by combining the category, the number of recipients, and the summary text. The generated summary will have the following format:

[0607] "Summary of this email\nCategory: ${category}\nNumber of recipients: ${recipientCount}\nSummary: ${summaryText}"

[0608] Step 10:

[0609] The server returns the generated summary to the terminal.

[0610] Step 11:

[0611] The terminal receives the response from the server and obtains the summary information.

[0612] Step 12:

[0613] The summary information received by the terminal is inserted at the beginning of the email body. The new email body will look like this:

[0614] "let updatedEmailBody = ${summary}\n\n${emailBody}"

[0615] Step 13:

[0616] The terminal generates a new email body with a summary and resumes the email sending process.

[0617] Step 14:

[0618] The device sends the updated email body to the recipient, and the email is sent.

[0619] Example 1

[0620] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0621] Efficient communication via e-mail is important in many business processes. However, when the body of an e-mail is lengthy, it is difficult for the recipient to quickly grasp the important information. This results in reduced work efficiency and slower decision-making. Furthermore, if the e-mail category is not properly determined, it can be difficult to organize and search for information. Furthermore, the number of e-mail recipients is also important information, and not knowing this information makes it difficult to respond appropriately.

[0622] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0623] In this invention, the server includes means for automatically analyzing the email body to determine its category, means for acquiring the number of recipients of the email, means for extracting the first part of the email body to generate a summary, means for inserting the generated summary at the beginning of the email body, means for transmitting the email body with the summary, means for determining the category based on keywords using natural language processing technology, means for sending an email analysis request to the server, and means for receiving summary information from the server and updating the email body. This allows email recipients to quickly grasp important information and take appropriate action. Automating email category determination and recording the number of recipients facilitates information organization and search, improving business efficiency.

[0624] "Means for automatically determining the category by analyzing the body of an email" refers to technology that analyzes the content of an email and automatically identifies the type and purpose of the email based on specific keywords and patterns.

[0625] "Means for obtaining the number of recipients of an email" refers to a method for calculating the total number of recipients from the destination information of an email and recording that information.

[0626] "Means for extracting the first part of the email body and generating a summary" refers to a technology that extracts text within a specified number of characters from the email body and uses that text as the summary of the email.

[0627] "Means for inserting the generated summary at the beginning of the email body" refers to a technology or method for adding the generated summary to the beginning of the original email content.

[0628] "Means for sending an email body with a summary" refers to a technique for delivering an email to a designated recipient after a summary has been added.

[0629] "Means for determining categories based on keywords using natural language processing technology" refers to a method of using natural language processing (NLP) algorithms to extract important keywords from the text in an email and determine the type of email based on that.

[0630] "Means for sending an email analysis request to a server" refers to a technology for sending the email body and related information to a server in order to analyze the content of an email created by a user.

[0631] "Means for receiving summary information from a server and updating the email body" refers to a technology or method for receiving summary information returned from a server and using it to update the original email content.

[0632] An embodiment of the present invention will be described below. This invention provides a system that analyzes the body of an email, automatically determines the category, obtains the number of recipients, generates an outline of the email body, creates a summary, and inserts it at the beginning of the email. This system enables email recipients to quickly grasp information and improve work efficiency.

[0633] Server-side processing

[0634] The server processes each email sent using Python software, with natural language processing (NLP) techniques such as NLTK and spaCy used for automated email analysis.

[0635] 1. Email analysis: The server analyzes the body of the received email and determines the category based on specific keywords. For example, emails containing keywords such as "contact" or "task" are classified into specific categories.

[0636] 2. Get the number of recipients: The server gets the number of recipients in the To, CC, and BCC fields of the email using Python's built-in library.

[0637] 3. Summary generation: The server extracts the first 200 characters of the email body and sets them as a summary, which succinctly expresses the important content of the email.

[0638] 4. Summary generation: The server generates a summary by combining the analyzed categories, the number of senders, and a summary. This summary is inserted at the beginning of the email.

[0639] Terminal side processing

[0640] The device primarily handles the process of sending emails, and the device extension uses JavaScript and the Gmail API.

[0641] 1. Email sending request: When a user presses the send button on the email composition screen, the device sends an email analysis request to the server. This request includes the email body, subject, and recipient information.

[0642] 2. Receiving a response from the server: The terminal receives summary information returned from the server, which includes the email category, the number of senders, and a summary.

[0643] 3. Update the email body: The terminal adds the summary information to the beginning of the email body and generates a new email body with the summary.

[0644] 4. Send email: The device finally sends the updated email body to the specified recipient.

[0645] User operations

[0646] The user opens an email creation screen such as Gmail as usual, enters the recipient, subject, and body of the email, and when they press the send button, the email is automatically analyzed and a summary is generated and inserted.

[0647] Specific examples

[0648] For example, consider the case where a user creates an email with the following content:

[0649] Subject: Regarding deadline extension

[0650] Thank you for your continued support. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0651] The server analyzes this email, determines that it is in the "Contact" category, and sets the number of recipients to 1. It extracts the first 200 characters of the email body and generates the following summary:

[0652] Summary of this email

[0653] Category: Contact

[0654] Number of senders: 1

[0655] Summary: Thank you for your continued support. I would like to extend the deadline for this project due to the following reasons...

[0656] This summary is inserted at the beginning of the email body and is finally sent to the recipient.

[0657] Prompt Sentence Examples

[0658] """A new email has been created. Please parse the body of the email below to generate a category and summary."""

[0659] This system allows users to quickly convey important information to recipients without performing any special operations, improving work efficiency and enabling faster decision-making.

[0660] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0661] Server-side processing

[0662] Step 1: Email Analysis

[0663] The server analyzes the body of each new email sent. It receives the body of the email to be sent as input and uses natural language processing (NLP) techniques to extract specific keywords. For example, it extracts keywords such as "project" and "contact," and automatically classifies the email as a "business contact" based on these keywords. This is done using Python and NLP libraries such as NLTK and spaCy.

[0664] Input: Email body

[0665] Output: Email category (e.g. "Business Notice")

[0666] Specific operation: The server runs a Python script to extract keywords from the email body and determine the category.

[0667] Step 2: Get the number of senders

[0668] The server obtains the number of recipients listed in the To, CC, and BCC fields of the email. It receives the email header information as input and calculates the number of recipients using Python's built-in library. For example, if there are three To, two CC, and one BCC recipients, the server obtains a total of six recipients.

[0669] Input: Email header information

[0670] Output: Number of recipients (e.g. 6)

[0671] Specific operation: The server analyzes the header information of the received email and compiles a list of recipients.

[0672] Step 3: Generate a summary

[0673] The server extracts the first 200 characters of the email body and sets it as a summary. It receives the email body as input and performs string manipulation to extract the first 200 characters. This generates a summary that succinctly conveys the important content of the email.

[0674] Input: Email body

[0675] Output: Summary (e.g. "Thank you for your continued support. The deadline for this project is...")

[0676] Specific operation: The server uses a Python script to extract the first 200 characters of the email body and generate a summary.

[0677] Step 4: Generate a summary

[0678] The server generates a summary by combining the category based on the analysis results, the number of senders, and the summary. As input, it receives the determined category, the number of senders, and the generated summary, and inserts these into a standard format to generate the summary.

[0679] Input: Category, number of recipients, summary

[0680] Output: Summary (Example: "Summary of this email\nCategory: Business communication\nNumber of recipients: 6\nSummary: Thank you for your continued support...")

[0681] What it does: The server runs a Python script that generates a summary by inserting the category, number of senders, and summary text into a format.

[0682] Terminal side processing

[0683] Step 1: Email Sending Request

[0684] When a user enters the email body on the email composition screen and presses the send button, the device sends an email analysis request to the server. The device takes the email body, subject, and recipient information entered by the user as input, generates an HTTP request using JavaScript and the Gmail API, and sends it to the server.

[0685] Input: Email body, subject, recipient information

[0686] Output: Sending an email parsing request

[0687] Specific operation: The device executes JavaScript and sends the email information to the server as an HTTP request.

[0688] Step 2: Receiving a response from the server

[0689] The terminal receives the summary information returned from the server. As input, it receives the HTTP response from the server and parses it using JavaScript. The summary information includes the email category, the number of senders, and a summary.

[0690] Input: HTTP response from the server

[0691] Output: Receive summary information

[0692] Specific operation: The terminal receives the HTTP response and extracts summary information using JavaScript.

[0693] Step 3: Update the email body

[0694] The terminal adds the summary information to the beginning of the email body and generates a new email body. As input, it receives the received summary information and the original email body, performs string manipulation, and adds the summary to the beginning.

[0695] Input: Summary information, original email body

[0696] Output: New email body

[0697] Specific operation: The device uses JavaScript to add summary information to the beginning of the original email body.

[0698] Step 4: Send email

[0699] The terminal finally sends the new email body with the summary to the specified recipient. As input, it takes the new email body and email destination information and sends it using the Gmail API.

[0700] Input: New email body, email recipient information

[0701] Output: Send email

[0702] Specific operation: The device uses the Gmail API to send the new email body to the recipient.

[0703] User operations

[0704] Step 1: Create an email

[0705] The user opens the email creation screen as usual and enters the recipient, subject, and body of the email. The terminal receives the email creation information manually entered by the user as input and manages it.

[0706] Input: User email creation information

[0707] Output: Save email information

[0708] Specific operation: The user enters email information using an email composition screen such as Gmail.

[0709] (Application example 1)

[0710] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0711] When an email contains a large amount of information, it is difficult for the recipient to quickly understand the content. Furthermore, as the number of customer response emails and notifications increases in virtual stores, there is a need for a method to efficiently manage these emails and quickly convey important information to recipients. To solve this problem, it is necessary to automate email analysis and automatically generate summaries using a generative AI model. Furthermore, when generating summaries, a function is also needed to automatically insert the generated summaries into the email body.

[0712] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0713] In this invention, the server includes means for analyzing the email body and automatically determining the category, means for acquiring the number of recipients of the email, means for extracting the first part of the email body and generating a summary, means for inserting the generated summary at the beginning of the email body, means for sending the email body with the summary, means for analyzing emails and notifications for customer service in the virtual store and generating summaries, and means for using a generation AI model and prompt text when generating summaries. This enables efficient management of emails and notifications for customer service in the virtual store and enables recipients to quickly grasp important information.

[0714] "Means for automatically determining the category by analyzing the body of the email" is a function that interprets the content of the email and automatically identifies its category based on specific keywords or patterns.

[0715] "Means for obtaining the number of recipients of an email" is a function that automatically calculates and obtains the number of recipients listed in the To, CC, and BCC fields of an email.

[0716] The "means for extracting the first part of the email body and generating a summary" is a function that extracts a certain portion of the first part of the email body and uses that portion to generate a summary as a short sentence.

[0717] The "means for inserting the generated summary at the beginning of the email body" is a function for adding an automatically generated summary to the beginning of the email body and inserting it at the beginning of the email body.

[0718] The "means for sending the email body with the summary" is a function for finally sending the improved email with the summary inserted to the specified recipient.

[0719] "Means for analyzing emails and notifications related to customer service in a virtual store and generating summaries" is a function that analyzes emails and notifications related to the operation of a virtual store and automatically generates summaries that summarize their contents in a concise and easy-to-understand format.

[0720] "Means for using a generative AI model and prompt sentences when generating summaries" refers to a function that utilizes a generative AI model when generating summaries and performs effective natural language generation using optimal prompt sentences.

[0721] MODE FOR CARRYING OUT THE INVENTION

[0722] overview

[0723] This invention provides a system for efficiently and quickly processing customer correspondence emails and notifications in a virtual store. In particular, the system analyzes the text of the email, automatically classifies it into an appropriate category, generates a summary, and inserts the generated summary at the beginning of the email text before sending it, allowing the recipient to quickly grasp important information.

[0724] Server-side processing

[0725] Each time a new email is sent, the server performs the following process. First, the server analyzes the email body and automatically assigns it to a specified category. This process is performed using natural language processing (NLP) technology, based on specific keywords and phrases. Next, the server obtains the number of recipients from the email's recipient list and records that number. After that, it extracts the first part of the email body (for example, the first 200 characters) and sets it as the summary. Finally, it combines the category, number of recipients, and summary to generate a summary, which is then inserted at the beginning of the email body.

[0726] Terminal side processing

[0727] When a user sends an email, the device first sends an email sending request to the server. This request includes the email body, subject, and recipient information. The server receives the request, performs the server-side processing described above to generate a summary, and returns it to the device. The device then adds the received summary information to the beginning of the email body to generate a new email body with the summary. When the user finally presses the send button, the device sends the email body with the summary to the specified recipient.

[0728] Program processing

[0729] This system is implemented using a Python program. Specifically, it uses a natural language processing library (e.g., scikit-learn) to analyze the email body and determine the category. It also uses a generative AI model to generate summaries and efficiently generate natural language using optimal prompts. The SMTP protocol is used to send emails, utilizing the Python smtplib library.

[0730] Hardware / Software used

[0731] Hardware: Standard servers or cloud-based servers (e.g., AWS or Google Cloud)

[0732] Software: Python, natural language processing library (scikit-learn), SMTP library (smtplib)

[0733] Specific examples

[0734] For example, if the support team for a hypothetical store, "XYZ Store," sends an email with the following content:

[0735] text

[0736] Subject: Enquiry about new features in XYZ Store

[0737] Body: Thank you for your support. This is customer support from XYZ Store. We'll respond to your inquiry about new features shortly...

[0738] The system automatically inserts the following summary:

[0739] text

[0740] Summary of this email

[0741] Category: Inquiry

[0742] Number of senders: 1

[0743] Summary: Hello, this is customer support for XYZ Store. We'll get back to you shortly with any questions you may have about new features...

[0744] Prompt Sentence Examples

[0745] An example prompt for a generative AI model is:

[0746] text

[0747] Analyze the content of the email below and generate the category, number of recipients, and summary.

[0748] ---

[0749] Subject: {subject}

[0750] Body: {body}

[0751] This system streamlines customer-facing emails and notifications in virtual stores, allowing recipients to quickly grasp important information.

[0752] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0753] Program processing steps

[0754] Step 1: Email Sending Request

[0755] When the user enters the email body on the email creation screen and presses the send button, the device sends a send request including the email body, subject, and recipient information to the server.

[0756] Input: Email body, subject, recipient information

[0757] Output: Email parsing request to the server

[0758] Specific operation: When the user completes the input and presses the send button, the terminal compiles this data and sends it to the server as an HTTP request.

[0759] Step 2: Email Analysis

[0760] The server analyzes the body of the received email and automatically determines the category based on specific keywords and phrases, using natural language processing technology.

[0761] Input: Email body

[0762] Output: Email Category

[0763] Specific operation: The server analyzes the email body using a natural language processing model (such as scikit-learn) and determines the category based on the frequency of word occurrence and context.

[0764] Step 3: Get the number of senders

[0765] The server obtains the number of recipients from the email address list and records that number.

[0766] Input: To information, CC information, BCC information

[0767] Output: Number of recipients

[0768] Specific operation: The server analyzes the recipient list, totals the number of email addresses contained in each list, and obtains the number of recipients.

[0769] Step 4: Generate a summary

[0770] The server extracts the first 200 characters of the email body and sets them as the summary.

[0771] Input: Email body

[0772] Output: Summary

[0773] What it does: The server extracts the first 200 characters from the email body and generates a concise summary.

[0774] Step 5: Generate a summary

[0775] The server generates a summary by combining the category, number of senders, and summary text.

[0776] Input: Email category, number of recipients, summary

[0777] Output: Summary

[0778] Specific operation: The server integrates each piece of data and creates a text in the format of "Summary of this email."

[0779] Step 6: Inserting a summary

[0780] The server inserts the generated summary at the beginning of the email body.

[0781] Input: Email body, summary

[0782] Output: Email body with summary

[0783] Specific behavior: The server adds a summary in text format before the original email body.

[0784] Step 7: Return summary information

[0785] The server returns the email body with the summary to the terminal.

[0786] Input: Email body with summary

[0787] Output: Data sent to the terminal

[0788] Specific operation: The server sends the email body with the summary to the terminal as an HTTP response.

[0789] Step 8: Update the email body

[0790] The terminal updates the mail body based on the received summary information and generates a new mail body with the summary.

[0791] Input: Email body with summary

[0792] Output: Updated email body

[0793] Specific operation: The device creates a new email body based on the received data and completes preparations to send the email.

[0794] Step 9: Send email

[0795] Finally, the terminal sends the new mail body with the summary to the user's intended recipient.

[0796] Input: Updated email body, recipient information

[0797] Output: Email sent

[0798] Specific operation: The terminal uses the SMTP protocol to send an email with a summary to the specified recipient.

[0799] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0800] An embodiment of the present invention will be described. This embodiment provides a system that analyzes an email body, automatically determines its category, and further recognizes the user's emotions and reflects that information in a summary. This system acquires the number of recipients of the email, extracts the first part of the email body to generate a summary, inserts the generated summary at the beginning of the email body, and sends the email body with the summary. It can also analyze the user's emotions using an emotion engine, further subdivide the email category, and add emotional information to the summary.

[0801] Server-side processing

[0802] The server performs the following process each time a new email is sent:

[0803] 1. Email Analysis

[0804] The server analyzes the content of the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). Furthermore, it uses an emotion engine to extract the user's emotions (e.g., joy, anger, sadness, etc.) from the body of the email.

[0805] 2. Obtaining the number of senders

[0806] The server obtains the number of recipients listed in the To, CC, and BCC fields of the email and records this number as the number of recipients.

[0807] 3. Summary Generation

[0808] The server extracts the first 200 characters of the email body and sets it as a summary, which is used to succinctly express the important content of the email.

[0809] 4. Generating a summary

[0810] The server generates a "summary of this email" by combining the category based on the analysis results, the number of recipients, the summary text, and the emotional information extracted from the emotion engine.

[0811] Terminal side processing

[0812] The terminal performs the following process when the user sends an email.

[0813] 1. Email Request

[0814] When a user enters the email body on the email composition screen and presses the send button, the device sends an email analysis request to the server via the extension, which includes the email body, subject, and recipient information.

[0815] 2. Receiving a response from the server

[0816] The terminal receives summary information returned from the server, which includes the email category, the number of recipients, a summary, and the user's emotional information.

[0817] 3. Update the email body

[0818] The terminal adds the received summary information to the beginning of the mail body, and generates a new mail body with the summary.

[0819] 4. Send email

[0820] Finally, the terminal sends the new mail body with the summary to the user's intended recipient.

[0821] User operations

[0822] The user performs the following operations:

[0823] 1. Create an email

[0824] The user opens the email composition screen as usual and enters the recipient, subject, and body of the email.

[0825] 2. Send email

[0826] When the user presses the send button, a summary and emotional information are automatically generated and inserted at the beginning of the email body, after which the email is sent to the recipient.

[0827] Explanation with a concrete example

[0828] For example, suppose a user creates an email like this:

[0829] Subject: Regarding deadline extension

[0830] Thank you for your continued support. This is Suzuki from the company.

[0831] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0832] When this email is sent, the server analyzes the text and determines the category as "Contact," and uses the emotion engine to recognize the emotion as "Impatience." The server then obtains the number of recipients as 1. It generates a summary by extracting the first 200 characters and creates the following summary:

[0833] Summary of this email

[0834] Category: Contact

[0835] Number of senders: 1

[0836] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0837] Emotion: Impatience

[0838] This summary will be inserted at the beginning of the email body, and will look like this:

[0839] Summary of this email

[0840] Category: Contact

[0841] Number of senders: 1

[0842] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0843] Emotion: Impatience

[0844] Subject: Regarding deadline extension

[0845] Thank you for your continued support. This is Suzuki from the company.

[0846] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0847] Ultimately, users can send emails that are properly structured and contain emotional information without any special operations, making it easier for recipients to understand the content. In this way, the present invention provides a system that helps email recipients quickly assess the content and improves work efficiency.

[0848] The processing flow will be explained below.

[0849] Step 1:

[0850] The user opens the email creation screen and enters the recipient, subject, and body of the email. This is the normal email creation process.

[0851] Step 2:

[0852] The user clicks the "Send" button. At this moment, the device starts pre-processing for sending the email.

[0853] Step 3:

[0854] The terminal's extension function is launched and acquires the body, subject, and recipient information of the email currently being composed.

[0855] Step 4:

[0856] The terminal generates a request to send the acquired email body, subject, and destination information to the server. The request includes the email body text and destination information.

[0857] Step 5:

[0858] The server receives the request and begins parsing the email body.

[0859] Step 6:

[0860] The server analyzes the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). The category is determined, for example, as follows:

[0861] "if (emailBody.includes('Tasks')) { category = 'Tasks';}"

[0862] "else if (emailBody.includes('Contact')) { category = 'Contact';}"

[0863] "else { category = 'Other';}"

[0864] Step 7:

[0865] The server uses an emotion engine to recognize the user's emotions from the email body. For example, it uses natural language processing technology to analyze emotion-related words and context in the body of the email. The recognized emotions are specifically classified as "joy," "anger," "sadness," etc.

[0866] Step 8:

[0867] The server obtains the number of recipients based on the destination information, which can be easily obtained from the email header information.

[0868] Step 9:

[0869] The server extracts the first 200 characters of the email body and generates a summary that summarizes the important parts of the email body. For example, it is extracted as "let summaryText = emailBody.substring(0, 200);".

[0870] Step 10:

[0871] The server generates a summary by combining the category based on the analysis results, the number of senders, the summary text, and the emotion information extracted from the emotion engine. The generated summary has the following format:

[0872] "Summary of this email\nCategory: ${category}\nNumber of recipients: ${recipientCount}\nSummary: ${summaryText}\nEmotion: ${emotion}"

[0873] Step 11:

[0874] The server returns the generated summary to the terminal.

[0875] Step 12:

[0876] The terminal receives the response from the server and obtains the summary information.

[0877] Step 13:

[0878] The summary information received by the terminal is inserted at the beginning of the email body. The new email body will look like this:

[0879] "let updatedEmailBody = ${summary}\n\n${emailBody}"

[0880] Step 14:

[0881] The terminal generates a new email body with a summary and resumes the email sending process.

[0882] Step 15:

[0883] The device sends the updated email body to the recipient, and the email is sent.

[0884] Example 2

[0885] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0886] In recent years, the use of email has increased, and recipients are being asked to process large volumes of emails effectively. However, many emails are lengthy, making it difficult to grasp important information and understand the emotional nuances at a glance. Therefore, there is a need for a method that allows recipients to quickly understand the content of emails and respond appropriately. Conventional email systems do not adequately provide automatic functions for categorizing emails or determining their emotional content, and this lack is particularly evident in business situations.

[0887] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0888] In this invention, the server includes means for automatically determining the category and emotional information by analyzing the email body, means for acquiring the number of recipients of the email, means for extracting the first part of the email body to generate a summary, means for inserting the generated summary at the beginning of the email body, and means for sending the email body with the summary. This allows the content of the email to be presented in a concise and easy-to-understand format, enabling the recipient to quickly understand the main information and emotional nuances.

[0889] "Means for automatically determining category and emotion information by analyzing the body of an email" refers to a device or program that has the function of analyzing the content of an email and automatically identifying the category and emotion from the content using a text analysis engine or an emotion analysis engine.

[0890] The "means for acquiring the number of recipients of an e-mail" is a device or program that has the function of counting the number of recipients from an e-mail destination list and collecting that information.

[0891] The "means for extracting the first part of the email body and generating a summary" refers to a device or program that has the function of extracting a certain number of first characters from the email body and summarizing them as a concise summary.

[0892] The "means for inserting the generated summary at the beginning of the email body" refers to a device or program that has the function of adding the generated summary or analysis results to the beginning of the email body and creating an updated email body.

[0893] The "means for sending a mail body with a summary" is a device or program that has the function of sending an email containing an updated mail body to a specified recipient.

[0894] This section describes an embodiment of the present invention. This embodiment provides a system that analyzes the text of an email, automatically determines the category and emotional information, and generates an outline that reflects the results in a summary. This system is composed of a server and a terminal.

[0895] Each time an email is sent, the server performs the following process. First, the server analyzes the email body. Specifically, it uses a text analysis engine (e.g., Google Cloud Natural Language API) to analyze the body and determine the email category based on specific keywords and context. At the same time, it uses an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) to extract the user's emotional information (joy, anger, sadness, etc.) from the body of the email.

[0896] Next, the server extracts the number of recipients from the To, CC, and BCC fields of the email. This is recorded as the number of recipients of the email. The server then extracts the first 200 characters of the email body and uses this as a summary. This summary is used to concisely express the important content of the email.

[0897] The server then generates a summary based on the analysis results, combining the category, number of recipients, summary text, and sentiment information. This summary is saved as a "summary of this email."

[0898] When the user presses the send button, the terminal sends an email analysis request to the server. This request includes the email body, subject, and recipient information. After receiving a response from the server, the terminal adds the summary information to the beginning of the email body to generate a new email body with the summary. Finally, the terminal sends the email with the summary to the recipient specified by the user.

[0899] Users simply enter the recipient, subject, and message body on the email composition screen as usual and press the send button. This action sends a properly structured email that includes a summary and emotional information without requiring any special operations.

[0900] For example, if a user creates an email like this:

[0901] Subject: Regarding deadline extension

[0902] Thank you for your continued support. This is Suzuki from the company.

[0903] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0904] The server analyzes the text and determines the category as "Contact," and uses the emotion engine to identify the emotion as "Impatience." The server then obtains the number of recipients as 1. The server extracts the first 200 characters to generate a summary, creating the following:

[0905] Summary of this email

[0906] Category: Contact

[0907] Number of senders: 1

[0908] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0909] Emotion: Impatience

[0910] This summary will be inserted at the beginning of the email body, and will look like this:

[0911] Summary of this email

[0912] Category: Contact

[0913] Number of senders: 1

[0914] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0915] Emotion: Impatience

[0916] Subject: Regarding deadline extension

[0917] Thank you for your continued support. This is Suzuki from the company.

[0918] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[0919] In this way, the present invention provides a system that helps the recipient of the mail to quickly judge the content and improves business efficiency.

[0920] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0921] Server-side processing

[0922] Step 1: Email Analysis

[0923] The server takes as input the body of the email the user is about to send. It uses a text analysis engine (e.g., Google Cloud Natural Language API) to analyze the body of the email and extract specific keywords and context. Based on this analysis, it determines the email category (e.g., "contact" or "task"). It also uses an emotion engine (e.g., IBM Watson or Microsoft Azure Emotion API) to extract the user's emotional information (e.g., joy, anger, sadness) from the body of the email. As a result of this data processing and calculation, it outputs category information and emotional information.

[0924] Step 2: Get the number of senders

[0925] The server takes the email's To, CC, and BCC fields as input. It counts the number of recipients from these fields and outputs that information as the number of recipients. This step simply counts the email addresses listed in each field.

[0926] Step 3: Generate a summary

[0927] The server takes the first part of the email body (e.g., the first 200 characters) as input. It extracts this part of the body and sets it as the summary. It outputs the extracted part as the summary.

[0928] Step 4: Generate a summary

[0929] The server inputs the category information, emotion information, number of recipients, and summary obtained in steps 1, 2, and 3. It combines these to generate and output a "summary of this email."

[0930] Terminal side processing

[0931] Step 1: Email Sending Request

[0932] The user enters the body, subject, and recipient information on the email creation screen and presses the send button. The terminal receives this information as input and sends it to the server as an email analysis request. Specifically, the terminal sends the body, subject, and recipient information of the email to the server.

[0933] Step 2: Receiving a response from the server

[0934] The terminal receives summary information returned from the server as input. This summary information includes category information, emotion information, the number of senders, and a summary. This information is then output as material for generating a new email body.

[0935] Step 3: Update the email body

[0936] The terminal takes the summary information received in step 2 and the original email body as input. It adds the summary information to the beginning of the email body to generate a new email body. This operation outputs the email body with the summary.

[0937] Step 4: Send email

[0938] The user sends the new email body with the summary to the intended recipient. This step involves sending the updated email body using the standard email sending process.

[0939] User operations

[0940] Step 1: Create an email

[0941] The user opens a mail composition screen as usual and enters the recipient, subject, and body of the message. This information becomes the input data for subsequent processing steps.

[0942] Step 2: Send an email

[0943] When the user presses the send button, the device automatically generates a summary and emotional information and inserts them at the beginning of the email body.The device then sends the email to the server.This operation ensures that the email, including the summary and emotional information, is delivered to the recipient.

[0944] Through the above processing steps, the present invention is a system that presents the contents of an email in a concise and easy-to-understand format, allowing the recipient to quickly understand the main information and emotional nuances.

[0945] (Application example 2)

[0946] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0947] In conventional email systems, it was difficult for recipients to quickly and accurately understand the contents of emails, increasing the likelihood of missing important information. Furthermore, because emails did not contain emotional information, it was difficult for recipients to understand the sender's intentions and emotions. Furthermore, there was a lack of effective ways to communicate promotional and campaign information to users in physical stores.

[0948] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically determining the category by analyzing the email body, means for acquiring the number of recipients of the email, means for extracting the first part of the email body and generating a summary, means for inserting the generated summary at the beginning of the email body, means for sending the email body with the summary, and means for recognizing the emotion of the email and reflecting that information in the summary. This allows the recipient to quickly and accurately understand the content of the email and the sender's intentions and emotions. It also makes it possible to effectively communicate information about promotions and campaigns at physical stores to users.

[0949] "Means for automatically determining the category by analyzing the body of the email" is a function that analyzes the content of the email and classifies the email into an appropriate category based on that content.

[0950] The "means for obtaining the number of recipients of an email" is a function for obtaining the number of recipients listed in the To, CC, and BCC fields of an email.

[0951] The "means for extracting the first part of the email body and generating a summary" is a function that extracts a certain portion of the first part of the email body and generates a short sentence based on that portion to express the summary of the email.

[0952] "Means for inserting the generated summary at the beginning of the email body" is a function for adding the generated summary text and category information to the beginning of the email body.

[0953] The "means for sending an email body with a summary" is a function for sending an email body with a summary attached to the recipient.

[0954] "Means of recognizing the emotion of an email and reflecting that information in the summary" is a function that analyzes the email body to recognize the emotion of the sender and adds that emotional information to the summary.

[0955] "Judgment based on specific keywords" is a method of classifying and evaluating emails based on specific keywords in the email body.

[0956] "Obtaining a positive or negative sentiment score" is a method of quantitatively evaluating the sentiment of the email body and scoring it as positive or negative.

[0957] System program generation

[0958] The server analyzes the email body and automatically determines the category. This analysis uses Natural Language Processing (NLP) technology, performing specific keyword analysis and sentiment analysis to obtain a positive or negative sentiment score. It also obtains the number of recipients of the email and extracts the first 200 characters of the email body to generate a summary.

[0959] Processing Description

[0960] The server-side program operates as follows:

[0961] Email Analysis

[0962] The server analyzes the body of the received email. The analysis uses Python NLP libraries (e.g., NLTK, TextBlob). This detects specific keywords in the email and automatically determines the category. TextBlob is also used to analyze the sentiment within the email and obtain a positive or negative sentiment score.

[0963] Get the number of senders

[0964] The server gets the number of recipients listed in the To, CC, and BCC fields of the email. This information is extracted from the send request.

[0965] Summary generation

[0966] The server extracts the first 200 characters of the email body and generates a summary based on that, which succinctly summarizes the email's key content.

[0967] Summary generation and insertion

[0968] The generated summary, category information, sentiment score, and number of recipients information are combined to generate a final summary, which is inserted at the beginning of the email body.

[0969] Send email

[0970] Send the email body with the final summary to the recipient.

[0971] Terminal side processing

[0972] When a user composes an email as usual and presses the send button, the program on the terminal sends an email analysis request to the server via the extension. The program receives the summary information returned from the server and inserts it at the beginning of the email body.

[0973] Specific examples

[0974] If a user composes an email like this:

[0975] Subject: Sale Announcement

[0976] Dear Customer,

[0977] This weekend, we're having a special sale in our store. Come and take advantage of 20% off all products. More details below...

[0978] The server analyzes the email body, determines the category as "Promotion", calculates the sentiment score as "Positive", and obtains the number of recipients as 1. It generates a summary by extracting the first 200 characters and generates the following:

[0979] Summary of this email

[0980] Category: Promotion

[0981] Number of senders: 1

[0982] Summary: Dear customers, we are holding a special sale in our store this weekend. Please come and take advantage of this opportunity to get 20% off all products. Further details are as follows...

[0983] Emotion: Positive

[0984] This summary will be inserted at the beginning of the email body and will look something like this:

[0985] Summary of this email

[0986] Category: Promotion

[0987] Number of senders: 1

[0988] Summary: Dear customers, we are holding a special sale in our store this weekend. Please come and take advantage of this opportunity to get 20% off all products. Further details are as follows...

[0989] Emotion: Positive

[0990] Subject: Sale Announcement

[0991] Dear Customer,

[0992] This weekend, we're having a special sale in our store. Come and take advantage of 20% off all products. More details below...

[0993] Example prompts to input to a generative AI model:

[0994] "Please analyze the content of this email, determine its category, recognize its sentiment, and create a summary."

[0995] Example of email content:

[0996] "Dear customers, we are having a special sale in our store this weekend. We are offering 20% ​​off all products, so please come and visit us. More details below..."

[0997] Hardware and software used

[0998] The hardware used is a smartphone, and the software uses Python, NLP libraries (NLTK, TextBlob), and smartphone application development frameworks (e.g., React Native, Swift, Kotlin).

[0999] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1000] Step 1:

[1001] The user creates an email. The recipient, subject, and body of the email are entered on the email creation screen. The input includes the email body and recipient information. When the user presses the send button, the device sends an email analysis request to the server.

[1002] Step 2:

[1003] The server receives an email analysis request, which includes the email body, subject, and recipient information. The server analyzes the content to identify email categories and sentiment. This process uses NLP libraries such as Python's NLTK or TextBlob to extract specific keywords and sentiment scores.

[1004] Input: Email body, subject, recipient information

[1005] Output: Email category, sentiment score

[1006] Step 3:

[1007] The server obtains the number of recipients of the email. It counts the number of recipients listed in the To, CC, and BCC fields. This generates the number of recipients information.

[1008] Input: To, CC, BCC information

[1009] Output: Number of recipients

[1010] Step 4:

[1011] The server extracts the first 200 characters of the email body and generates a summary based on them. This summary is generated to concisely express the important content of the email.

[1012] Input: Email body

[1013] Output: Summary

[1014] Step 5:

[1015] The server combines the email category, sentiment score, number of recipients, and the generated summary to generate a summary, which is then added to the beginning of the email body.

[1016] Input: Email category, sentiment score, number of recipients, summary

[1017] Output: Summary

[1018] Step 6:

[1019] The server inserts the generated summary at the beginning of the email body, thus creating a new email body with the summary.

[1020] Input: Summary, email body

[1021] Output: Email body with summary

[1022] Step 7:

[1023] The server sends the email body with the summary to the terminal. The terminal receives this information and displays the email in a format with the summary added to the beginning of the email body.

[1024] Input: Email body with summary

[1025] Output: Send to terminal

[1026] Step 8:

[1027] The terminal transmits the email body with the summary to the recipient, so that the recipient can receive the email with the summary.

[1028] Input: Email body with summary

[1029] Output: Send to recipient

[1030] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1031] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1032] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1033] [Third embodiment]

[1034] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1035] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1036] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1037] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1038] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1039] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1040] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1041] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1042] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[1043] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1044] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1045] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[1046] An embodiment of the present invention will be described below, which concerns a system that analyzes the body of an email, automatically determines the category, acquires the number of recipients, extracts the first part of the email body, generates a summary, generates a summary based on this information, and sends the email body with the summary inserted at the beginning of the email body.

[1047] Server-side processing

[1048] The server performs the following process each time a new email is sent:

[1049] 1. Email Analysis

[1050] The server analyzes the content of the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). This analysis process may use natural language processing (NLP) technology.

[1051] 2. Obtaining the number of senders

[1052] The server obtains the number of recipients listed in the To, CC, and BCC fields of the email and records this number as the number of recipients.

[1053] 3. Summary Generation

[1054] The server extracts the first 200 characters of the email body and sets it as a summary, which is used to succinctly express the important content of the email.

[1055] 4. Generating a summary

[1056] The server generates a "summary of this email" by combining the category, number of recipients, and summary text based on the analysis results.

[1057] Terminal side processing

[1058] The terminal performs the following process when the user sends an email.

[1059] 1. Email Request

[1060] When a user enters the email body on the email composition screen and presses the send button, the device sends an email analysis request to the server via the extension, which includes the email body, subject, and recipient information.

[1061] 2. Receiving a response from the server

[1062] The terminal receives summary information returned from the server, which includes the email category, the number of senders, and a summary.

[1063] 3. Update the email body

[1064] The terminal adds the received summary information to the beginning of the mail body, and generates a new mail body with the summary.

[1065] 4. Send email

[1066] Finally, the terminal sends the new mail body with the summary to the user's intended recipient.

[1067] User operations

[1068] The user performs the following operations:

[1069] 1. Create an email

[1070] The user opens the Gmail email composition screen as usual and enters the recipient, subject, and body of the email.

[1071] 2. Send email

[1072] When the user hits the send button, a summary is automatically generated and inserted at the beginning of the email body, after which the email is sent to its destination.

[1073] Explanation with a concrete example

[1074] For example, suppose a user creates an email like this:

[1075] Subject: Regarding deadline extension

[1076] Thank you for your continued support. This is Suzuki from the company.

[1077] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1078] When this email is sent, the server analyzes the text, determines the category as "Contact," and gets the number of recipients as 1. It generates a summary by extracting the first 200 characters and creates the following summary:

[1079] Summary of this email

[1080] Category: Contact

[1081] Number of senders: 1

[1082] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1083] This summary will be inserted at the beginning of the email body, and will look like this:

[1084] Summary of this email

[1085] Category: Contact

[1086] Number of senders: 1

[1087] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1088] Subject: Regarding deadline extension

[1089] Thank you for your continued support. This is Suzuki from the company.

[1090] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1091] Finally, the user can send a properly structured email without any special operations, making it easier for the recipient to understand the content. In this way, the present invention provides a system that helps the recipient of the email quickly understand the content and improves work efficiency.

[1092] The processing flow will be explained below.

[1093] Step 1:

[1094] The user opens the email composition screen, enters the recipient, subject, and body of the email, and performs the usual email composition operation.

[1095] Step 2:

[1096] The user clicks the "Send" button. At this moment, the device starts pre-processing for sending the email.

[1097] Step 3:

[1098] The terminal's extension function is launched and acquires the body, subject, and recipient information of the email currently being composed.

[1099] Step 4:

[1100] The terminal generates a request to send the acquired email body, subject, and destination information to the server. The request includes the email body text and destination information.

[1101] Step 5:

[1102] The server receives the request and begins parsing the email body.

[1103] Step 6:

[1104] The server analyzes the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). The category is determined, for example, as follows:

[1105] "if (emailBody.includes('Tasks')) { category = 'Tasks';}"

[1106] "else if (emailBody.includes('Contact')) { category = 'Contact';}"

[1107] "else { category = 'Other';}"

[1108] Step 7:

[1109] The server obtains the number of recipients based on the destination information, which can be easily obtained from the email header information.

[1110] Step 8:

[1111] The server extracts the first 200 characters of the email body and generates a summary that summarizes the important parts of the email body. For example, it is extracted as "let summaryText = emailBody.substring(0, 200);".

[1112] Step 9:

[1113] The server generates a summary by combining the category, the number of recipients, and the summary text. The generated summary will have the following format:

[1114] "Summary of this email\nCategory: ${category}\nNumber of recipients: ${recipientCount}\nSummary: ${summaryText}"

[1115] Step 10:

[1116] The server returns the generated summary to the terminal.

[1117] Step 11:

[1118] The terminal receives the response from the server and obtains the summary information.

[1119] Step 12:

[1120] The summary information received by the terminal is inserted at the beginning of the email body. The new email body will look like this:

[1121] "let updatedEmailBody = ${summary}\n\n${emailBody}"

[1122] Step 13:

[1123] The terminal generates a new email body with a summary and resumes the email sending process.

[1124] Step 14:

[1125] The device sends the updated email body to the recipient, and the email is sent.

[1126] Example 1

[1127] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1128] Efficient communication via e-mail is important in many business processes. However, when the body of an e-mail is lengthy, it is difficult for the recipient to quickly grasp the important information. This results in reduced work efficiency and slower decision-making. Furthermore, if the e-mail category is not properly determined, it can be difficult to organize and search for information. Furthermore, the number of e-mail recipients is also important information, and not knowing this information makes it difficult to respond appropriately.

[1129] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1130] In this invention, the server includes means for automatically analyzing the email body to determine its category, means for acquiring the number of recipients of the email, means for extracting the first part of the email body to generate a summary, means for inserting the generated summary at the beginning of the email body, means for transmitting the email body with the summary, means for determining the category based on keywords using natural language processing technology, means for sending an email analysis request to the server, and means for receiving summary information from the server and updating the email body. This allows email recipients to quickly grasp important information and take appropriate action. Automating email category determination and recording the number of recipients facilitates information organization and search, improving business efficiency.

[1131] "Means for automatically determining the category by analyzing the body of an email" refers to technology that analyzes the content of an email and automatically identifies the type and purpose of the email based on specific keywords and patterns.

[1132] "Means for obtaining the number of recipients of an email" refers to a method for calculating the total number of recipients from the destination information of an email and recording that information.

[1133] "Means for extracting the first part of the email body and generating a summary" refers to a technology that extracts text within a specified number of characters from the email body and uses that text as the summary of the email.

[1134] "Means for inserting the generated summary at the beginning of the email body" refers to a technology or method for adding the generated summary to the beginning of the original email content.

[1135] "Means for sending an email body with a summary" refers to a technique for delivering an email to a designated recipient after a summary has been added.

[1136] "Means for determining categories based on keywords using natural language processing technology" refers to a method of using natural language processing (NLP) algorithms to extract important keywords from the text in an email and determine the type of email based on that.

[1137] "Means for sending an email analysis request to a server" refers to a technology for sending the email body and related information to a server in order to analyze the content of an email created by a user.

[1138] "Means for receiving summary information from a server and updating the email body" refers to a technology or method for receiving summary information returned from a server and using it to update the original email content.

[1139] An embodiment of the present invention will be described below. This invention provides a system that analyzes the body of an email, automatically determines the category, obtains the number of recipients, generates an outline of the email body, creates a summary, and inserts it at the beginning of the email. This system enables email recipients to quickly grasp information and improve work efficiency.

[1140] Server-side processing

[1141] The server processes each email sent using Python software, with natural language processing (NLP) techniques such as NLTK and spaCy used for automated email analysis.

[1142] 1. Email analysis: The server analyzes the body of the received email and determines the category based on specific keywords. For example, emails containing keywords such as "contact" or "task" are classified into specific categories.

[1143] 2. Get the number of recipients: The server gets the number of recipients in the To, CC, and BCC fields of the email using Python's built-in library.

[1144] 3. Summary generation: The server extracts the first 200 characters of the email body and sets them as a summary, which succinctly expresses the important content of the email.

[1145] 4. Summary generation: The server generates a summary by combining the analyzed categories, the number of senders, and a summary. This summary is inserted at the beginning of the email.

[1146] Terminal side processing

[1147] The device primarily handles the process of sending emails, and the device extension uses JavaScript and the Gmail API.

[1148] 1. Email sending request: When a user presses the send button on the email composition screen, the device sends an email analysis request to the server. This request includes the email body, subject, and recipient information.

[1149] 2. Receiving a response from the server: The terminal receives summary information returned from the server, which includes the email category, the number of senders, and a summary.

[1150] 3. Update the email body: The terminal adds the summary information to the beginning of the email body and generates a new email body with the summary.

[1151] 4. Send email: The device finally sends the updated email body to the specified recipient.

[1152] User operations

[1153] The user opens an email creation screen such as Gmail as usual, enters the recipient, subject, and body of the email, and when they press the send button, the email is automatically analyzed and a summary is generated and inserted.

[1154] Specific examples

[1155] For example, consider the case where a user creates an email with the following content:

[1156] Subject: Regarding deadline extension

[1157] Thank you for your continued support. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1158] The server analyzes this email, determines that it is in the "Contact" category, and sets the number of recipients to 1. It extracts the first 200 characters of the email body and generates the following summary:

[1159] Summary of this email

[1160] Category: Contact

[1161] Number of senders: 1

[1162] Summary: Thank you for your continued support. I would like to extend the deadline for this project due to the following reasons...

[1163] This summary is inserted at the beginning of the email body and is finally sent to the recipient.

[1164] Prompt Sentence Examples

[1165] """A new email has been created. Please parse the body of the email below to generate a category and summary."""

[1166] This system allows users to quickly convey important information to recipients without performing any special operations, improving work efficiency and enabling faster decision-making.

[1167] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1168] Server-side processing

[1169] Step 1: Email Analysis

[1170] The server analyzes the body of each new email sent. It receives the body of the email to be sent as input and uses natural language processing (NLP) techniques to extract specific keywords. For example, it extracts keywords such as "project" and "contact," and automatically classifies the email as a "business contact" based on these keywords. This is done using Python and NLP libraries such as NLTK and spaCy.

[1171] Input: Email body

[1172] Output: Email category (e.g. "Business Notice")

[1173] Specific operation: The server runs a Python script to extract keywords from the email body and determine the category.

[1174] Step 2: Get the number of senders

[1175] The server obtains the number of recipients listed in the To, CC, and BCC fields of the email. It receives the email header information as input and calculates the number of recipients using Python's built-in library. For example, if there are three To, two CC, and one BCC recipients, the server obtains a total of six recipients.

[1176] Input: Email header information

[1177] Output: Number of recipients (e.g. 6)

[1178] Specific operation: The server analyzes the header information of the received email and compiles a list of recipients.

[1179] Step 3: Generate a summary

[1180] The server extracts the first 200 characters of the email body and sets it as a summary. It receives the email body as input and performs string manipulation to extract the first 200 characters. This generates a summary that succinctly conveys the important content of the email.

[1181] Input: Email body

[1182] Output: Summary (e.g. "Thank you for your continued support. The deadline for this project is...")

[1183] Specific operation: The server uses a Python script to extract the first 200 characters of the email body and generate a summary.

[1184] Step 4: Generate a summary

[1185] The server generates a summary by combining the category based on the analysis results, the number of senders, and the summary. As input, it receives the determined category, the number of senders, and the generated summary, and inserts these into a standard format to generate the summary.

[1186] Input: Category, number of recipients, summary

[1187] Output: Summary (Example: "Summary of this email\nCategory: Business communication\nNumber of recipients: 6\nSummary: Thank you for your continued support...")

[1188] What it does: The server runs a Python script that generates a summary by inserting the category, number of senders, and summary text into a format.

[1189] Terminal side processing

[1190] Step 1: Email Sending Request

[1191] When a user enters the email body on the email composition screen and presses the send button, the device sends an email analysis request to the server. The device takes the email body, subject, and recipient information entered by the user as input, generates an HTTP request using JavaScript and the Gmail API, and sends it to the server.

[1192] Input: Email body, subject, recipient information

[1193] Output: Sending an email parsing request

[1194] Specific operation: The device executes JavaScript and sends the email information to the server as an HTTP request.

[1195] Step 2: Receiving a response from the server

[1196] The terminal receives the summary information returned from the server. As input, it receives the HTTP response from the server and parses it using JavaScript. The summary information includes the email category, the number of senders, and a summary.

[1197] Input: HTTP response from the server

[1198] Output: Receive summary information

[1199] Specific operation: The terminal receives the HTTP response and extracts summary information using JavaScript.

[1200] Step 3: Update the email body

[1201] The terminal adds the summary information to the beginning of the email body and generates a new email body. As input, it receives the received summary information and the original email body, performs string manipulation, and adds the summary to the beginning.

[1202] Input: Summary information, original email body

[1203] Output: New email body

[1204] Specific operation: The device uses JavaScript to add summary information to the beginning of the original email body.

[1205] Step 4: Send email

[1206] The terminal finally sends the new email body with the summary to the specified recipient. As input, it takes the new email body and email destination information and sends it using the Gmail API.

[1207] Input: New email body, email recipient information

[1208] Output: Send email

[1209] Specific operation: The device uses the Gmail API to send the new email body to the recipient.

[1210] User operations

[1211] Step 1: Create an email

[1212] The user opens the email creation screen as usual and enters the recipient, subject, and body of the email. The terminal receives the email creation information manually entered by the user as input and manages it.

[1213] Input: User email creation information

[1214] Output: Save email information

[1215] Specific operation: The user enters email information using an email composition screen such as Gmail.

[1216] (Application example 1)

[1217] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1218] When an email contains a large amount of information, it is difficult for the recipient to quickly understand the content. Furthermore, as the number of customer response emails and notifications increases in virtual stores, there is a need for a method to efficiently manage these emails and quickly convey important information to recipients. To solve this problem, it is necessary to automate email analysis and automatically generate summaries using a generative AI model. Furthermore, when generating summaries, a function is also needed to automatically insert the generated summaries into the email body.

[1219] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1220] In this invention, the server includes means for analyzing the email body and automatically determining the category, means for acquiring the number of recipients of the email, means for extracting the first part of the email body and generating a summary, means for inserting the generated summary at the beginning of the email body, means for sending the email body with the summary, means for analyzing emails and notifications for customer service in the virtual store and generating summaries, and means for using a generation AI model and prompt text when generating summaries. This enables efficient management of emails and notifications for customer service in the virtual store and enables recipients to quickly grasp important information.

[1221] "Means for automatically determining the category by analyzing the body of the email" is a function that interprets the content of the email and automatically identifies its category based on specific keywords or patterns.

[1222] "Means for obtaining the number of recipients of an email" is a function that automatically calculates and obtains the number of recipients listed in the To, CC, and BCC fields of an email.

[1223] The "means for extracting the first part of the email body and generating a summary" is a function that extracts a certain portion of the first part of the email body and uses that portion to generate a summary as a short sentence.

[1224] The "means for inserting the generated summary at the beginning of the email body" is a function for adding an automatically generated summary to the beginning of the email body and inserting it at the beginning of the email body.

[1225] The "means for sending the email body with the summary" is a function for finally sending the improved email with the summary inserted to the specified recipient.

[1226] "Means for analyzing emails and notifications related to customer service in a virtual store and generating summaries" is a function that analyzes emails and notifications related to the operation of a virtual store and automatically generates summaries that summarize their contents in a concise and easy-to-understand format.

[1227] "Means for using a generative AI model and prompt sentences when generating summaries" refers to a function that utilizes a generative AI model when generating summaries and performs effective natural language generation using optimal prompt sentences.

[1228] MODE FOR CARRYING OUT THE INVENTION

[1229] overview

[1230] This invention provides a system for efficiently and quickly processing customer correspondence emails and notifications in a virtual store. In particular, the system analyzes the text of the email, automatically classifies it into an appropriate category, generates a summary, and inserts the generated summary at the beginning of the email text before sending it, allowing the recipient to quickly grasp important information.

[1231] Server-side processing

[1232] Each time a new email is sent, the server performs the following process. First, the server analyzes the email body and automatically assigns it to a specified category. This process is performed using natural language processing (NLP) technology, based on specific keywords and phrases. Next, the server obtains the number of recipients from the email's recipient list and records that number. After that, it extracts the first part of the email body (for example, the first 200 characters) and sets it as the summary. Finally, it combines the category, number of recipients, and summary to generate a summary, which is then inserted at the beginning of the email body.

[1233] Terminal side processing

[1234] When a user sends an email, the device first sends an email sending request to the server. This request includes the email body, subject, and recipient information. The server receives the request, performs the server-side processing described above to generate a summary, and returns it to the device. The device then adds the received summary information to the beginning of the email body to generate a new email body with the summary. When the user finally presses the send button, the device sends the email body with the summary to the specified recipient.

[1235] Program processing

[1236] This system is implemented using a Python program. Specifically, it uses a natural language processing library (e.g., scikit-learn) to analyze the email body and determine the category. It also uses a generative AI model to generate summaries and efficiently generate natural language using optimal prompts. The SMTP protocol is used to send emails, utilizing the Python smtplib library.

[1237] Hardware / Software used

[1238] Hardware: Standard servers or cloud-based servers (e.g., AWS or Google Cloud)

[1239] Software: Python, natural language processing library (scikit-learn), SMTP library (smtplib)

[1240] Specific examples

[1241] For example, if the support team for a hypothetical store, "XYZ Store," sends an email with the following content:

[1242] text

[1243] Subject: Enquiry about new features in XYZ Store

[1244] Body: Thank you for your support. This is customer support from XYZ Store. We'll respond to your inquiry about new features shortly...

[1245] The system automatically inserts the following summary:

[1246] text

[1247] Summary of this email

[1248] Category: Inquiry

[1249] Number of senders: 1

[1250] Summary: Hello, this is customer support for XYZ Store. We'll get back to you shortly with any questions you may have about new features...

[1251] Prompt Sentence Examples

[1252] An example prompt for a generative AI model is:

[1253] text

[1254] Analyze the content of the email below and generate the category, number of recipients, and summary.

[1255] ---

[1256] Subject: {subject}

[1257] Body: {body}

[1258] This system streamlines customer-facing emails and notifications in virtual stores, allowing recipients to quickly grasp important information.

[1259] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1260] Program processing steps

[1261] Step 1: Email Sending Request

[1262] When the user enters the email body on the email creation screen and presses the send button, the device sends a send request including the email body, subject, and recipient information to the server.

[1263] Input: Email body, subject, recipient information

[1264] Output: Email parsing request to the server

[1265] Specific operation: When the user completes the input and presses the send button, the terminal compiles this data and sends it to the server as an HTTP request.

[1266] Step 2: Email Analysis

[1267] The server analyzes the body of the received email and automatically determines the category based on specific keywords and phrases, using natural language processing technology.

[1268] Input: Email body

[1269] Output: Email Category

[1270] Specific operation: The server analyzes the email body using a natural language processing model (such as scikit-learn) and determines the category based on the frequency of word occurrence and context.

[1271] Step 3: Get the number of senders

[1272] The server obtains the number of recipients from the email address list and records that number.

[1273] Input: To information, CC information, BCC information

[1274] Output: Number of recipients

[1275] Specific operation: The server analyzes the recipient list, totals the number of email addresses contained in each list, and obtains the number of recipients.

[1276] Step 4: Generate a summary

[1277] The server extracts the first 200 characters of the email body and sets them as the summary.

[1278] Input: Email body

[1279] Output: Summary

[1280] What it does: The server extracts the first 200 characters from the email body and generates a concise summary.

[1281] Step 5: Generate a summary

[1282] The server generates a summary by combining the category, number of senders, and summary text.

[1283] Input: Email category, number of recipients, summary

[1284] Output: Summary

[1285] Specific operation: The server integrates each piece of data and creates a text in the format of "Summary of this email."

[1286] Step 6: Inserting a summary

[1287] The server inserts the generated summary at the beginning of the email body.

[1288] Input: Email body, summary

[1289] Output: Email body with summary

[1290] Specific behavior: The server adds a summary in text format before the original email body.

[1291] Step 7: Return summary information

[1292] The server returns the email body with the summary to the terminal.

[1293] Input: Email body with summary

[1294] Output: Data sent to the terminal

[1295] Specific operation: The server sends the email body with the summary to the terminal as an HTTP response.

[1296] Step 8: Update the email body

[1297] The terminal updates the mail body based on the received summary information and generates a new mail body with the summary.

[1298] Input: Email body with summary

[1299] Output: Updated email body

[1300] Specific operation: The device creates a new email body based on the received data and completes preparations to send the email.

[1301] Step 9: Send email

[1302] Finally, the terminal sends the new mail body with the summary to the user's intended recipient.

[1303] Input: Updated email body, recipient information

[1304] Output: Email sent

[1305] Specific operation: The terminal uses the SMTP protocol to send an email with a summary to the specified recipient.

[1306] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1307] An embodiment of the present invention will be described. This embodiment provides a system that analyzes an email body, automatically determines its category, and further recognizes the user's emotions and reflects that information in a summary. This system acquires the number of recipients of the email, extracts the first part of the email body to generate a summary, inserts the generated summary at the beginning of the email body, and sends the email body with the summary. It can also analyze the user's emotions using an emotion engine, further subdivide the email category, and add emotional information to the summary.

[1308] Server-side processing

[1309] The server performs the following process each time a new email is sent:

[1310] 1. Email Analysis

[1311] The server analyzes the content of the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). Furthermore, it uses an emotion engine to extract the user's emotions (e.g., joy, anger, sadness, etc.) from the body of the email.

[1312] 2. Obtaining the number of senders

[1313] The server obtains the number of recipients listed in the To, CC, and BCC fields of the email and records this number as the number of recipients.

[1314] 3. Summary Generation

[1315] The server extracts the first 200 characters of the email body and sets it as a summary, which is used to succinctly express the important content of the email.

[1316] 4. Generating a summary

[1317] The server generates a "summary of this email" by combining the category based on the analysis results, the number of recipients, the summary text, and the emotional information extracted from the emotion engine.

[1318] Terminal side processing

[1319] The terminal performs the following process when the user sends an email.

[1320] 1. Email Request

[1321] When a user enters the email body on the email composition screen and presses the send button, the device sends an email analysis request to the server via the extension, which includes the email body, subject, and recipient information.

[1322] 2. Receiving a response from the server

[1323] The terminal receives summary information returned from the server, which includes the email category, the number of recipients, a summary, and the user's emotional information.

[1324] 3. Update the email body

[1325] The terminal adds the received summary information to the beginning of the mail body, and generates a new mail body with the summary.

[1326] 4. Send email

[1327] Finally, the terminal sends the new mail body with the summary to the user's intended recipient.

[1328] User operations

[1329] The user performs the following operations:

[1330] 1. Create an email

[1331] The user opens the email composition screen as usual and enters the recipient, subject, and body of the email.

[1332] 2. Send email

[1333] When the user presses the send button, a summary and emotional information are automatically generated and inserted at the beginning of the email body, after which the email is sent to the recipient.

[1334] Explanation with a concrete example

[1335] For example, suppose a user creates an email like this:

[1336] Subject: Regarding deadline extension

[1337] Thank you for your continued support. This is Suzuki from the company.

[1338] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1339] When this email is sent, the server analyzes the text and determines the category as "Contact," and uses the emotion engine to recognize the emotion as "Impatience." The server then obtains the number of recipients as 1. It generates a summary by extracting the first 200 characters and creates the following summary:

[1340] Summary of this email

[1341] Category: Contact

[1342] Number of senders: 1

[1343] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1344] Emotion: Impatience

[1345] This summary will be inserted at the beginning of the email body, and will look like this:

[1346] Summary of this email

[1347] Category: Contact

[1348] Number of senders: 1

[1349] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1350] Emotion: Impatience

[1351] Subject: Regarding deadline extension

[1352] Thank you for your continued support. This is Suzuki from the company.

[1353] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1354] Ultimately, users can send emails that are properly structured and contain emotional information without any special operations, making it easier for recipients to understand the content. In this way, the present invention provides a system that helps email recipients quickly assess the content and improves work efficiency.

[1355] The processing flow will be explained below.

[1356] Step 1:

[1357] The user opens the email creation screen and enters the recipient, subject, and body of the email. This is the normal email creation process.

[1358] Step 2:

[1359] The user clicks the "Send" button. At this moment, the device starts pre-processing for sending the email.

[1360] Step 3:

[1361] The terminal's extension function is launched and acquires the body, subject, and recipient information of the email currently being composed.

[1362] Step 4:

[1363] The terminal generates a request to send the acquired email body, subject, and destination information to the server. The request includes the email body text and destination information.

[1364] Step 5:

[1365] The server receives the request and begins parsing the email body.

[1366] Step 6:

[1367] The server analyzes the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). The category is determined, for example, as follows:

[1368] "if (emailBody.includes('Tasks')) { category = 'Tasks';}"

[1369] "else if (emailBody.includes('Contact')) { category = 'Contact';}"

[1370] "else { category = 'Other';}"

[1371] Step 7:

[1372] The server uses an emotion engine to recognize the user's emotions from the email body. For example, it uses natural language processing technology to analyze emotion-related words and context in the body of the email. The recognized emotions are specifically classified as "joy," "anger," "sadness," etc.

[1373] Step 8:

[1374] The server obtains the number of recipients based on the destination information, which can be easily obtained from the email header information.

[1375] Step 9:

[1376] The server extracts the first 200 characters of the email body and generates a summary that summarizes the important parts of the email body. For example, it is extracted as "let summaryText = emailBody.substring(0, 200);".

[1377] Step 10:

[1378] The server generates a summary by combining the category based on the analysis results, the number of senders, the summary text, and the emotion information extracted from the emotion engine. The generated summary has the following format:

[1379] "Summary of this email\nCategory: ${category}\nNumber of recipients: ${recipientCount}\nSummary: ${summaryText}\nEmotion: ${emotion}"

[1380] Step 11:

[1381] The server returns the generated summary to the terminal.

[1382] Step 12:

[1383] The terminal receives the response from the server and obtains the summary information.

[1384] Step 13:

[1385] The summary information received by the terminal is inserted at the beginning of the email body. The new email body will look like this:

[1386] "let updatedEmailBody = ${summary}\n\n${emailBody}"

[1387] Step 14:

[1388] The terminal generates a new email body with a summary and resumes the email sending process.

[1389] Step 15:

[1390] The device sends the updated email body to the recipient, and the email is sent.

[1391] Example 2

[1392] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1393] In recent years, the use of email has increased, and recipients are being asked to process large volumes of emails effectively. However, many emails are lengthy, making it difficult to grasp important information and understand the emotional nuances at a glance. Therefore, there is a need for a method that allows recipients to quickly understand the content of emails and respond appropriately. Conventional email systems do not adequately provide automatic functions for categorizing emails or determining their emotional content, and this lack is particularly evident in business situations.

[1394] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1395] In this invention, the server includes means for automatically determining the category and emotional information by analyzing the email body, means for acquiring the number of recipients of the email, means for extracting the first part of the email body to generate a summary, means for inserting the generated summary at the beginning of the email body, and means for sending the email body with the summary. This allows the content of the email to be presented in a concise and easy-to-understand format, enabling the recipient to quickly understand the main information and emotional nuances.

[1396] "Means for automatically determining category and emotion information by analyzing the body of an email" refers to a device or program that has the function of analyzing the content of an email and automatically identifying the category and emotion from the content using a text analysis engine or an emotion analysis engine.

[1397] The "means for acquiring the number of recipients of an e-mail" is a device or program that has the function of counting the number of recipients from an e-mail destination list and collecting that information.

[1398] The "means for extracting the first part of the email body and generating a summary" refers to a device or program that has the function of extracting a certain number of first characters from the email body and summarizing them as a concise summary.

[1399] The "means for inserting the generated summary at the beginning of the email body" refers to a device or program that has the function of adding the generated summary or analysis results to the beginning of the email body and creating an updated email body.

[1400] The "means for sending a mail body with a summary" is a device or program that has the function of sending an email containing an updated mail body to a specified recipient.

[1401] This section describes an embodiment of the present invention. This embodiment provides a system that analyzes the text of an email, automatically determines the category and emotional information, and generates an outline that reflects the results in a summary. This system is composed of a server and a terminal.

[1402] Each time an email is sent, the server performs the following process. First, the server analyzes the email body. Specifically, it uses a text analysis engine (e.g., Google Cloud Natural Language API) to analyze the body and determine the email category based on specific keywords and context. At the same time, it uses an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) to extract the user's emotional information (joy, anger, sadness, etc.) from the body of the email.

[1403] Next, the server extracts the number of recipients from the To, CC, and BCC fields of the email. This is recorded as the number of recipients of the email. The server then extracts the first 200 characters of the email body and uses this as a summary. This summary is used to concisely express the important content of the email.

[1404] The server then generates a summary based on the analysis results, combining the category, number of recipients, summary text, and sentiment information. This summary is saved as a "summary of this email."

[1405] When the user presses the send button, the terminal sends an email analysis request to the server. This request includes the email body, subject, and recipient information. After receiving a response from the server, the terminal adds the summary information to the beginning of the email body to generate a new email body with the summary. Finally, the terminal sends the email with the summary to the recipient specified by the user.

[1406] Users simply enter the recipient, subject, and message body on the email composition screen as usual and press the send button. This action sends a properly structured email that includes a summary and emotional information without requiring any special operations.

[1407] For example, if a user creates an email like this:

[1408] Subject: Regarding deadline extension

[1409] Thank you for your continued support. This is Suzuki from the company.

[1410] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1411] The server analyzes the text and determines the category as "Contact," and uses the emotion engine to identify the emotion as "Impatience." The server then obtains the number of recipients as 1. The server extracts the first 200 characters to generate a summary, creating the following:

[1412] Summary of this email

[1413] Category: Contact

[1414] Number of senders: 1

[1415] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1416] Emotion: Impatience

[1417] This summary will be inserted at the beginning of the email body, and will look like this:

[1418] Summary of this email

[1419] Category: Contact

[1420] Number of senders: 1

[1421] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1422] Emotion: Impatience

[1423] Subject: Regarding deadline extension

[1424] Thank you for your continued support. This is Suzuki from the company.

[1425] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1426] In this way, the present invention provides a system that helps the recipient of the mail to quickly judge the content and improves business efficiency.

[1427] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1428] Server-side processing

[1429] Step 1: Email Analysis

[1430] The server takes as input the body of the email the user is about to send. It uses a text analysis engine (e.g., Google Cloud Natural Language API) to analyze the body of the email and extract specific keywords and context. Based on this analysis, it determines the email category (e.g., "contact" or "task"). It also uses an emotion engine (e.g., IBM Watson or Microsoft Azure Emotion API) to extract the user's emotional information (e.g., joy, anger, sadness) from the body of the email. As a result of this data processing and calculation, it outputs category information and emotional information.

[1431] Step 2: Get the number of senders

[1432] The server takes the email's To, CC, and BCC fields as input. It counts the number of recipients from these fields and outputs that information as the number of recipients. This step simply counts the email addresses listed in each field.

[1433] Step 3: Generate a summary

[1434] The server takes the first part of the email body (e.g., the first 200 characters) as input. It extracts this part of the body and sets it as the summary. It outputs the extracted part as the summary.

[1435] Step 4: Generate a summary

[1436] The server inputs the category information, emotion information, number of recipients, and summary obtained in steps 1, 2, and 3. It combines these to generate and output a "summary of this email."

[1437] Terminal side processing

[1438] Step 1: Email Sending Request

[1439] The user enters the body, subject, and recipient information on the email creation screen and presses the send button. The terminal receives this information as input and sends it to the server as an email analysis request. Specifically, the terminal sends the body, subject, and recipient information of the email to the server.

[1440] Step 2: Receiving a response from the server

[1441] The terminal receives summary information returned from the server as input. This summary information includes category information, emotion information, the number of senders, and a summary. This information is then output as material for generating a new email body.

[1442] Step 3: Update the email body

[1443] The terminal takes the summary information received in step 2 and the original email body as input. It adds the summary information to the beginning of the email body to generate a new email body. This operation outputs the email body with the summary.

[1444] Step 4: Send email

[1445] The user sends the new email body with the summary to the intended recipient. This step involves sending the updated email body using the standard email sending process.

[1446] User operations

[1447] Step 1: Create an email

[1448] The user opens a mail composition screen as usual and enters the recipient, subject, and body of the message. This information becomes the input data for subsequent processing steps.

[1449] Step 2: Send an email

[1450] When the user presses the send button, the device automatically generates a summary and emotional information and inserts them at the beginning of the email body.The device then sends the email to the server.This operation ensures that the email, including the summary and emotional information, is delivered to the recipient.

[1451] Through the above processing steps, the present invention is a system that presents the contents of an email in a concise and easy-to-understand format, allowing the recipient to quickly understand the main information and emotional nuances.

[1452] (Application example 2)

[1453] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1454] In conventional email systems, it was difficult for recipients to quickly and accurately understand the contents of emails, increasing the likelihood of missing important information. Furthermore, because emails did not contain emotional information, it was difficult for recipients to understand the sender's intentions and emotions. Furthermore, there was a lack of effective ways to communicate promotional and campaign information to users in physical stores.

[1455] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically determining the category by analyzing the email body, means for acquiring the number of recipients of the email, means for extracting the first part of the email body and generating a summary, means for inserting the generated summary at the beginning of the email body, means for sending the email body with the summary, and means for recognizing the emotion of the email and reflecting that information in the summary. This allows the recipient to quickly and accurately understand the content of the email and the sender's intentions and emotions. It also makes it possible to effectively communicate information about promotions and campaigns at physical stores to users.

[1456] "Means for automatically determining the category by analyzing the body of the email" is a function that analyzes the content of the email and classifies the email into an appropriate category based on that content.

[1457] The "means for obtaining the number of recipients of an email" is a function for obtaining the number of recipients listed in the To, CC, and BCC fields of an email.

[1458] The "means for extracting the first part of the email body and generating a summary" is a function that extracts a certain portion of the first part of the email body and generates a short sentence based on that portion to express the summary of the email.

[1459] "Means for inserting the generated summary at the beginning of the email body" is a function for adding the generated summary text and category information to the beginning of the email body.

[1460] The "means for sending an email body with a summary" is a function for sending an email body with a summary attached to the recipient.

[1461] "Means of recognizing the emotion of an email and reflecting that information in the summary" is a function that analyzes the email body to recognize the emotion of the sender and adds that emotional information to the summary.

[1462] "Judgment based on specific keywords" is a method of classifying and evaluating emails based on specific keywords in the email body.

[1463] "Obtaining a positive or negative sentiment score" is a method of quantitatively evaluating the sentiment of the email body and scoring it as positive or negative.

[1464] System program generation

[1465] The server analyzes the email body and automatically determines the category. This analysis uses Natural Language Processing (NLP) technology, performing specific keyword analysis and sentiment analysis to obtain a positive or negative sentiment score. It also obtains the number of recipients of the email and extracts the first 200 characters of the email body to generate a summary.

[1466] Processing Description

[1467] The server-side program operates as follows:

[1468] Email Analysis

[1469] The server analyzes the body of the received email. The analysis uses Python NLP libraries (e.g., NLTK, TextBlob). This detects specific keywords in the email and automatically determines the category. TextBlob is also used to analyze the sentiment within the email and obtain a positive or negative sentiment score.

[1470] Get the number of senders

[1471] The server gets the number of recipients listed in the To, CC, and BCC fields of the email. This information is extracted from the send request.

[1472] Summary generation

[1473] The server extracts the first 200 characters of the email body and generates a summary based on that, which succinctly summarizes the email's key content.

[1474] Summary generation and insertion

[1475] The generated summary, category information, sentiment score, and number of recipients information are combined to generate a final summary, which is inserted at the beginning of the email body.

[1476] Send email

[1477] Send the email body with the final summary to the recipient.

[1478] Terminal side processing

[1479] When a user composes an email as usual and presses the send button, the program on the terminal sends an email analysis request to the server via the extension. The program receives the summary information returned from the server and inserts it at the beginning of the email body.

[1480] Specific examples

[1481] If a user composes an email like this:

[1482] Subject: Sale Announcement

[1483] Dear Customer,

[1484] This weekend, we're having a special sale in our store. Come and take advantage of 20% off all products. More details below...

[1485] The server analyzes the email body, determines the category as "Promotion", calculates the sentiment score as "Positive", and obtains the number of recipients as 1. It generates a summary by extracting the first 200 characters and generates the following:

[1486] Summary of this email

[1487] Category: Promotion

[1488] Number of senders: 1

[1489] Summary: Dear customers, we are holding a special sale in our store this weekend. Please come and take advantage of this opportunity to get 20% off all products. Further details are as follows...

[1490] Emotion: Positive

[1491] This summary will be inserted at the beginning of the email body and will look something like this:

[1492] Summary of this email

[1493] Category: Promotion

[1494] Number of senders: 1

[1495] Summary: Dear customers, we are holding a special sale in our store this weekend. Please come and take advantage of this opportunity to get 20% off all products. Further details are as follows...

[1496] Emotion: Positive

[1497] Subject: Sale Announcement

[1498] Dear Customer,

[1499] This weekend, we're having a special sale in our store. Come and take advantage of 20% off all products. More details below...

[1500] Example prompts to input to a generative AI model:

[1501] "Please analyze the content of this email, determine its category, recognize its sentiment, and create a summary."

[1502] Example of email content:

[1503] "Dear customers, we are having a special sale in our store this weekend. We are offering 20% ​​off all products, so please come and visit us. More details below..."

[1504] Hardware and software used

[1505] The hardware used is a smartphone, and the software uses Python, NLP libraries (NLTK, TextBlob), and smartphone application development frameworks (e.g., React Native, Swift, Kotlin).

[1506] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1507] Step 1:

[1508] The user creates an email. The recipient, subject, and body of the email are entered on the email creation screen. The input includes the email body and recipient information. When the user presses the send button, the device sends an email analysis request to the server.

[1509] Step 2:

[1510] The server receives an email analysis request, which includes the email body, subject, and recipient information. The server analyzes the content to identify email categories and sentiment. This process uses NLP libraries such as Python's NLTK or TextBlob to extract specific keywords and sentiment scores.

[1511] Input: Email body, subject, recipient information

[1512] Output: Email category, sentiment score

[1513] Step 3:

[1514] The server obtains the number of recipients of the email. It counts the number of recipients listed in the To, CC, and BCC fields. This generates the number of recipients information.

[1515] Input: To, CC, BCC information

[1516] Output: Number of recipients

[1517] Step 4:

[1518] The server extracts the first 200 characters of the email body and generates a summary based on them. This summary is generated to concisely express the important content of the email.

[1519] Input: Email body

[1520] Output: Summary

[1521] Step 5:

[1522] The server combines the email category, sentiment score, number of recipients, and the generated summary to generate a summary, which is then added to the beginning of the email body.

[1523] Input: Email category, sentiment score, number of recipients, summary

[1524] Output: Summary

[1525] Step 6:

[1526] The server inserts the generated summary at the beginning of the email body, thus creating a new email body with the summary.

[1527] Input: Summary, email body

[1528] Output: Email body with summary

[1529] Step 7:

[1530] The server sends the email body with the summary to the terminal. The terminal receives this information and displays the email in a format with the summary added to the beginning of the email body.

[1531] Input: Email body with summary

[1532] Output: Send to terminal

[1533] Step 8:

[1534] The terminal transmits the email body with the summary to the recipient, so that the recipient can receive the email with the summary.

[1535] Input: Email body with summary

[1536] Output: Send to recipient

[1537] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1538] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1539] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1540] [Fourth embodiment]

[1541] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1542] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1543] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1544] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1545] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1546] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1547] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1548] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1549] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1550] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[1551] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1552] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1553] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1554] An embodiment of the present invention will be described below, which concerns a system that analyzes the body of an email, automatically determines the category, acquires the number of recipients, extracts the first part of the email body, generates a summary, generates a summary based on this information, and sends the email body with the summary inserted at the beginning of the email body.

[1555] Server-side processing

[1556] The server performs the following process each time a new email is sent:

[1557] 1. Email Analysis

[1558] The server analyzes the content of the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). This analysis process may use natural language processing (NLP) technology.

[1559] 2. Obtaining the number of senders

[1560] The server obtains the number of recipients listed in the To, CC, and BCC fields of the email and records this number as the number of recipients.

[1561] 3. Summary Generation

[1562] The server extracts the first 200 characters of the email body and sets it as a summary, which is used to succinctly express the important content of the email.

[1563] 4. Generating a summary

[1564] The server generates a "summary of this email" by combining the category, number of recipients, and summary text based on the analysis results.

[1565] Terminal side processing

[1566] The terminal performs the following process when the user sends an email.

[1567] 1. Email Request

[1568] When a user enters the email body on the email composition screen and presses the send button, the device sends an email analysis request to the server via the extension, which includes the email body, subject, and recipient information.

[1569] 2. Receiving a response from the server

[1570] The terminal receives summary information returned from the server, which includes the email category, the number of senders, and a summary.

[1571] 3. Update the email body

[1572] The terminal adds the received summary information to the beginning of the mail body, and generates a new mail body with the summary.

[1573] 4. Send email

[1574] Finally, the terminal sends the new mail body with the summary to the user's intended recipient.

[1575] User operations

[1576] The user performs the following operations:

[1577] 1. Create an email

[1578] The user opens the Gmail email composition screen as usual and enters the recipient, subject, and body of the email.

[1579] 2. Send email

[1580] When the user hits the send button, a summary is automatically generated and inserted at the beginning of the email body, after which the email is sent to its destination.

[1581] Explanation with a concrete example

[1582] For example, suppose a user creates an email like this:

[1583] Subject: Regarding deadline extension

[1584] Thank you for your continued support. This is Suzuki from the company.

[1585] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1586] When this email is sent, the server analyzes the text, determines the category as "Contact," and gets the number of recipients as 1. It generates a summary by extracting the first 200 characters and creates the following summary:

[1587] Summary of this email

[1588] Category: Contact

[1589] Number of senders: 1

[1590] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1591] This summary will be inserted at the beginning of the email body, and will look like this:

[1592] Summary of this email

[1593] Category: Contact

[1594] Number of senders: 1

[1595] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1596] Subject: Regarding deadline extension

[1597] Thank you for your continued support. This is Suzuki from the company.

[1598] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1599] Finally, the user can send a properly structured email without any special operations, making it easier for the recipient to understand the content. In this way, the present invention provides a system that helps the recipient of the email quickly understand the content and improves work efficiency.

[1600] The processing flow will be explained below.

[1601] Step 1:

[1602] The user opens the email composition screen, enters the recipient, subject, and body of the email, and performs the usual email composition operation.

[1603] Step 2:

[1604] The user clicks the "Send" button. At this moment, the device starts pre-processing for sending the email.

[1605] Step 3:

[1606] The terminal's extension function is launched and acquires the body, subject, and recipient information of the email currently being composed.

[1607] Step 4:

[1608] The terminal generates a request to send the acquired email body, subject, and destination information to the server. The request includes the email body text and destination information.

[1609] Step 5:

[1610] The server receives the request and begins parsing the email body.

[1611] Step 6:

[1612] The server analyzes the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). The category is determined, for example, as follows:

[1613] "if (emailBody.includes('Tasks')) { category = 'Tasks';}"

[1614] "else if (emailBody.includes('Contact')) { category = 'Contact';}"

[1615] "else { category = 'Other';}"

[1616] Step 7:

[1617] The server obtains the number of recipients based on the destination information, which can be easily obtained from the email header information.

[1618] Step 8:

[1619] The server extracts the first 200 characters of the email body and generates a summary that summarizes the important parts of the email body. For example, it is extracted as "let summaryText = emailBody.substring(0, 200);".

[1620] Step 9:

[1621] The server generates a summary by combining the category, the number of recipients, and the summary text. The generated summary will have the following format:

[1622] "Summary of this email\nCategory: ${category}\nNumber of recipients: ${recipientCount}\nSummary: ${summaryText}"

[1623] Step 10:

[1624] The server returns the generated summary to the terminal.

[1625] Step 11:

[1626] The terminal receives the response from the server and obtains the summary information.

[1627] Step 12:

[1628] The summary information received by the terminal is inserted at the beginning of the email body. The new email body will look like this:

[1629] "let updatedEmailBody = ${summary}\n\n${emailBody}"

[1630] Step 13:

[1631] The terminal generates a new email body with a summary and resumes the email sending process.

[1632] Step 14:

[1633] The device sends the updated email body to the recipient, and the email is sent.

[1634] Example 1

[1635] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1636] Efficient communication via e-mail is important in many business processes. However, when the body of an e-mail is lengthy, it is difficult for the recipient to quickly grasp the important information. This results in reduced work efficiency and slower decision-making. Furthermore, if the e-mail category is not properly determined, it can be difficult to organize and search for information. Furthermore, the number of e-mail recipients is also important information, and not knowing this information makes it difficult to respond appropriately.

[1637] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1638] In this invention, the server includes means for automatically analyzing the email body to determine its category, means for acquiring the number of recipients of the email, means for extracting the first part of the email body to generate a summary, means for inserting the generated summary at the beginning of the email body, means for transmitting the email body with the summary, means for determining the category based on keywords using natural language processing technology, means for sending an email analysis request to the server, and means for receiving summary information from the server and updating the email body. This allows email recipients to quickly grasp important information and take appropriate action. Automating email category determination and recording the number of recipients facilitates information organization and search, improving business efficiency.

[1639] "Means for automatically determining the category by analyzing the body of an email" refers to technology that analyzes the content of an email and automatically identifies the type and purpose of the email based on specific keywords and patterns.

[1640] "Means for obtaining the number of recipients of an email" refers to a method for calculating the total number of recipients from the destination information of an email and recording that information.

[1641] "Means for extracting the first part of the email body and generating a summary" refers to a technology that extracts text within a specified number of characters from the email body and uses that text as the summary of the email.

[1642] "Means for inserting the generated summary at the beginning of the email body" refers to a technology or method for adding the generated summary to the beginning of the original email content.

[1643] "Means for sending an email body with a summary" refers to a technique for delivering an email to a designated recipient after a summary has been added.

[1644] "Means for determining categories based on keywords using natural language processing technology" refers to a method of using natural language processing (NLP) algorithms to extract important keywords from the text in an email and determine the type of email based on that.

[1645] "Means for sending an email analysis request to a server" refers to a technology for sending the email body and related information to a server in order to analyze the content of an email created by a user.

[1646] "Means for receiving summary information from a server and updating the email body" refers to a technology or method for receiving summary information returned from a server and using it to update the original email content.

[1647] An embodiment of the present invention will be described below. This invention provides a system that analyzes the body of an email, automatically determines the category, obtains the number of recipients, generates an outline of the email body, creates a summary, and inserts it at the beginning of the email. This system enables email recipients to quickly grasp information and improve work efficiency.

[1648] Server-side processing

[1649] The server processes each email sent using Python software, with natural language processing (NLP) techniques such as NLTK and spaCy used for automated email analysis.

[1650] 1. Email analysis: The server analyzes the body of the received email and determines the category based on specific keywords. For example, emails containing keywords such as "contact" or "task" are classified into specific categories.

[1651] 2. Get the number of recipients: The server gets the number of recipients in the To, CC, and BCC fields of the email using Python's built-in library.

[1652] 3. Summary generation: The server extracts the first 200 characters of the email body and sets them as a summary, which succinctly expresses the important content of the email.

[1653] 4. Summary generation: The server generates a summary by combining the analyzed categories, the number of senders, and a summary. This summary is inserted at the beginning of the email.

[1654] Terminal side processing

[1655] The device primarily handles the process of sending emails, and the device extension uses JavaScript and the Gmail API.

[1656] 1. Email sending request: When a user presses the send button on the email composition screen, the device sends an email analysis request to the server. This request includes the email body, subject, and recipient information.

[1657] 2. Receiving a response from the server: The terminal receives summary information returned from the server, which includes the email category, the number of senders, and a summary.

[1658] 3. Update the email body: The terminal adds the summary information to the beginning of the email body and generates a new email body with the summary.

[1659] 4. Send email: The device finally sends the updated email body to the specified recipient.

[1660] User operations

[1661] The user opens an email creation screen such as Gmail as usual, enters the recipient, subject, and body of the email, and when they press the send button, the email is automatically analyzed and a summary is generated and inserted.

[1662] Specific examples

[1663] For example, consider the case where a user creates an email with the following content:

[1664] Subject: Regarding deadline extension

[1665] Thank you for your continued support. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1666] The server analyzes this email, determines that it is in the "Contact" category, and sets the number of recipients to 1. It extracts the first 200 characters of the email body and generates the following summary:

[1667] Summary of this email

[1668] Category: Contact

[1669] Number of senders: 1

[1670] Summary: Thank you for your continued support. I would like to extend the deadline for this project due to the following reasons...

[1671] This summary is inserted at the beginning of the email body and is finally sent to the recipient.

[1672] Prompt Sentence Examples

[1673] """A new email has been created. Please parse the body of the email below to generate a category and summary."""

[1674] This system allows users to quickly convey important information to recipients without performing any special operations, improving work efficiency and enabling faster decision-making.

[1675] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1676] Server-side processing

[1677] Step 1: Email Analysis

[1678] The server analyzes the body of each new email sent. It receives the body of the email to be sent as input and uses natural language processing (NLP) techniques to extract specific keywords. For example, it extracts keywords such as "project" and "contact," and automatically classifies the email as a "business contact" based on these keywords. This is done using Python and NLP libraries such as NLTK and spaCy.

[1679] Input: Email body

[1680] Output: Email category (e.g. "Business Notice")

[1681] Specific operation: The server runs a Python script to extract keywords from the email body and determine the category.

[1682] Step 2: Get the number of senders

[1683] The server obtains the number of recipients listed in the To, CC, and BCC fields of the email. It receives the email header information as input and calculates the number of recipients using Python's built-in library. For example, if there are three To, two CC, and one BCC recipients, the server obtains a total of six recipients.

[1684] Input: Email header information

[1685] Output: Number of recipients (e.g. 6)

[1686] Specific operation: The server analyzes the header information of the received email and compiles a list of recipients.

[1687] Step 3: Generate a summary

[1688] The server extracts the first 200 characters of the email body and sets it as a summary. It receives the email body as input and performs string manipulation to extract the first 200 characters. This generates a summary that succinctly conveys the important content of the email.

[1689] Input: Email body

[1690] Output: Summary (e.g. "Thank you for your continued support. The deadline for this project is...")

[1691] Specific operation: The server uses a Python script to extract the first 200 characters of the email body and generate a summary.

[1692] Step 4: Generate a summary

[1693] The server generates a summary by combining the category based on the analysis results, the number of senders, and the summary. As input, it receives the determined category, the number of senders, and the generated summary, and inserts these into a standard format to generate the summary.

[1694] Input: Category, number of recipients, summary

[1695] Output: Summary (Example: "Summary of this email\nCategory: Business communication\nNumber of recipients: 6\nSummary: Thank you for your continued support...")

[1696] What it does: The server runs a Python script that generates a summary by inserting the category, number of senders, and summary text into a format.

[1697] Terminal side processing

[1698] Step 1: Email Sending Request

[1699] When a user enters the email body on the email composition screen and presses the send button, the device sends an email analysis request to the server. The device takes the email body, subject, and recipient information entered by the user as input, generates an HTTP request using JavaScript and the Gmail API, and sends it to the server.

[1700] Input: Email body, subject, recipient information

[1701] Output: Sending an email parsing request

[1702] Specific operation: The device executes JavaScript and sends the email information to the server as an HTTP request.

[1703] Step 2: Receiving a response from the server

[1704] The terminal receives the summary information returned from the server. As input, it receives the HTTP response from the server and parses it using JavaScript. The summary information includes the email category, the number of senders, and a summary.

[1705] Input: HTTP response from the server

[1706] Output: Receive summary information

[1707] Specific operation: The terminal receives the HTTP response and extracts summary information using JavaScript.

[1708] Step 3: Update the email body

[1709] The terminal adds the summary information to the beginning of the email body and generates a new email body. As input, it receives the received summary information and the original email body, performs string manipulation, and adds the summary to the beginning.

[1710] Input: Summary information, original email body

[1711] Output: New email body

[1712] Specific operation: The device uses JavaScript to add summary information to the beginning of the original email body.

[1713] Step 4: Send email

[1714] The terminal finally sends the new email body with the summary to the specified recipient. As input, it takes the new email body and email destination information and sends it using the Gmail API.

[1715] Input: New email body, email recipient information

[1716] Output: Send email

[1717] Specific operation: The device uses the Gmail API to send the new email body to the recipient.

[1718] User operations

[1719] Step 1: Create an email

[1720] The user opens the email creation screen as usual and enters the recipient, subject, and body of the email. The terminal receives the email creation information manually entered by the user as input and manages it.

[1721] Input: User email creation information

[1722] Output: Save email information

[1723] Specific operation: The user enters email information using an email composition screen such as Gmail.

[1724] (Application example 1)

[1725] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1726] When an email contains a large amount of information, it is difficult for the recipient to quickly understand the content. Furthermore, as the number of customer response emails and notifications increases in virtual stores, there is a need for a method to efficiently manage these emails and quickly convey important information to recipients. To solve this problem, it is necessary to automate email analysis and automatically generate summaries using a generative AI model. Furthermore, when generating summaries, a function is also needed to automatically insert the generated summaries into the email body.

[1727] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1728] In this invention, the server includes means for analyzing the email body and automatically determining the category, means for acquiring the number of recipients of the email, means for extracting the first part of the email body and generating a summary, means for inserting the generated summary at the beginning of the email body, means for sending the email body with the summary, means for analyzing emails and notifications for customer service in the virtual store and generating summaries, and means for using a generation AI model and prompt text when generating summaries. This enables efficient management of emails and notifications for customer service in the virtual store and enables recipients to quickly grasp important information.

[1729] "Means for automatically determining the category by analyzing the body of the email" is a function that interprets the content of the email and automatically identifies its category based on specific keywords or patterns.

[1730] "Means for obtaining the number of recipients of an email" is a function that automatically calculates and obtains the number of recipients listed in the To, CC, and BCC fields of an email.

[1731] The "means for extracting the first part of the email body and generating a summary" is a function that extracts a certain portion of the first part of the email body and uses that portion to generate a summary as a short sentence.

[1732] The "means for inserting the generated summary at the beginning of the email body" is a function for adding an automatically generated summary to the beginning of the email body and inserting it at the beginning of the email body.

[1733] The "means for sending the email body with the summary" is a function for finally sending the improved email with the summary inserted to the specified recipient.

[1734] "Means for analyzing emails and notifications related to customer service in a virtual store and generating summaries" is a function that analyzes emails and notifications related to the operation of a virtual store and automatically generates summaries that summarize their contents in a concise and easy-to-understand format.

[1735] "Means for using a generative AI model and prompt sentences when generating summaries" refers to a function that utilizes a generative AI model when generating summaries and performs effective natural language generation using optimal prompt sentences.

[1736] MODE FOR CARRYING OUT THE INVENTION

[1737] overview

[1738] This invention provides a system for efficiently and quickly processing customer correspondence emails and notifications in a virtual store. In particular, the system analyzes the text of the email, automatically classifies it into an appropriate category, generates a summary, and inserts the generated summary at the beginning of the email text before sending it, allowing the recipient to quickly grasp important information.

[1739] Server-side processing

[1740] Each time a new email is sent, the server performs the following process. First, the server analyzes the email body and automatically assigns it to a specified category. This process is performed using natural language processing (NLP) technology, based on specific keywords and phrases. Next, the server obtains the number of recipients from the email's recipient list and records that number. After that, it extracts the first part of the email body (for example, the first 200 characters) and sets it as the summary. Finally, it combines the category, number of recipients, and summary to generate a summary, which is then inserted at the beginning of the email body.

[1741] Terminal side processing

[1742] When a user sends an email, the device first sends an email sending request to the server. This request includes the email body, subject, and recipient information. The server receives the request, performs the server-side processing described above to generate a summary, and returns it to the device. The device then adds the received summary information to the beginning of the email body to generate a new email body with the summary. When the user finally presses the send button, the device sends the email body with the summary to the specified recipient.

[1743] Program processing

[1744] This system is implemented using a Python program. Specifically, it uses a natural language processing library (e.g., scikit-learn) to analyze the email body and determine the category. It also uses a generative AI model to generate summaries and efficiently generate natural language using optimal prompts. The SMTP protocol is used to send emails, utilizing the Python smtplib library.

[1745] Hardware / Software used

[1746] Hardware: Standard servers or cloud-based servers (e.g., AWS or Google Cloud)

[1747] Software: Python, natural language processing library (scikit-learn), SMTP library (smtplib)

[1748] Specific examples

[1749] For example, if the support team for a hypothetical store, "XYZ Store," sends an email with the following content:

[1750] text

[1751] Subject: Enquiry about new features in XYZ Store

[1752] Body: Thank you for your support. This is customer support from XYZ Store. We'll respond to your inquiry about new features shortly...

[1753] The system automatically inserts the following summary:

[1754] text

[1755] Summary of this email

[1756] Category: Inquiry

[1757] Number of senders: 1

[1758] Summary: Hello, this is customer support for XYZ Store. We'll get back to you shortly with any questions you may have about new features...

[1759] Prompt Sentence Examples

[1760] An example prompt for a generative AI model is:

[1761] text

[1762] Analyze the content of the email below and generate the category, number of recipients, and summary.

[1763] ---

[1764] Subject: {subject}

[1765] Body: {body}

[1766] This system streamlines customer-facing emails and notifications in virtual stores, allowing recipients to quickly grasp important information.

[1767] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1768] Program processing steps

[1769] Step 1: Email Sending Request

[1770] When the user enters the email body on the email creation screen and presses the send button, the device sends a send request including the email body, subject, and recipient information to the server.

[1771] Input: Email body, subject, recipient information

[1772] Output: Email parsing request to the server

[1773] Specific operation: When the user completes the input and presses the send button, the terminal compiles this data and sends it to the server as an HTTP request.

[1774] Step 2: Email Analysis

[1775] The server analyzes the body of the received email and automatically determines the category based on specific keywords and phrases, using natural language processing technology.

[1776] Input: Email body

[1777] Output: Email Category

[1778] Specific operation: The server analyzes the email body using a natural language processing model (such as scikit-learn) and determines the category based on the frequency of word occurrence and context.

[1779] Step 3: Get the number of senders

[1780] The server obtains the number of recipients from the email address list and records that number.

[1781] Input: To information, CC information, BCC information

[1782] Output: Number of recipients

[1783] Specific operation: The server analyzes the recipient list, totals the number of email addresses contained in each list, and obtains the number of recipients.

[1784] Step 4: Generate a summary

[1785] The server extracts the first 200 characters of the email body and sets them as the summary.

[1786] Input: Email body

[1787] Output: Summary

[1788] What it does: The server extracts the first 200 characters from the email body and generates a concise summary.

[1789] Step 5: Generate a summary

[1790] The server generates a summary by combining the category, number of senders, and summary text.

[1791] Input: Email category, number of recipients, summary

[1792] Output: Summary

[1793] Specific operation: The server integrates each piece of data and creates a text in the format of "Summary of this email."

[1794] Step 6: Inserting a summary

[1795] The server inserts the generated summary at the beginning of the email body.

[1796] Input: Email body, summary

[1797] Output: Email body with summary

[1798] Specific behavior: The server adds a summary in text format before the original email body.

[1799] Step 7: Return summary information

[1800] The server returns the email body with the summary to the terminal.

[1801] Input: Email body with summary

[1802] Output: Data sent to the terminal

[1803] Specific operation: The server sends the email body with the summary to the terminal as an HTTP response.

[1804] Step 8: Update the email body

[1805] The terminal updates the mail body based on the received summary information and generates a new mail body with the summary.

[1806] Input: Email body with summary

[1807] Output: Updated email body

[1808] Specific operation: The device creates a new email body based on the received data and completes preparations to send the email.

[1809] Step 9: Send email

[1810] Finally, the terminal sends the new mail body with the summary to the user's intended recipient.

[1811] Input: Updated email body, recipient information

[1812] Output: Email sent

[1813] Specific operation: The terminal uses the SMTP protocol to send an email with a summary to the specified recipient.

[1814] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1815] An embodiment of the present invention will be described. This embodiment provides a system that analyzes an email body, automatically determines its category, and further recognizes the user's emotions and reflects that information in a summary. This system acquires the number of recipients of the email, extracts the first part of the email body to generate a summary, inserts the generated summary at the beginning of the email body, and sends the email body with the summary. It can also analyze the user's emotions using an emotion engine, further subdivide the email category, and add emotional information to the summary.

[1816] Server-side processing

[1817] The server performs the following process each time a new email is sent:

[1818] 1. Email Analysis

[1819] The server analyzes the content of the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). Furthermore, it uses an emotion engine to extract the user's emotions (e.g., joy, anger, sadness, etc.) from the body of the email.

[1820] 2. Obtaining the number of senders

[1821] The server obtains the number of recipients listed in the To, CC, and BCC fields of the email and records this number as the number of recipients.

[1822] 3. Summary Generation

[1823] The server extracts the first 200 characters of the email body and sets it as a summary, which is used to succinctly express the important content of the email.

[1824] 4. Generating a summary

[1825] The server generates a "summary of this email" by combining the category based on the analysis results, the number of recipients, the summary text, and the emotional information extracted from the emotion engine.

[1826] Terminal side processing

[1827] The terminal performs the following process when the user sends an email.

[1828] 1. Email Request

[1829] When a user enters the email body on the email composition screen and presses the send button, the device sends an email analysis request to the server via the extension, which includes the email body, subject, and recipient information.

[1830] 2. Receiving a response from the server

[1831] The terminal receives summary information returned from the server, which includes the email category, the number of recipients, a summary, and the user's emotional information.

[1832] 3. Update the email body

[1833] The terminal adds the received summary information to the beginning of the mail body, and generates a new mail body with the summary.

[1834] 4. Send email

[1835] Finally, the terminal sends the new mail body with the summary to the user's intended recipient.

[1836] User operations

[1837] The user performs the following operations:

[1838] 1. Create an email

[1839] The user opens the email composition screen as usual and enters the recipient, subject, and body of the email.

[1840] 2. Send email

[1841] When the user presses the send button, a summary and emotional information are automatically generated and inserted at the beginning of the email body, after which the email is sent to the recipient.

[1842] Explanation with a concrete example

[1843] For example, suppose a user creates an email like this:

[1844] Subject: Regarding deadline extension

[1845] Thank you for your continued support. This is Suzuki from the company.

[1846] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1847] When this email is sent, the server analyzes the text and determines the category as "Contact," and uses the emotion engine to recognize the emotion as "Impatience." The server then obtains the number of recipients as 1. It generates a summary by extracting the first 200 characters and creates the following summary:

[1848] Summary of this email

[1849] Category: Contact

[1850] Number of senders: 1

[1851] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1852] Emotion: Impatience

[1853] This summary will be inserted at the beginning of the email body, and will look like this:

[1854] Summary of this email

[1855] Category: Contact

[1856] Number of senders: 1

[1857] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1858] Emotion: Impatience

[1859] Subject: Regarding deadline extension

[1860] Thank you for your continued support. This is Suzuki from the company.

[1861] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1862] Ultimately, users can send emails that are properly structured and contain emotional information without any special operations, making it easier for recipients to understand the content. In this way, the present invention provides a system that helps email recipients quickly assess the content and improves work efficiency.

[1863] The processing flow will be explained below.

[1864] Step 1:

[1865] The user opens the email creation screen and enters the recipient, subject, and body of the email. This is the normal email creation process.

[1866] Step 2:

[1867] The user clicks the "Send" button. At this moment, the device starts pre-processing for sending the email.

[1868] Step 3:

[1869] The terminal's extension function is launched and acquires the body, subject, and recipient information of the email currently being composed.

[1870] Step 4:

[1871] The terminal generates a request to send the acquired email body, subject, and destination information to the server. The request includes the email body text and destination information.

[1872] Step 5:

[1873] The server receives the request and begins parsing the email body.

[1874] Step 6:

[1875] The server analyzes the email body and automatically determines the category of the email based on specific keywords (e.g., "contact," "task," etc.). The category is determined, for example, as follows:

[1876] "if (emailBody.includes('Tasks')) { category = 'Tasks';}"

[1877] "else if (emailBody.includes('Contact')) { category = 'Contact';}"

[1878] "else { category = 'Other';}"

[1879] Step 7:

[1880] The server uses an emotion engine to recognize the user's emotions from the email body. For example, it uses natural language processing technology to analyze emotion-related words and context in the body of the email. The recognized emotions are specifically classified as "joy," "anger," "sadness," etc.

[1881] Step 8:

[1882] The server obtains the number of recipients based on the destination information, which can be easily obtained from the email header information.

[1883] Step 9:

[1884] The server extracts the first 200 characters of the email body and generates a summary that summarizes the important parts of the email body. For example, it is extracted as "let summaryText = emailBody.substring(0, 200);".

[1885] Step 10:

[1886] The server generates a summary by combining the category based on the analysis results, the number of senders, the summary text, and the emotion information extracted from the emotion engine. The generated summary has the following format:

[1887] "Summary of this email\nCategory: ${category}\nNumber of recipients: ${recipientCount}\nSummary: ${summaryText}\nEmotion: ${emotion}"

[1888] Step 11:

[1889] The server returns the generated summary to the terminal.

[1890] Step 12:

[1891] The terminal receives the response from the server and obtains the summary information.

[1892] Step 13:

[1893] The summary information received by the terminal is inserted at the beginning of the email body. The new email body will look like this:

[1894] "let updatedEmailBody = ${summary}\n\n${emailBody}"

[1895] Step 14:

[1896] The terminal generates a new email body with a summary and resumes the email sending process.

[1897] Step 15:

[1898] The device sends the updated email body to the recipient, and the email is sent.

[1899] Example 2

[1900] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1901] In recent years, the use of email has increased, and recipients are being asked to process large volumes of emails effectively. However, many emails are lengthy, making it difficult to grasp important information and understand the emotional nuances at a glance. Therefore, there is a need for a method that allows recipients to quickly understand the content of emails and respond appropriately. Conventional email systems do not adequately provide automatic functions for categorizing emails or determining their emotional content, and this lack is particularly evident in business situations.

[1902] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1903] In this invention, the server includes means for automatically determining the category and emotional information by analyzing the email body, means for acquiring the number of recipients of the email, means for extracting the first part of the email body to generate a summary, means for inserting the generated summary at the beginning of the email body, and means for sending the email body with the summary. This allows the content of the email to be presented in a concise and easy-to-understand format, enabling the recipient to quickly understand the main information and emotional nuances.

[1904] "Means for automatically determining category and emotion information by analyzing the body of an email" refers to a device or program that has the function of analyzing the content of an email and automatically identifying the category and emotion from the content using a text analysis engine or an emotion analysis engine.

[1905] The "means for acquiring the number of recipients of an e-mail" is a device or program that has the function of counting the number of recipients from an e-mail destination list and collecting that information.

[1906] The "means for extracting the first part of the email body and generating a summary" refers to a device or program that has the function of extracting a certain number of first characters from the email body and summarizing them as a concise summary.

[1907] The "means for inserting the generated summary at the beginning of the email body" refers to a device or program that has the function of adding the generated summary or analysis results to the beginning of the email body and creating an updated email body.

[1908] The "means for sending a mail body with a summary" is a device or program that has the function of sending an email containing an updated mail body to a specified recipient.

[1909] This section describes an embodiment of the present invention. This embodiment provides a system that analyzes the text of an email, automatically determines the category and emotional information, and generates an outline that reflects the results in a summary. This system is composed of a server and a terminal.

[1910] Each time an email is sent, the server performs the following process. First, the server analyzes the email body. Specifically, it uses a text analysis engine (e.g., Google Cloud Natural Language API) to analyze the body and determine the email category based on specific keywords and context. At the same time, it uses an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) to extract the user's emotional information (joy, anger, sadness, etc.) from the body of the email.

[1911] Next, the server extracts the number of recipients from the To, CC, and BCC fields of the email. This is recorded as the number of recipients of the email. The server then extracts the first 200 characters of the email body and uses this as a summary. This summary is used to concisely express the important content of the email.

[1912] The server then generates a summary based on the analysis results, combining the category, number of recipients, summary text, and sentiment information. This summary is saved as a "summary of this email."

[1913] When the user presses the send button, the terminal sends an email analysis request to the server. This request includes the email body, subject, and recipient information. After receiving a response from the server, the terminal adds the summary information to the beginning of the email body to generate a new email body with the summary. Finally, the terminal sends the email with the summary to the recipient specified by the user.

[1914] Users simply enter the recipient, subject, and message body on the email composition screen as usual and press the send button. This action sends a properly structured email that includes a summary and emotional information without requiring any special operations.

[1915] For example, if a user creates an email like this:

[1916] Subject: Regarding deadline extension

[1917] Thank you for your continued support. This is Suzuki from the company.

[1918] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1919] The server analyzes the text and determines the category as "Contact," and uses the emotion engine to identify the emotion as "Impatience." The server then obtains the number of recipients as 1. The server extracts the first 200 characters to generate a summary, creating the following:

[1920] Summary of this email

[1921] Category: Contact

[1922] Number of senders: 1

[1923] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1924] Emotion: Impatience

[1925] This summary will be inserted at the beginning of the email body, and will look like this:

[1926] Summary of this email

[1927] Category: Contact

[1928] Number of senders: 1

[1929] Summary: Thank you for your continued support. This is Suzuki from the company. I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1930] Emotion: Impatience

[1931] Subject: Regarding deadline extension

[1932] Thank you for your continued support. This is Suzuki from the company.

[1933] I would like to extend the deadline for this project for the following reasons. My specific proposal is as follows...

[1934] In this way, the present invention provides a system that helps the recipient of the mail to quickly judge the content and improves business efficiency.

[1935] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1936] Server-side processing

[1937] Step 1: Email Analysis

[1938] The server takes as input the body of the email the user is about to send. It uses a text analysis engine (e.g., Google Cloud Natural Language API) to analyze the body of the email and extract specific keywords and context. Based on this analysis, it determines the email category (e.g., "contact" or "task"). It also uses an emotion engine (e.g., IBM Watson or Microsoft Azure Emotion API) to extract the user's emotional information (e.g., joy, anger, sadness) from the body of the email. As a result of this data processing and calculation, it outputs category information and emotional information.

[1939] Step 2: Get the number of senders

[1940] The server takes the email's To, CC, and BCC fields as input. It counts the number of recipients from these fields and outputs that information as the number of recipients. This step simply counts the email addresses listed in each field.

[1941] Step 3: Generate a summary

[1942] The server takes the first part of the email body (e.g., the first 200 characters) as input. It extracts this part of the body and sets it as the summary. It outputs the extracted part as the summary.

[1943] Step 4: Generate a summary

[1944] The server inputs the category information, emotion information, number of recipients, and summary obtained in steps 1, 2, and 3. It combines these to generate and output a "summary of this email."

[1945] Terminal side processing

[1946] Step 1: Email Sending Request

[1947] The user enters the body, subject, and recipient information on the email creation screen and presses the send button. The terminal receives this information as input and sends it to the server as an email analysis request. Specifically, the terminal sends the body, subject, and recipient information of the email to the server.

[1948] Step 2: Receiving a response from the server

[1949] The terminal receives summary information returned from the server as input. This summary information includes category information, emotion information, the number of senders, and a summary. This information is then output as material for generating a new email body.

[1950] Step 3: Update the email body

[1951] The terminal takes the summary information received in step 2 and the original email body as input. It adds the summary information to the beginning of the email body to generate a new email body. This operation outputs the email body with the summary.

[1952] Step 4: Send email

[1953] The user sends the new email body with the summary to the intended recipient. This step involves sending the updated email body using the standard email sending process.

[1954] User operations

[1955] Step 1: Create an email

[1956] The user opens a mail composition screen as usual and enters the recipient, subject, and body of the message. This information becomes the input data for subsequent processing steps.

[1957] Step 2: Send an email

[1958] When the user presses the send button, the device automatically generates a summary and emotional information and inserts them at the beginning of the email body.The device then sends the email to the server.This operation ensures that the email, including the summary and emotional information, is delivered to the recipient.

[1959] Through the above processing steps, the present invention is a system that presents the contents of an email in a concise and easy-to-understand format, allowing the recipient to quickly understand the main information and emotional nuances.

[1960] (Application example 2)

[1961] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1962] In conventional email systems, it was difficult for recipients to quickly and accurately understand the contents of emails, increasing the likelihood of missing important information. Furthermore, because emails did not contain emotional information, it was difficult for recipients to understand the sender's intentions and emotions. Furthermore, there was a lack of effective ways to communicate promotional and campaign information to users in physical stores.

[1963] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically determining the category by analyzing the email body, means for acquiring the number of recipients of the email, means for extracting the first part of the email body and generating a summary, means for inserting the generated summary at the beginning of the email body, means for sending the email body with the summary, and means for recognizing the emotion of the email and reflecting that information in the summary. This allows the recipient to quickly and accurately understand the content of the email and the sender's intentions and emotions. It also makes it possible to effectively communicate information about promotions and campaigns at physical stores to users.

[1964] "Means for automatically determining the category by analyzing the body of the email" is a function that analyzes the content of the email and classifies the email into an appropriate category based on that content.

[1965] The "means for obtaining the number of recipients of an email" is a function for obtaining the number of recipients listed in the To, CC, and BCC fields of an email.

[1966] The "means for extracting the first part of the email body and generating a summary" is a function that extracts a certain portion of the first part of the email body and generates a short sentence based on that portion to express the summary of the email.

[1967] "Means for inserting the generated summary at the beginning of the email body" is a function for adding the generated summary text and category information to the beginning of the email body.

[1968] The "means for sending an email body with a summary" is a function for sending an email body with a summary attached to the recipient.

[1969] "Means of recognizing the emotion of an email and reflecting that information in the summary" is a function that analyzes the email body to recognize the emotion of the sender and adds that emotional information to the summary.

[1970] "Judgment based on specific keywords" is a method of classifying and evaluating emails based on specific keywords in the email body.

[1971] "Obtaining a positive or negative sentiment score" is a method of quantitatively evaluating the sentiment of the email body and scoring it as positive or negative.

[1972] System program generation

[1973] The server analyzes the email body and automatically determines the category. This analysis uses Natural Language Processing (NLP) technology, performing specific keyword analysis and sentiment analysis to obtain a positive or negative sentiment score. It also obtains the number of recipients of the email and extracts the first 200 characters of the email body to generate a summary.

[1974] Processing Description

[1975] The server-side program operates as follows:

[1976] Email Analysis

[1977] The server analyzes the body of the received email. The analysis uses Python NLP libraries (e.g., NLTK, TextBlob). This detects specific keywords in the email and automatically determines the category. TextBlob is also used to analyze the sentiment within the email and obtain a positive or negative sentiment score.

[1978] Get the number of senders

[1979] The server gets the number of recipients listed in the To, CC, and BCC fields of the email. This information is extracted from the send request.

[1980] Summary generation

[1981] The server extracts the first 200 characters of the email body and generates a summary based on that, which succinctly summarizes the email's key content.

[1982] Summary generation and insertion

[1983] The generated summary, category information, sentiment score, and number of recipients information are combined to generate a final summary, which is inserted at the beginning of the email body.

[1984] Send email

[1985] Send the email body with the final summary to the recipient.

[1986] Terminal side processing

[1987] When a user composes an email as usual and presses the send button, the program on the terminal sends an email analysis request to the server via the extension. The program receives the summary information returned from the server and inserts it at the beginning of the email body.

[1988] Specific examples

[1989] If a user composes an email like this:

[1990] Subject: Sale Announcement

[1991] Dear Customer,

[1992] This weekend, we're having a special sale in our store. Come and take advantage of 20% off all products. More details below...

[1993] The server analyzes the email body, determines the category as "Promotion", calculates the sentiment score as "Positive", and obtains the number of recipients as 1. It generates a summary by extracting the first 200 characters and generates the following:

[1994] Summary of this email

[1995] Category: Promotion

[1996] Number of senders: 1

[1997] Summary: Dear customers, we are holding a special sale in our store this weekend. Please come and take advantage of this opportunity to get 20% off all products. Further details are as follows...

[1998] Emotion: Positive

[1999] This summary will be inserted at the beginning of the email body and will look something like this:

[2000] Summary of this email

[2001] Category: Promotion

[2002] Number of senders: 1

[2003] Summary: Dear customers, we are holding a special sale in our store this weekend. Please come and take advantage of this opportunity to get 20% off all products. Further details are as follows...

[2004] Emotion: Positive

[2005] Subject: Sale Announcement

[2006] Dear Customer,

[2007] This weekend, we're having a special sale in our store. Come and take advantage of 20% off all products. More details below...

[2008] Example prompts to input to a generative AI model:

[2009] "Please analyze the content of this email, determine its category, recognize its sentiment, and create a summary."

[2010] Example of email content:

[2011] "Dear customers, we are having a special sale in our store this weekend. We are offering 20% ​​off all products, so please come and visit us. More details below..."

[2012] Hardware and software used

[2013] The hardware used is a smartphone, and the software uses Python, NLP libraries (NLTK, TextBlob), and smartphone application development frameworks (e.g., React Native, Swift, Kotlin).

[2014] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2015] Step 1:

[2016] The user creates an email. The recipient, subject, and body of the email are entered on the email creation screen. The input includes the email body and recipient information. When the user presses the send button, the device sends an email analysis request to the server.

[2017] Step 2:

[2018] The server receives an email analysis request, which includes the email body, subject, and recipient information. The server analyzes the content to identify email categories and sentiment. This process uses NLP libraries such as Python's NLTK or TextBlob to extract specific keywords and sentiment scores.

[2019] Input: Email body, subject, recipient information

[2020] Output: Email category, sentiment score

[2021] Step 3:

[2022] The server obtains the number of recipients of the email. It counts the number of recipients listed in the To, CC, and BCC fields. This generates the number of recipients information.

[2023] Input: To, CC, BCC information

[2024] Output: Number of recipients

[2025] Step 4:

[2026] The server extracts the first 200 characters of the email body and generates a summary based on them. This summary is generated to concisely express the important content of the email.

[2027] Input: Email body

[2028] Output: Summary

[2029] Step 5:

[2030] The server combines the email category, sentiment score, number of recipients, and the generated summary to generate a summary, which is then added to the beginning of the email body.

[2031] Input: Email category, sentiment score, number of recipients, summary

[2032] Output: Summary

[2033] Step 6:

[2034] The server inserts the generated summary at the beginning of the email body, thus creating a new email body with the summary.

[2035] Input: Summary, email body

[2036] Output: Email body with summary

[2037] Step 7:

[2038] The server sends the email body with the summary to the terminal. The terminal receives this information and displays the email in a format with the summary added to the beginning of the email body.

[2039] Input: Email body with summary

[2040] Output: Send to terminal

[2041] Step 8:

[2042] The terminal transmits the email body with the summary to the recipient, so that the recipient can receive the email with the summary.

[2043] Input: Email body with summary

[2044] Output: Send to recipient

[2045] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2046] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2047] 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 the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2048] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2049] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2050] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2051] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2052] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2053] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2054] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2055] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2056] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2057] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2058] 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.

[2059] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2060] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2061] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2062] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2063] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2064] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2065] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2066] The following is further disclosed regarding the above embodiment.

[2067] (Claim 1)

[2068] A method to analyze the body of an email and automatically determine the category,

[2069] A means for obtaining the number of recipients of the email;

[2070] A means for extracting the first part of the email body and generating a summary;

[2071] A means for inserting the generated summary at the beginning of the email body;

[2072] a means for sending an email body with a summary;

[2073] A system including:

[2074] (Claim 2)

[2075] 2. The system according to claim 1, wherein the category of an email is determined based on a specific keyword.

[2076] (Claim 3)

[2077] The system of claim 1, wherein the system extracts the first 200 characters of the email body to generate a summary.

[2078] "Example 1"

[2079] (Claim 1)

[2080] A method to analyze the body of an email and automatically determine the category,

[2081] A means for obtaining the number of recipients of the email;

[2082] A means for extracting the first part of the email body and generating a summary;

[2083] A means for inserting the generated summary at the beginning of the email body;

[2084] a means for sending an email body with a summary;

[2085] A means for determining a category based on keywords using natural language processing technology;

[2086] a means for sending an email analysis request to a server;

[2087] means for receiving summary information from the server and updating the email body;

[2088] A system including:

[2089] (Claim 2)

[2090] 2. The system according to claim 1, wherein the category of an email is determined based on a specific keyword.

[2091] (Claim 3)

[2092] The system of claim 1, wherein the system extracts the first 200 characters of the email body to generate a summary.

[2093] "Application Example 1"

[2094] (Claim 1)

[2095] A method to analyze the body of an email and automatically determine the category,

[2096] A means for obtaining the number of recipients of the email;

[2097] A means for extracting the first part of the email body and generating a summary;

[2098] A means for inserting the generated summary at the beginning of the email body;

[2099] a means for sending an email body with a summary;

[2100] A means for analyzing and summarizing customer correspondence emails and notifications in the virtual store;

[2101] a means for using the generative AI model and prompts in generating the summary;

[2102] A system including:

[2103] (Claim 2)

[2104] 2. The system according to claim 1, wherein the category of an email is determined based on a specific keyword.

[2105] (Claim 3)

[2106] The system of claim 1, wherein the system extracts the first 200 characters of the email body to generate a summary.

[2107] "Example 2: Combining Emotion Engines"

[2108] (Claim 1)

[2109] A means for automatically determining category and emotional information by analyzing the body of an email;

[2110] A means for obtaining the number of recipients of the email;

[2111] A means for extracting the first part of the email body and generating a summary;

[2112] A means for inserting the generated summary at the beginning of the email body;

[2113] a means for sending an email body with a summary;

[2114] A system including:

[2115] (Claim 2)

[2116] 2. The system according to claim 1, wherein the category and sentiment information of an email are determined using specific keywords and an analysis engine.

[2117] (Claim 3)

[2118] The system of claim 1, wherein the system extracts the first 200 characters of the email body to generate a summary.

[2119] "Application example 2 when combining emotion engines"

[2120] (Claim 1)

[2121] A method to analyze the body of an email and automatically determine the category,

[2122] A means for obtaining the number of recipients of the email;

[2123] A means for extracting the first part of the email body and generating a summary;

[2124] A means for inserting the generated summary at the beginning of the email body;

[2125] a means for sending an email body with a summary;

[2126] A way to recognize the sentiment of an email and reflect that information in the summary,

[2127] A system including:

[2128] (Claim 2)

[2129] 2. The system according to claim 1, wherein the category of an email is determined based on a specific keyword.

[2130] (Claim 3)

[2131] The system of claim 1, wherein the system extracts the first 200 characters of the email body to generate a summary.

[2132] (Claim 4)

[2133] 10. The system of claim 1, wherein when analyzing the sentiment of an email, a positive or negative sentiment score is obtained. [Explanation of symbols]

[2134] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A method to analyze the body of an email and automatically determine the category, A means for obtaining the number of recipients of the email; A means for extracting the first part of the email body and generating a summary; A means for inserting the generated summary at the beginning of the email body; a means for sending an email body with a summary; A system including:

2. 2. The system according to claim 1, wherein the category of an email is determined based on a specific keyword.

3. 2. The system according to claim 1, wherein the first 200 characters of the email body are extracted to generate a summary.

Images