system

Abstract

We provide the system. [Solution] A device for acquiring user input data, A device that encrypts the aforementioned input data and transmits it to a device having a communication function, A device that analyzes text data decoded by the aforementioned communication device and determines that it is defamatory if it meets certain conditions, A device that generates a warning message based on the aforementioned judgment result and notifies the user, A device that displays the aforementioned warning message based on the input content in the transaction memo when the user conducts an electronic transaction, A system that includes this.

Description

Technical Field

[0004] , ,

[0005] , , ,

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In communication on the Internet, troubles caused by slander and inappropriate expressions are increasing. Such problems are particularly serious for young users and may cause mental stress. Conventional filtering technologies and post-monitoring systems have difficulty completely preventing such slander, and there is a demand for a system that can make accurate judgments in real time and give warnings to users immediately.

Means for Solving the Problems

[0005] This invention provides a system for monitoring user input in real time. Specifically, it acquires data entered by the user, encrypts it, and then transmits it to a communication device. The communication device decrypts the received encrypted data and uses an analysis algorithm to determine whether the text data is defamatory. Based on this determination, it generates a warning message as needed and notifies the user at an appropriate time, thereby preventing the posting of defamatory content.

[0006] A "user" is the entity that operates and inputs data into a system, and is usually a human user.

[0007] "Input data" refers to information that a user provides to the system via a communication device, and includes strings of characters and other digital data.

[0008] "Encryption" is a technology that transforms data using a specific algorithm to protect it from unauthorized access when it is transmitted.

[0009] "Communication equipment" refers to devices that send, receive, and process data, and includes servers and network terminals.

[0010] "Decryption" is the process of restoring encrypted data to its original format, and it is carried out using appropriate keys and algorithms.

[0011] "Analysis" is the act of evaluating acquired data and interpreting or judging its content based on specific conditions.

[0012] "Defamation" refers to words or actions that unfairly belittle others, and should be detected by the system as something to be removed or flagged for warning.

[0013] A "warning message" is information that the system notifies the user based on its own judgment, and may include content that points out inappropriate input and prompts reconsideration. [Brief explanation of the drawing]

[0014] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This embodiment provides a system aimed at preventing defamation and slander based on real-time input from users. This system includes a series of processes from the initial stage where the user inputs information via a terminal, through analysis by communication equipment, to the final display of a warning.

[0036] As a user begins typing on the terminal, the input is captured sequentially by the terminal. The terminal monitors this input data in real time and encrypts the captured data using a security protocol. The encrypted data is then transmitted to a communication device via a secure network connection. This communication device is typically a server located in a data center.

[0037] The server immediately decrypts the received data and analyzes it using natural language processing (NLP) techniques. This analysis employs machine learning algorithms to determine whether the data contains specific words or phrases related to defamation.

[0038] For example, if a user types "AA is stupid," the server analyzes this input and determines that the word "stupid" contributes to a negative rating. If this result exceeds the threshold, the server immediately generates feedback and sends the result back to the terminal. The feedback includes a warning message to inform the user that it may be defamatory. This warning encourages the user to review their input and try to change it to a more appropriate expression.

[0039] As described above, the present invention can improve the quality of communication and prevent problems on the internet by evaluating user input in a short time and immediately providing a response as needed.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The terminal captures data entered by the user using the keyboard in real time. This input data is temporarily stored in a buffer sequentially.

[0043] Step 2:

[0044] The device encrypts the captured input data. Standard encryption algorithms are used to ensure data security. This encrypted data is then ready to be transmitted to communication devices over the network.

[0045] Step 3:

[0046] The server receives encrypted data sent from the terminal. The received data is immediately decrypted using the appropriate key and returned to the original text data.

[0047] Step 4:

[0048] The server analyzes the decrypted text data using natural language processing. This includes text mining using machine learning algorithms to detect words and phrases that constitute defamation or libel.

[0049] Step 5:

[0050] The server determines whether the input data is defamatory based on the analysis results. The algorithm considers it defamatory if it reaches a score that exceeds a pre-set threshold. In this case, evidence of the defamatory determination is also recorded.

[0051] Step 6:

[0052] The server generates feedback based on its judgment. This feedback includes a warning message for the user, informing them that the content contains defamatory language.

[0053] Step 7:

[0054] The terminal displays feedback received from the server to the user. The user sees a warning message and has an opportunity to review their input. This display usually appears as a pop-up next to the input field.

[0055] (Example 1)

[0056] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0057] Online defamation and slander degrade the quality of communication and infringe upon individual personality rights and human rights. However, current technology is insufficient to detect these in real time and issue warnings proactively. To address this challenge, there is a need for a system that effectively detects defamation and slander at the user input stage and provides a swift response.

[0058] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0059] In this invention, the server includes means for sequentially acquiring user input text, means for securely transmitting the input text to a communication device using an encryption protocol, and means for decrypting the data received by the communication device, analyzing its content using natural language processing technology, and identifying defamatory elements. This makes it possible to detect the risk of defamation in real time and immediately warn the user.

[0060] A "user" is the entity that operates the system and generates input data.

[0061] "Input text" refers to text data that a user provides to the system through their device.

[0062] An "encryption protocol" is a set of rules and techniques used to ensure the security of data.

[0063] "Communication equipment" refers to a device used to transmit data to another device or system.

[0064] "Natural language processing technology" is the technology that enables computers to understand and process human language.

[0065] "Defamatory elements" are words or phrases that may harm a specific individual or group.

[0066] "Warning information" refers to messages displayed to the user to alert them about the input data.

[0067] A "generative AI model" is an artificial intelligence model that has been trained using historical data and is used for analyzing and predicting text data.

[0068] This invention is a system that instantly detects whether defamatory elements are present in text input by a user in real time and displays warning information. This system consists of a user, a terminal, and a server.

[0069] When a user enters text data into a terminal, the terminal captures that data sequentially. The terminal encrypts the captured input text using AES (Advanced Encryption Standard) and sends it to a server, which is a communication device, using a secure protocol (e.g., TLS). This encryption ensures the confidentiality of the data.

[0070] The server receives encrypted data, verifies the digital signature, and then decrypts it. Afterward, it uses natural language processing techniques to analyze the defamatory elements within the text. Specifically, it uses a generative AI model to identify defamatory elements based on past data. This generative AI model utilizes a model like BERT (Bidirectional Encoder Representations from Transformers) to achieve highly accurate analysis.

[0071] If defamatory elements are detected, the server generates appropriate warning information for the user and sends it back to the terminal. The terminal immediately displays this warning information to the user, prompting them to correct their input. This allows the user to review their inappropriate language and improve the quality of the conversation.

[0072] For example, if a user enters "○○ is stupid" into a community site, the AI ​​model will analyze that the word "stupid" contains negative elements and generate a warning message. An example of a prompt message could be: "Please evaluate whether the entered text constitutes defamation. Text: '○○ is stupid'." In this way, a system is built to support smooth and healthy communication on the internet.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The user enters text into the device. The characters being entered are captured sequentially. This string data is temporarily stored in the device's memory.

[0076] Step 2:

[0077] The terminal encrypts the captured input text using AES. The input text is converted into secure binary data by the encryption algorithm, and this encrypted data is generated as output. The encrypted data is sent to the server using a secure protocol.

[0078] Step 3:

[0079] The server receives the encrypted data, verifies the digital signature, and then decrypts it. The input is encrypted binary data, and after the decryption process, human-readable string data is output.

[0080] Step 4:

[0081] The server analyzes the decrypted text data using natural language processing techniques. Here, a generative AI model is employed to score the likelihood of defamation based on the input text. The input is the decrypted text, and the output is the score and the analysis results of the defamatory elements.

[0082] Step 5:

[0083] If the score generated by the server exceeds a set threshold, it is judged to be defamation. Based on this analysis, warning information is generated. The input is the score and analysis result, and the output is a warning message to notify the user.

[0084] Step 6:

[0085] The server sends a warning message to the terminal. The terminal displays the received message to the user, prompting them to review their input. The input is the warning message data, and the output is the warning information displayed on the user's screen. This display gives the user an opportunity to improve their expression.

[0086] (Application Example 1)

[0087] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0088] In electronic transactions, the inclusion of potentially defamatory language in transaction memos and comment sections by users can cause problems and hinder safe and smooth transactions.

[0089] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0090] In this invention, the server includes a device for acquiring user input data, a device for encrypting the input data and transmitting it to a device having a communication function, a device for analyzing the text data decrypted by the device having a communication function and determining that it is defamatory if certain conditions are met, a device for generating a warning message based on the determination result and notifying the user, and a device for displaying the aforementioned warning message based on the input content in the transaction memo when the user is conducting an electronic transaction. This makes it possible for users to avoid defamation even during transactions and promotes safe and reliable communication.

[0091] The term "user" refers to a trader who uses this system to input data.

[0092] "Input data" refers to text information or strings of characters entered by a user using an electronic device.

[0093] "Encryption" is the process of transforming input data using a specific algorithm to protect it from unauthorized access and leakage.

[0094] A "device with communication capabilities" refers to a device that can send and receive data over a network, and generally includes servers and routers.

[0095] "Decryption" refers to the technique of restoring encrypted data to its original, readable format.

[0096] "Analysis" is the process of analyzing input data using specific algorithms and methods, and then evaluating the results.

[0097] "Specific conditions" refer to defining words, phrases, or patterns that serve as criteria for determining whether something constitutes defamation or libel.

[0098] "Judgment" is the process of determining whether the input content constitutes defamation or libel based on the analyzed data.

[0099] A "warning message" is a notification displayed as a warning when the content entered by the user may be inappropriate.

[0100] "Electronic transaction" is a term that refers to transactions conducted online for the purpose of exchanging goods and services.

[0101] "Transaction memo" refers to a field in electronic transactions where users can freely enter comments or notes.

[0102] The system implementing this invention provides a secure electronic transaction environment by analyzing user input data in real time and preventing defamatory expressions.

[0103] The server receives data entered by the user via the terminal and encrypts it using encryption technology. The encryption library "cryptography.fernet" is used for encryption. A secure network connection is established as the means of communication, and data is sent and received to the server using the "requests" library. After decrypting the received data, the server performs analysis using natural language processing technology. In this analysis, machine learning algorithms are used to determine whether certain conditions are met and to assess the possibility of defamation.

[0104] Users can enter notes or comments during transactions, but if the content is determined to be defamatory, the server immediately generates a warning message and notifies the user. This allows users to correct inappropriate language during transactions, ensuring safe and smooth transactions.

[0105] For example, if a user enters "This item is ridiculously overpriced" in the transaction memo, the server will detect this phrase and display a warning message, thus preventing misunderstandings and problems.

[0106] Thus, an example of a prompt message would be, "How should a warning message be displayed if a user might use inappropriate language in a remittance note in an electronic payment service?"

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] The device captures user input data. This input data consists of strings entered by the user, and the device monitors this data in real time and temporarily stores it as text data.

[0110] Step 2:

[0111] The terminal encrypts the input data. The terminal uses "cryptography.fernet" to encrypt this text data and generate encrypted data. This encrypted data is intended to prevent unauthorized access and information leakage from external sources.

[0112] Step 3:

[0113] The terminal sends encrypted data to a device with communication capabilities. This encrypted data is then sent to the server using the "requests" library via a secure network connection. The input here is the encrypted data, and the output is the status of the transmission to the server.

[0114] Step 4:

[0115] The server decrypts the received data. The server takes the encrypted data sent from the terminal, decrypts it, and reconstructs the original text data. In this decryption step, the input is the encrypted data and the output is the original text data.

[0116] Step 5:

[0117] The server analyzes the text data. The server uses natural language processing techniques to analyze the decoded text data. Using machine learning algorithms, it determines whether the text contains words or phrases related to defamation and generates the results. The input is text data, and the output is the analysis result.

[0118] Step 6:

[0119] The server generates a warning message based on the analysis results. If the analysis results meet certain conditions, the server creates a warning message and constructs data to present to the user. The input is the analysis results, and the output is the warning message.

[0120] Step 7:

[0121] The terminal displays a warning message received from the server to the user. The terminal receives this warning message and displays it on the user's screen to prompt correction of the input. The input is the data of the warning message, and the output is a visual warning display to the user.

[0122] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0123] In this embodiment, by integrating an emotion engine in addition to a defamation detection function for user input, a system is realized that more accurately recognizes the user's emotional state and provides appropriate interaction. This system includes an integrated process from the initial stage of user input through the terminal to the eventual display of warnings and feedback.

[0124] When a user enters text into their device, the data is encrypted and sent to the server. The server decrypts the received data and first analyzes the input using natural language processing (NLP) to determine if it contains defamation or libel. Simultaneously, an emotion engine is activated to analyze the emotions associated with the input.

[0125] The emotion engine utilizes machine learning algorithms to determine whether the input text evokes positive or negative emotions. This allows it to recognize the user's emotional state in real time and determine when attention is needed, especially if negative emotions are strong. For example, if a user enters the phrase "I really hate it," the emotion engine interprets this as an indication of heightened negative emotions.

[0126] Based on the results of the defamation detection and emotional recognition, the server generates a warning message. This message is then adjusted to be more appropriate and considerate, taking into account the user's emotional state. For example, a warning such as, "This expression may hurt others. Please reconsider," might be displayed.

[0127] Ultimately, the device presents the user with feedback received from the server, prompting the user to revise their input based on that feedback. Through this process, it becomes possible to prevent defamation and slander while also providing flexible responses that address the user's emotional needs.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] The device captures text data entered by the user using the keyboard in real time. This data is temporarily stored in the device's memory. During this process, the user can continue typing as usual.

[0131] Step 2:

[0132] The terminal encrypts the entered text data and sends it to the server using a secure communication protocol. This encryption process is crucial for maintaining data confidentiality.

[0133] Step 3:

[0134] The server receives the encrypted data from the terminal and decrypts it using the appropriate key. This allows the original text data entered by the user who sent the data to be reconstructed.

[0135] Step 4:

[0136] The server analyzes the decoded text data using natural language processing (NLP) to determine whether or not it contains defamation. During this process, a pre-trained algorithm detects specific language patterns.

[0137] Step 5:

[0138] The server activates the emotion engine and analyzes the emotional elements contained in the input. The emotion engine uses a machine learning model to determine whether the input represents a positive or negative emotion.

[0139] Step 6:

[0140] The server integrates the defamation detection results and the sentiment recognition results to generate an appropriate warning message. For example, if the text strongly expresses negative sentiment and is determined to be defamatory, the warning message will include the phrase, "This expression may offend others."

[0141] Step 7:

[0142] The terminal displays a warning message sent from the server to the user. This message is provided as a visual notification, such as a pop-up, giving the user an opportunity to review their input.

[0143] Step 8:

[0144] Users refer to the displayed warning messages and correct their input as needed. This feedback loop promotes interactive and secure communication.

[0145] (Example 2)

[0146] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0147] As information and communication environments develop, defamation and aggressive language have become a problem in online communication. Consequently, there is a growing need for systems that can appropriately recognize users' emotions and provide appropriate feedback in advance. This invention aims to prevent communication problems by accurately understanding users' emotional states and not only detecting aggressive language but also providing appropriate warnings tailored to their emotions.

[0148] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0149] In this invention, the server includes means for acquiring user input information, means for transmitting the input information to a communication device using data encryption technology, means for analyzing the text decrypted by the communication device and determining if it is an aggressive expression if it meets certain conditions, means for generating warning information based on the analysis results and notifying the user, means including an emotion analysis function that performs emotion analysis on the user's input text, means for identifying negative emotional states, and means for generating considerate warning information according to the emotional state. This makes it possible to analyze negative emotions and aggressive expressions in the text entered by the user in real time and provide appropriate feedback based on the results.

[0150] "User input information" refers to the text and data entered by the user through a terminal, before it is processed by the system.

[0151] "Data encryption technology" is a technology used to protect information from being deciphered by third parties when it is transmitted externally, and is used to ensure the confidentiality of information.

[0152] "Communication equipment" refers to devices and network environments used for sending and receiving data, and is used to exchange information between users and servers.

[0153] "Decryption" refers to the process of restoring encrypted information to its original state, a technique used to enable the recipient to read the data's contents.

[0154] "Analysis" refers to the process of analyzing data and information to extract useful information, and is performed in order for a system to understand the content of the input text.

[0155] "Specific conditions" refer to the criteria and rules set by the system to determine whether input data constitutes defamation or libel, and these are created based on past cases and statistical information.

[0156] "Aggressive language" refers to words or phrases that are offensive or potentially offensive to others, and can cause problems in online communication.

[0157] "Warning information" refers to a cautionary message that the system notifies the user of, intended to encourage them to review or improve their input.

[0158] "Emotional analysis function" refers to technology that analyzes the emotional state from text entered by the user and determines whether the emotion is positive or negative.

[0159] A "negative emotional state" refers to a negative emotional state detected by the system from user input, indicating a situation where a warning or follow-up is necessary.

[0160] "Considerate warning information" refers to warning information generated with the user's emotional state in mind, and is adjusted to provide more appropriate and emotionally sensitive content.

[0161] This invention provides a system that analyzes user input information and determines their emotional state in order to improve the quality of online communication. This system consists of a terminal, a communication device, and a server.

[0162] First, when a user enters text through their device, that input information is acquired in real time. At that time, the device encrypts the user's input information and sends it to the server while maintaining security. Common encryption methods such as AES (Advanced Encryption Standard) are used for encryption.

[0163] Next, the server decodes the received input information. It analyzes the received text data using natural language processing libraries such as Python and TENSORFLOW®. The purpose of the analysis is to detect offensive expressions contained in the input information, using a pre-configured terminology log.

[0164] The server also activates its sentiment analysis function, analyzing the user's emotions based on their input. Using machine learning algorithms, such as BERT (Bidirectional Encoder Representations from Transformers), it determines positive or negative emotions in real time. If strong negative emotions are detected, appropriate and considerate warning information is generated.

[0165] Finally, the warning information generated by the server is returned to the terminal and presented to the user visually. This encourages the user to review their input, thus preventing inappropriate online communication.

[0166] For example, if a user tries to post a negative comment on social media such as "I hate my job," the sentiment analysis function can identify this as a negative emotion and inform the user that the comment may be problematic.

[0167] An example of a prompt message is, "Analyze the sentiment contained in the text entered by the user and generate appropriate feedback. Text: 'XXX'." In this way, the present invention supports healthy user communication by integrating multiple technologies to provide appropriate feedback.

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] The user enters text.

[0171] The user enters text data such as comments and messages on the device, and this input information is captured by the device. This input information becomes the data for the next encryption step.

[0172] Step 2:

[0173] The terminal encrypts the input information and sends it to the server.

[0174] The terminal encrypts the acquired text data using encryption technologies such as AES. This encrypted data enables secure transfer to the server and guarantees the protection of the input information after transfer. The output is encrypted data.

[0175] Step 3:

[0176] The server decrypts the data.

[0177] The server performs a decryption process to return the received encrypted data back to its original text. After receiving the decrypted data, it becomes the input data for the next analysis step. The output is the original text data.

[0178] Step 4:

[0179] The server analyzes the text data and detects offensive expressions.

[0180] The server uses a natural language processing library to analyze text data. It determines whether specific keywords or phrases in the input text match past terminology records and generates output indicating whether they are offensive expressions.

[0181] Step 5:

[0182] The server performs sentiment analysis.

[0183] The server launches a machine learning model to analyze sentiment based on text data. It utilizes models such as BERT to determine whether the input represents positive or negative sentiment and outputs the result.

[0184] Step 6:

[0185] The server generates warning information and provides feedback to the user.

[0186] The server generates appropriate warning information based on the results of aggressive language and sentiment analysis, and sends it to the terminal as feedback. This feedback includes specific measures such as suggestions for improving language use, and the output is warning information notified to the user.

[0187] Step 7:

[0188] The device displays a warning message.

[0189] The terminal displays warning information received from the server to the user in a visible format. Here, the user can review their input and make corrections as needed, thus maintaining the health of online communication. The output is feedback that the user can see.

[0190] (Application Example 2)

[0191] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0192] In conventional electronic trading systems, users may conduct transactions while emotionally overwhelmed, potentially leading to inappropriate communication and defamation. To prevent such situations and promote appropriate communication, a system is needed that recognizes users' emotions in real time and provides appropriate feedback.

[0193] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0194] In this invention, the server includes means for acquiring user data input, means for encrypting the data input and transmitting it to an information processing device, means for analyzing the decrypted character data in the information processing device and determining defamation if certain conditions are met, means for analyzing the user's emotions based on the character data and determining the emotional state, means for generating an appropriate interaction based on the emotional state and notifying the user, and means for generating a warning message based on the determination result and notifying the user. This makes it possible to provide flexible and appropriate interactions according to the user's emotional state and prevent inappropriate communication.

[0195] "Means for obtaining user data input" refers to a function that receives data entered by a user into the system and collects that information for processing.

[0196] "Means of encrypting data input and transmitting it to an information processing device" refers to a method of protecting data input obtained from a user using encryption technology and securely delivering the data to the destination information processing device.

[0197] "A means of analyzing decrypted character data using an information processing device and determining if it constitutes defamation if it meets specific conditions" refers to a process of decrypting encrypted character data, analyzing its content, evaluating whether it matches pre-set criteria, and then considering it to be defamatory.

[0198] "A means of analyzing a user's emotions and determining their emotional state based on text data" refers to a function that analyzes the text data entered by the user to evaluate their emotions at that time and identify whether their emotional state is positive or negative.

[0199] "A means of generating appropriate interactions based on emotional state and notifying the user" refers to the process of creating and communicating messages and suggestions designed to allow the user to respond appropriately, based on the analyzed emotional state of the user.

[0200] "A means of generating a warning message based on the judgment result and notifying the user" refers to a function that, when something is judged to be defamatory, creates a warning message for the user based on that information and sends a notification.

[0201] The system for realizing this invention consists mainly of a user, a terminal, and a server. The user inputs data via the terminal. The terminal receives this data, encrypts it, and then sends it to the server.

[0202] The server first decodes the received data. Next, it analyzes the text data using natural language processing techniques and, if necessary, compares it against specific conditions to determine if it constitutes defamation. These conditions utilize a vocabulary list of defamatory terms based on past judgments. Simultaneously, it analyzes the user's emotional state using a machine learning algorithm based on the text data from the user. This allows it to determine if the user is emotionally agitated and generate appropriate feedback.

[0203] Feedback provides appropriate interactions based on the user's emotional state, including warning messages and correction suggestions. The generated warning messages also include suggestions for reviewing the user's input.

[0204] The implementation of this system can utilize Python libraries (e.g., Spacy, NLTK) and machine learning frameworks (e.g., TensorFlow) on the server side. These technologies enable efficient analysis of received data, allowing for sentiment analysis and feedback generation.

[0205] For example, if a user enters a negative phrase such as "Do something!" during an electronic transaction, the server can analyze this phrase to determine the user's emotional state and provide thoughtful feedback such as, "Could you please provide additional information so we can understand the situation better?"

[0206] An example of a prompt to input into a generative AI model is: "Classify the following user input as positive or negative, check for slander, and generate an appropriate feedback message: 'Do something!'" Using this prompt enables highly accurate feedback.

[0207] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0208] Step 1:

[0209] The user enters a message using the terminal. This input data is received by the terminal as text data, including the user's intentions and feelings. The terminal receives this data, encrypts it using an encryption algorithm, and sends it to the server for further processing.

[0210] Step 2:

[0211] The server receives encrypted data sent from the terminal. The original text data is extracted by decrypting the received data. The decrypted data is then analyzed using natural language processing (NLP) techniques to determine if it contains defamation. Specifically, words and phrases in the text are compared against a vocabulary list of defamatory terms.

[0212] Step 3:

[0213] The server utilizes machine learning algorithms to analyze emotions from the decoded data. It evaluates the emotional aspects of the input data and classifies them as positive or negative. This process determines the user's emotional state, and the result is reflected in the prompt text of the generating AI model.

[0214] Step 4:

[0215] The server generates feedback based on the analysis of emotions and slander. This feedback includes specific warning messages and messages suggesting further action. For example, if emotions are heightened, it will generate advice such as, "Let's calm down and think about the situation."

[0216] Step 5:

[0217] Finally, the server sends the generated feedback message to the device, notifying the user. The user can then review the message on their device and revise their input based on the feedback provided. This process gives the user an opportunity to avoid slander and maintain appropriate communication.

[0218] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0219] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0220] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0221] [Second Embodiment]

[0222] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0223] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0224] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0225] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0226] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0227] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0228] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0229] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0230] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0231] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0232] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0233] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0234] This embodiment provides a system aimed at preventing defamation and slander based on real-time input from users. This system includes a series of processes from the initial stage where the user inputs information via a terminal, through analysis by communication equipment, to the final display of a warning.

[0235] As a user begins typing on the terminal, the input is captured sequentially by the terminal. The terminal monitors this input data in real time and encrypts the captured data using a security protocol. The encrypted data is then transmitted to a communication device via a secure network connection. This communication device is typically a server located in a data center.

[0236] The server immediately decrypts the received data and analyzes it using natural language processing (NLP) techniques. This analysis employs machine learning algorithms to determine whether the data contains specific words or phrases related to defamation.

[0237] For example, if a user types "AA is stupid," the server analyzes this input and determines that the word "stupid" contributes to a negative rating. If this result exceeds the threshold, the server immediately generates feedback and sends the result back to the terminal. The feedback includes a warning message to inform the user that it may be defamatory. This warning encourages the user to review their input and try to change it to a more appropriate expression.

[0238] As described above, the present invention can improve the quality of communication and prevent problems on the internet by evaluating user input in a short time and immediately providing a response as needed.

[0239] The following describes the processing flow.

[0240] Step 1:

[0241] The terminal captures data entered by the user using the keyboard in real time. This input data is temporarily stored in a buffer sequentially.

[0242] Step 2:

[0243] The device encrypts the captured input data. Standard encryption algorithms are used to ensure data security. This encrypted data is then ready to be transmitted to communication devices over the network.

[0244] Step 3:

[0245] The server receives encrypted data sent from the terminal. The received data is immediately decrypted using the appropriate key and returned to the original text data.

[0246] Step 4:

[0247] The server analyzes the decrypted text data using natural language processing. This includes text mining using machine learning algorithms to detect words and phrases that constitute defamation or libel.

[0248] Step 5:

[0249] The server determines whether the input data is defamatory based on the analysis results. The algorithm considers it defamatory if it reaches a score that exceeds a pre-set threshold. In this case, evidence of the defamatory determination is also recorded.

[0250] Step 6:

[0251] The server generates feedback based on its judgment. This feedback includes a warning message for the user, informing them that the content contains defamatory language.

[0252] Step 7:

[0253] The terminal displays feedback received from the server to the user. The user sees a warning message and has an opportunity to review their input. This display usually appears as a pop-up next to the input field.

[0254] (Example 1)

[0255] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0256] Online defamation and slander degrade the quality of communication and infringe upon individual personality rights and human rights. However, current technology is insufficient to detect these in real time and issue warnings proactively. To address this challenge, there is a need for a system that effectively detects defamation and slander at the user input stage and provides a swift response.

[0257] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0258] In this invention, the server includes means for sequentially acquiring user input text, means for securely transmitting the input text to a communication device using an encryption protocol, and means for decrypting the data received by the communication device, analyzing its content using natural language processing technology, and identifying defamatory elements. This makes it possible to detect the risk of defamation in real time and immediately warn the user.

[0259] A "user" is the entity that operates the system and generates input data.

[0260] "Input text" refers to text data that a user provides to the system through their device.

[0261] An "encryption protocol" is a set of rules and techniques used to ensure the security of data.

[0262] "Communication equipment" refers to a device used to transmit data to another device or system.

[0263] "Natural language processing technology" is the technology that enables computers to understand and process human language.

[0264] "Defamatory elements" are words or phrases that may harm a specific individual or group.

[0265] "Warning information" refers to messages displayed to the user to alert them about the input data.

[0266] A "generative AI model" is an artificial intelligence model that has been trained using historical data and is used for analyzing and predicting text data.

[0267] This invention is a system that instantly detects whether defamatory elements are present in text input by a user in real time and displays warning information. This system consists of a user, a terminal, and a server.

[0268] When a user enters text data into a terminal, the terminal captures that data sequentially. The terminal encrypts the captured input text using AES (Advanced Encryption Standard) and sends it to a server, which is a communication device, using a secure protocol (e.g., TLS). This encryption ensures the confidentiality of the data.

[0269] The server receives encrypted data, verifies the digital signature, and then decrypts it. Afterward, it uses natural language processing techniques to analyze the defamatory elements within the text. Specifically, it uses a generative AI model to identify defamatory elements based on past data. This generative AI model utilizes a model like BERT (Bidirectional Encoder Representations from Transformers) to achieve highly accurate analysis.

[0270] If defamatory elements are detected, the server generates appropriate warning information for the user and sends it back to the terminal. The terminal immediately displays this warning information to the user, prompting them to correct their input. This allows the user to review their inappropriate language and improve the quality of the conversation.

[0271] For example, if a user enters "○○ is stupid" into a community site, the AI ​​model will analyze that the word "stupid" contains negative elements and generate a warning message. An example of a prompt message could be: "Please evaluate whether the entered text constitutes defamation. Text: '○○ is stupid'." In this way, a system is built to support smooth and healthy communication on the internet.

[0272] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0273] Step 1:

[0274] The user enters text into the device. The characters being entered are captured sequentially. This string data is temporarily stored in the device's memory.

[0275] Step 2:

[0276] The terminal encrypts the captured input text using AES. The input text is converted into secure binary data by the encryption algorithm, and this encrypted data is generated as output. The encrypted data is sent to the server using a secure protocol.

[0277] Step 3:

[0278] The server receives the encrypted data, verifies the digital signature, and then decrypts it. The input is encrypted binary data, and after the decryption process, human-readable string data is output.

[0279] Step 4:

[0280] The server analyzes the decrypted text data using natural language processing technology. Here, a generative AI model is utilized to score the likelihood of defamation based on the input text. The input is the decrypted text, and the output is the score and the analysis result of defamation elements.

[0281] Step 5:

[0282] If the score generated by the server exceeds the set threshold, it is determined as defamation. Based on this analysis result, warning information is generated. The input is the score and the analysis result, and a warning message for notifying the user is generated as the output.

[0283] Step 6:

[0284] The server sends the warning message to the terminal. The terminal displays the received message to the user and prompts the user to review the input content. The input is the warning message data, and the output is the warning information displayed on the user's screen. This display enables the user to have an opportunity to improve the expression.

[0285] (Application Example 1)

[0286] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0287] In electronic transactions, there is a problem that when a user inputs an expression that may be defamatory in a transaction memo or comment field, it can cause trouble and hinder a safe and smooth transaction.

[0288] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0289] In this invention, the server includes a device for acquiring user input data, a device for encrypting the input data and transmitting it to a device having a communication function, a device for analyzing the text data decrypted by the device having a communication function and determining that it is defamatory if certain conditions are met, a device for generating a warning message based on the determination result and notifying the user, and a device for displaying the aforementioned warning message based on the input content in the transaction memo when the user is conducting an electronic transaction. This makes it possible for users to avoid defamation even during transactions and promotes safe and reliable communication.

[0290] The term "user" refers to a trader who uses this system to input data.

[0291] "Input data" refers to text information or strings of characters entered by a user using an electronic device.

[0292] "Encryption" is the process of transforming input data using a specific algorithm to protect it from unauthorized access and leakage.

[0293] A "device with communication capabilities" refers to a device that can send and receive data over a network, and generally includes servers and routers.

[0294] "Decryption" refers to the technique of restoring encrypted data to its original, readable format.

[0295] "Analysis" is the process of analyzing input data using specific algorithms and methods, and then evaluating the results.

[0296] "Specific conditions" refer to defining words, phrases, or patterns that serve as criteria for determining whether something constitutes defamation or libel.

[0297] "Judgment" is the process of determining whether the input content constitutes defamation or libel based on the analyzed data.

[0298] A "warning message" is a notification displayed as a warning when the content entered by the user may be inappropriate.

[0299] "Electronic transaction" is a term that refers to transactions conducted online for the purpose of exchanging goods and services.

[0300] "Transaction memo" refers to a field in electronic transactions where users can freely enter comments or notes.

[0301] The system implementing this invention provides a secure electronic transaction environment by analyzing user input data in real time and preventing defamatory expressions.

[0302] The server receives data entered by the user via the terminal and encrypts it using encryption technology. The encryption library "cryptography.fernet" is used for encryption. A secure network connection is established as the means of communication, and data is sent and received to the server using the "requests" library. After decrypting the received data, the server performs analysis using natural language processing technology. In this analysis, machine learning algorithms are used to determine whether certain conditions are met and to assess the possibility of defamation.

[0303] Users can enter notes or comments during transactions, but if the content is determined to be defamatory, the server immediately generates a warning message and notifies the user. This allows users to correct inappropriate language during transactions, ensuring safe and smooth transactions.

[0304] For example, if a user enters "This item is ridiculously overpriced" in the transaction memo, the server will detect this phrase and display a warning message, thus preventing misunderstandings and problems.

[0305] Thus, as an example of a prompt sentence, it is utilized in the form of "When a user may use inappropriate expressions in a remittance memo in an electronic payment service, how do you display a warning message?"

[0306] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0307] Step 1:

[0308] The terminal captures the user's input data. The input data is the string entered by the user, and the terminal monitors this data in real time and temporarily holds it as text data.

[0309] Step 2:

[0310] The terminal encrypts the input data. The terminal uses "cryptography.fernet" to encrypt this text data and generates encrypted data. This encrypted data is for preventing unauthorized access from outside and information leakage.

[0311] Step 3:

[0312] The terminal transmits the encrypted data to a device having a communication function. Using the "requests" library via a secure network connection, this encrypted data is transmitted to the server. The input here is the encrypted data, and the output is the transmission status to the server.

[0313] Step 4:

[0314] The server decrypts the received data. The server obtains the encrypted data sent from the terminal, decrypts it, and reconstructs the original text data. The input in this decryption step is the encrypted data, and the output is the original text data.

[0315] Step 5:

[0316] The server analyzes the text data. The server uses natural language processing techniques to analyze the decoded text data. Using machine learning algorithms, it determines whether the text contains words or phrases related to defamation and generates the results. The input is text data, and the output is the analysis result.

[0317] Step 6:

[0318] The server generates a warning message based on the analysis results. If the analysis results meet certain conditions, the server creates a warning message and constructs data to present to the user. The input is the analysis results, and the output is the warning message.

[0319] Step 7:

[0320] The terminal displays a warning message received from the server to the user. The terminal receives this warning message and displays it on the user's screen to prompt correction of the input. The input is the data of the warning message, and the output is a visual warning display to the user.

[0321] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0322] In this embodiment, by integrating an emotion engine in addition to a defamation detection function for user input, a system is realized that more accurately recognizes the user's emotional state and provides appropriate interaction. This system includes an integrated process from the initial stage of user input through the terminal to the eventual display of warnings and feedback.

[0323] When a user enters text into their device, the data is encrypted and sent to the server. The server decrypts the received data and first analyzes the input using natural language processing (NLP) to determine if it contains defamation or libel. Simultaneously, an emotion engine is activated to analyze the emotions associated with the input.

[0324] The emotion engine utilizes machine learning algorithms to determine whether the input text evokes positive or negative emotions. This allows it to recognize the user's emotional state in real time and determine when attention is needed, especially if negative emotions are strong. For example, if a user enters the phrase "I really hate it," the emotion engine interprets this as an indication of heightened negative emotions.

[0325] Based on the results of the defamation detection and emotional recognition, the server generates a warning message. This message is then adjusted to be more appropriate and considerate, taking into account the user's emotional state. For example, a warning such as, "This expression may hurt others. Please reconsider," might be displayed.

[0326] Ultimately, the device presents the user with feedback received from the server, prompting the user to revise their input based on that feedback. Through this process, it becomes possible to prevent defamation and slander while also providing flexible responses that address the user's emotional needs.

[0327] The following describes the processing flow.

[0328] Step 1:

[0329] The device captures text data entered by the user using the keyboard in real time. This data is temporarily stored in the device's memory. During this process, the user can continue typing as usual.

[0330] Step 2:

[0331] The terminal encrypts the entered text data and sends it to the server using a secure communication protocol. This encryption process is crucial for maintaining data confidentiality.

[0332] Step 3:

[0333] The server receives the encrypted data from the terminal and decrypts it using the appropriate key. This allows the original text data entered by the user who sent the data to be reconstructed.

[0334] Step 4:

[0335] The server analyzes the decoded text data using natural language processing (NLP) to determine whether or not it contains defamation. During this process, a pre-trained algorithm detects specific language patterns.

[0336] Step 5:

[0337] The server activates the emotion engine and analyzes the emotional elements contained in the input. The emotion engine uses a machine learning model to determine whether the input represents a positive or negative emotion.

[0338] Step 6:

[0339] The server integrates the defamation detection results and the sentiment recognition results to generate an appropriate warning message. For example, if the text strongly expresses negative sentiment and is determined to be defamatory, the warning message will include the phrase, "This expression may offend others."

[0340] Step 7:

[0341] The terminal displays a warning message sent from the server to the user. This message is provided as a visual notification, such as a pop-up, giving the user an opportunity to review their input.

[0342] Step 8:

[0343] Users refer to the displayed warning messages and correct their input as needed. This feedback loop promotes interactive and secure communication.

[0344] (Example 2)

[0345] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0346] As information and communication environments develop, defamation and aggressive language have become a problem in online communication. Consequently, there is a growing need for systems that can appropriately recognize users' emotions and provide appropriate feedback in advance. This invention aims to prevent communication problems by accurately understanding users' emotional states and not only detecting aggressive language but also providing appropriate warnings tailored to their emotions.

[0347] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0348] In this invention, the server includes means for acquiring user input information, means for transmitting the input information to a communication device using data encryption technology, means for analyzing the text decrypted by the communication device and determining if it is an aggressive expression if it meets certain conditions, means for generating warning information based on the analysis results and notifying the user, means including an emotion analysis function that performs emotion analysis on the user's input text, means for identifying negative emotional states, and means for generating considerate warning information according to the emotional state. This makes it possible to analyze negative emotions and aggressive expressions in the text entered by the user in real time and provide appropriate feedback based on the results.

[0349] "User input information" refers to the text and data entered by the user through a terminal, before it is processed by the system.

[0350] "Data encryption technology" is a technology used to protect information from being deciphered by third parties when it is transmitted externally, and is used to ensure the confidentiality of information.

[0351] "Communication equipment" refers to devices and network environments used for sending and receiving data, and is used to exchange information between users and servers.

[0352] "Decryption" refers to the process of restoring encrypted information to its original state, a technique used to enable the recipient to read the data's contents.

[0353] "Analysis" refers to the process of analyzing data and information to extract useful information, and is performed in order for a system to understand the content of the input text.

[0354] "Specific conditions" refer to the criteria and rules set by the system to determine whether input data constitutes defamation or libel, and these are created based on past cases and statistical information.

[0355] "Aggressive language" refers to words or phrases that are offensive or potentially offensive to others, and can cause problems in online communication.

[0356] "Warning information" refers to a cautionary message that the system notifies the user of, intended to encourage them to review or improve their input.

[0357] "Emotional analysis function" refers to technology that analyzes the emotional state from text entered by the user and determines whether the emotion is positive or negative.

[0358] A "negative emotional state" refers to a negative emotional state detected by the system from user input, indicating a situation where a warning or follow-up is necessary.

[0359] "Considerate warning information" refers to warning information generated with the user's emotional state in mind, and is adjusted to provide more appropriate and emotionally sensitive content.

[0360] This invention provides a system that analyzes user input information and determines their emotional state in order to improve the quality of online communication. This system consists of a terminal, a communication device, and a server.

[0361] First, when a user enters text through their device, that input information is acquired in real time. At that time, the device encrypts the user's input information and sends it to the server while maintaining security. Common encryption methods such as AES (Advanced Encryption Standard) are used for encryption.

[0362] Next, the server decodes the received input information. It uses natural language processing libraries such as Python or TensorFlow to analyze the received text data. The purpose of the analysis is to detect offensive expressions contained in the input information, using a pre-configured terminology log.

[0363] The server also activates its sentiment analysis function, analyzing the user's emotions based on their input. Using machine learning algorithms, such as BERT (Bidirectional Encoder Representations from Transformers), it determines positive or negative emotions in real time. If strong negative emotions are detected, appropriate and considerate warning information is generated.

[0364] Finally, the warning information generated by the server is returned to the terminal and presented to the user visually. This encourages the user to review their input, thus preventing inappropriate online communication.

[0365] For example, if a user tries to post a negative comment on social media such as "I hate my job," the sentiment analysis function can identify this as a negative emotion and inform the user that the comment may be problematic.

[0366] An example of a prompt message is, "Analyze the sentiment contained in the text entered by the user and generate appropriate feedback. Text: 'XXX'." In this way, the present invention supports healthy user communication by integrating multiple technologies to provide appropriate feedback.

[0367] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0368] Step 1:

[0369] The user enters text.

[0370] The user enters text data such as comments and messages on the device, and this input information is captured by the device. This input information becomes the data for the next encryption step.

[0371] Step 2:

[0372] The terminal encrypts the input information and sends it to the server.

[0373] The terminal encrypts the acquired text data using encryption technologies such as AES. This encrypted data enables secure transfer to the server and guarantees the protection of the input information after transfer. The output is encrypted data.

[0374] Step 3:

[0375] The server decrypts the data.

[0376] The server performs a decryption process to return the received encrypted data back to its original text. After receiving the decrypted data, it becomes the input data for the next analysis step. The output is the original text data.

[0377] Step 4:

[0378] The server analyzes the text data and detects offensive expressions.

[0379] The server uses a natural language processing library to analyze text data. It determines whether specific keywords or phrases in the input text match past terminology records and generates output indicating whether they are offensive expressions.

[0380] Step 5:

[0381] The server performs sentiment analysis.

[0382] The server launches a machine learning model to analyze sentiment based on text data. It utilizes models such as BERT to determine whether the input represents positive or negative sentiment and outputs the result.

[0383] Step 6:

[0384] The server generates warning information and provides feedback to the user.

[0385] The server generates appropriate warning information based on the results of aggressive language and sentiment analysis, and sends it to the terminal as feedback. This feedback includes specific measures such as suggestions for improving language use, and the output is warning information notified to the user.

[0386] Step 7:

[0387] The device displays a warning message.

[0388] The terminal displays warning information received from the server to the user in a visible format. Here, the user can review their input and make corrections as needed, thus maintaining the health of online communication. The output is feedback that the user can see.

[0389] (Application Example 2)

[0390] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0391] In conventional electronic trading systems, users may conduct transactions while emotionally overwhelmed, potentially leading to inappropriate communication and defamation. To prevent such situations and promote appropriate communication, a system is needed that recognizes users' emotions in real time and provides appropriate feedback.

[0392] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0393] In this invention, the server includes means for acquiring user data input, means for encrypting the data input and transmitting it to an information processing device, means for analyzing the decrypted character data in the information processing device and determining defamation if certain conditions are met, means for analyzing the user's emotions based on the character data and determining the emotional state, means for generating an appropriate interaction based on the emotional state and notifying the user, and means for generating a warning message based on the determination result and notifying the user. This makes it possible to provide flexible and appropriate interactions according to the user's emotional state and prevent inappropriate communication.

[0394] "Means for obtaining user data input" refers to a function that receives data entered by a user into the system and collects that information for processing.

[0395] "Means of encrypting data input and transmitting it to an information processing device" refers to a method of protecting data input obtained from a user using encryption technology and securely delivering the data to the destination information processing device.

[0396] "A means of analyzing decrypted character data using an information processing device and determining if it constitutes defamation if it meets specific conditions" refers to a process of decrypting encrypted character data, analyzing its content, evaluating whether it matches pre-set criteria, and then considering it to be defamatory.

[0397] "A means of analyzing a user's emotions and determining their emotional state based on text data" refers to a function that analyzes the text data entered by the user to evaluate their emotions at that time and identify whether their emotional state is positive or negative.

[0398] "A means of generating appropriate interactions based on emotional state and notifying the user" refers to the process of creating and communicating messages and suggestions designed to allow the user to respond appropriately, based on the analyzed emotional state of the user.

[0399] "A means of generating a warning message based on the judgment result and notifying the user" refers to a function that, when something is judged to be defamatory, creates a warning message for the user based on that information and sends a notification.

[0400] The system for realizing this invention consists mainly of a user, a terminal, and a server. The user inputs data via the terminal. The terminal receives this data, encrypts it, and then sends it to the server.

[0401] The server first decodes the received data. Next, it analyzes the text data using natural language processing techniques and, if necessary, compares it against specific conditions to determine if it constitutes defamation. These conditions utilize a vocabulary list of defamatory terms based on past judgments. Simultaneously, it analyzes the user's emotional state using a machine learning algorithm based on the text data from the user. This allows it to determine if the user is emotionally agitated and generate appropriate feedback.

[0402] Feedback provides appropriate interactions based on the user's emotional state, including warning messages and correction suggestions. The generated warning messages also include suggestions for reviewing the user's input.

[0403] The implementation of this system can utilize Python libraries (e.g., Spacy, NLTK) and machine learning frameworks (e.g., TensorFlow) on the server side. These technologies enable efficient analysis of received data, allowing for sentiment analysis and feedback generation.

[0404] For example, if a user enters a negative phrase such as "Do something!" during an electronic transaction, the server can analyze this phrase to determine the user's emotional state and provide thoughtful feedback such as, "Could you please provide additional information so we can understand the situation better?"

[0405] An example of a prompt to input into a generative AI model is: "Classify the following user input as positive or negative, check for slander, and generate an appropriate feedback message: 'Do something!'" Using this prompt enables highly accurate feedback.

[0406] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0407] Step 1:

[0408] The user enters a message using the terminal. This input data is received by the terminal as text data, including the user's intentions and feelings. The terminal receives this data, encrypts it using an encryption algorithm, and sends it to the server for further processing.

[0409] Step 2:

[0410] The server receives encrypted data sent from the terminal. The original text data is extracted by decrypting the received data. The decrypted data is then analyzed using natural language processing (NLP) techniques to determine if it contains defamation. Specifically, words and phrases in the text are compared against a vocabulary list of defamatory terms.

[0411] Step 3:

[0412] The server utilizes machine learning algorithms to analyze emotions from the decoded data. It evaluates the emotional aspects of the input data and classifies them as positive or negative. This process determines the user's emotional state, and the result is reflected in the prompt text of the generating AI model.

[0413] Step 4:

[0414] The server generates feedback based on the analysis of emotions and slander. This feedback includes specific warning messages and messages suggesting further action. For example, if emotions are heightened, it will generate advice such as, "Let's calm down and think about the situation."

[0415] Step 5:

[0416] Finally, the server sends the generated feedback message to the device, notifying the user. The user can then review the message on their device and revise their input based on the feedback provided. This process gives the user an opportunity to avoid slander and maintain appropriate communication.

[0417] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0418] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0419] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0420] [Third Embodiment]

[0421] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0422] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0423] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0424] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0425] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0426] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0427] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0428] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0429] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0430] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0431] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0432] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0433] This embodiment provides a system aimed at preventing defamation and slander based on real-time input from users. This system includes a series of processes from the initial stage where the user inputs information via a terminal, through analysis by communication equipment, to the final display of a warning.

[0434] As a user begins typing on the terminal, the input is captured sequentially by the terminal. The terminal monitors this input data in real time and encrypts the captured data using a security protocol. The encrypted data is then transmitted to a communication device via a secure network connection. This communication device is typically a server located in a data center.

[0435] The server immediately decrypts the received data and analyzes it using natural language processing (NLP) techniques. This analysis employs machine learning algorithms to determine whether the data contains specific words or phrases related to defamation.

[0436] For example, if a user types "AA is stupid," the server analyzes this input and determines that the word "stupid" contributes to a negative rating. If this result exceeds the threshold, the server immediately generates feedback and sends the result back to the terminal. The feedback includes a warning message to inform the user that it may be defamatory. This warning encourages the user to review their input and try to change it to a more appropriate expression.

[0437] As described above, the present invention can improve the quality of communication and prevent problems on the internet by evaluating user input in a short time and immediately providing a response as needed.

[0438] The following describes the processing flow.

[0439] Step 1:

[0440] The terminal captures data entered by the user using the keyboard in real time. This input data is temporarily stored in a buffer sequentially.

[0441] Step 2:

[0442] The device encrypts the captured input data. Standard encryption algorithms are used to ensure data security. This encrypted data is then ready to be transmitted to communication devices over the network.

[0443] Step 3:

[0444] The server receives encrypted data sent from the terminal. The received data is immediately decrypted using the appropriate key and returned to the original text data.

[0445] Step 4:

[0446] The server analyzes the decrypted text data using natural language processing. This includes text mining using machine learning algorithms to detect words and phrases that constitute defamation or libel.

[0447] Step 5:

[0448] The server determines whether the input data is defamatory based on the analysis results. The algorithm considers it defamatory if it reaches a score that exceeds a pre-set threshold. In this case, evidence of the defamatory determination is also recorded.

[0449] Step 6:

[0450] The server generates feedback based on its judgment. This feedback includes a warning message for the user, informing them that the content contains defamatory language.

[0451] Step 7:

[0452] The terminal displays feedback received from the server to the user. The user sees a warning message and has an opportunity to review their input. This display usually appears as a pop-up next to the input field.

[0453] (Example 1)

[0454] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0455] Online defamation and slander degrade the quality of communication and infringe upon individual personality rights and human rights. However, current technology is insufficient to detect these in real time and issue warnings proactively. To address this challenge, there is a need for a system that effectively detects defamation and slander at the user input stage and provides a swift response.

[0456] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0457] In this invention, the server includes means for sequentially acquiring user input text, means for securely transmitting the input text to a communication device using an encryption protocol, and means for decrypting the data received by the communication device, analyzing its content using natural language processing technology, and identifying defamatory elements. This makes it possible to detect the risk of defamation in real time and immediately warn the user.

[0458] A "user" is the entity that operates the system and generates input data.

[0459] "Input text" refers to text data that a user provides to the system through their device.

[0460] An "encryption protocol" is a set of rules and techniques used to ensure the security of data.

[0461] "Communication equipment" refers to a device used to transmit data to another device or system.

[0462] "Natural language processing technology" is the technology that enables computers to understand and process human language.

[0463] "Defamatory elements" are words or phrases that may harm a specific individual or group.

[0464] "Warning information" refers to messages displayed to the user to alert them about the input data.

[0465] A "generative AI model" is an artificial intelligence model that has been trained using historical data and is used for analyzing and predicting text data.

[0466] This invention is a system that instantly detects whether defamatory elements are present in text input by a user in real time and displays warning information. This system consists of a user, a terminal, and a server.

[0467] When a user enters text data into a terminal, the terminal captures that data sequentially. The terminal encrypts the captured input text using AES (Advanced Encryption Standard) and sends it to a server, which is a communication device, using a secure protocol (e.g., TLS). This encryption ensures the confidentiality of the data.

[0468] The server receives encrypted data, verifies the digital signature, and then decrypts it. Afterward, it uses natural language processing techniques to analyze the defamatory elements within the text. Specifically, it uses a generative AI model to identify defamatory elements based on past data. This generative AI model utilizes a model like BERT (Bidirectional Encoder Representations from Transformers) to achieve highly accurate analysis.

[0469] If defamatory elements are detected, the server generates appropriate warning information for the user and sends it back to the terminal. The terminal immediately displays this warning information to the user, prompting them to correct their input. This allows the user to review their inappropriate language and improve the quality of the conversation.

[0470] For example, if a user enters "○○ is stupid" into a community site, the AI ​​model will analyze that the word "stupid" contains negative elements and generate a warning message. An example of a prompt message could be: "Please evaluate whether the entered text constitutes defamation. Text: '○○ is stupid'." In this way, a system is built to support smooth and healthy communication on the internet.

[0471] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0472] Step 1:

[0473] The user enters text into the device. The characters being entered are captured sequentially. This string data is temporarily stored in the device's memory.

[0474] Step 2:

[0475] The terminal encrypts the captured input text using AES. The input text is converted into secure binary data by the encryption algorithm, and this encrypted data is generated as output. The encrypted data is sent to the server using a secure protocol.

[0476] Step 3:

[0477] The server receives the encrypted data, verifies the digital signature, and then decrypts it. The input is encrypted binary data, and after the decryption process, human-readable string data is output.

[0478] Step 4:

[0479] The server analyzes the decrypted text data using natural language processing techniques. Here, a generative AI model is employed to score the likelihood of defamation based on the input text. The input is the decrypted text, and the output is the score and the analysis results of the defamatory elements.

[0480] Step 5:

[0481] If the score generated by the server exceeds a set threshold, it is judged to be defamation. Based on this analysis, warning information is generated. The input is the score and analysis result, and the output is a warning message to notify the user.

[0482] Step 6:

[0483] The server sends a warning message to the terminal. The terminal displays the received message to the user, prompting them to review their input. The input is the warning message data, and the output is the warning information displayed on the user's screen. This display gives the user an opportunity to improve their expression.

[0484] (Application Example 1)

[0485] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0486] In electronic transactions, the inclusion of potentially defamatory language in transaction memos and comment sections by users can cause problems and hinder safe and smooth transactions.

[0487] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0488] In this invention, the server includes a device for acquiring user input data, a device for encrypting the input data and transmitting it to a device having a communication function, a device for analyzing the text data decrypted by the device having a communication function and determining that it is defamatory if certain conditions are met, a device for generating a warning message based on the determination result and notifying the user, and a device for displaying the aforementioned warning message based on the input content in the transaction memo when the user is conducting an electronic transaction. This makes it possible for users to avoid defamation even during transactions and promotes safe and reliable communication.

[0489] The term "user" refers to a trader who uses this system to input data.

[0490] "Input data" refers to text information or strings of characters entered by a user using an electronic device.

[0491] "Encryption" is the process of transforming input data using a specific algorithm to protect it from unauthorized access and leakage.

[0492] A "device with communication capabilities" refers to a device that can send and receive data over a network, and generally includes servers and routers.

[0493] "Decryption" refers to the technique of restoring encrypted data to its original, readable format.

[0494] "Analysis" is the process of analyzing input data using specific algorithms and methods, and then evaluating the results.

[0495] "Specific conditions" refer to defining words, phrases, or patterns that serve as criteria for determining whether something constitutes defamation or libel.

[0496] "Judgment" is the process of determining whether the input content constitutes defamation or libel based on the analyzed data.

[0497] A "warning message" is a notification displayed as a warning when the content entered by the user may be inappropriate.

[0498] "Electronic transaction" is a term that refers to transactions conducted online for the purpose of exchanging goods and services.

[0499] "Transaction memo" refers to a field in electronic transactions where users can freely enter comments or notes.

[0500] The system implementing this invention provides a secure electronic transaction environment by analyzing user input data in real time and preventing defamatory expressions.

[0501] The server receives data entered by the user via the terminal and encrypts it using encryption technology. The encryption library "cryptography.fernet" is used for encryption. A secure network connection is established as the means of communication, and data is sent and received to the server using the "requests" library. After decrypting the received data, the server performs analysis using natural language processing technology. In this analysis, machine learning algorithms are used to determine whether certain conditions are met and to assess the possibility of defamation.

[0502] Users can enter notes or comments during transactions, but if the content is determined to be defamatory, the server immediately generates a warning message and notifies the user. This allows users to correct inappropriate language during transactions, ensuring safe and smooth transactions.

[0503] For example, if a user enters "This item is ridiculously overpriced" in the transaction memo, the server will detect this phrase and display a warning message, thus preventing misunderstandings and problems.

[0504] Thus, an example of a prompt message would be, "How should a warning message be displayed if a user might use inappropriate language in a remittance note in an electronic payment service?"

[0505] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0506] Step 1:

[0507] The device captures user input data. This input data consists of strings entered by the user, and the device monitors this data in real time and temporarily stores it as text data.

[0508] Step 2:

[0509] The terminal encrypts the input data. The terminal uses "cryptography.fernet" to encrypt this text data and generate encrypted data. This encrypted data is intended to prevent unauthorized access and information leakage from external sources.

[0510] Step 3:

[0511] The terminal sends encrypted data to a device with communication capabilities. This encrypted data is then sent to the server using the "requests" library via a secure network connection. The input here is the encrypted data, and the output is the status of the transmission to the server.

[0512] Step 4:

[0513] The server decrypts the received data. The server takes the encrypted data sent from the terminal, decrypts it, and reconstructs the original text data. In this decryption step, the input is the encrypted data and the output is the original text data.

[0514] Step 5:

[0515] The server analyzes the text data. The server uses natural language processing techniques to analyze the decoded text data. Using machine learning algorithms, it determines whether the text contains words or phrases related to defamation and generates the results. The input is text data, and the output is the analysis result.

[0516] Step 6:

[0517] The server generates a warning message based on the analysis results. If the analysis results meet certain conditions, the server creates a warning message and constructs data to present to the user. The input is the analysis results, and the output is the warning message.

[0518] Step 7:

[0519] The terminal displays a warning message received from the server to the user. The terminal receives this warning message and displays it on the user's screen to prompt correction of the input. The input is the data of the warning message, and the output is a visual warning display to the user.

[0520] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0521] In this embodiment, by integrating an emotion engine in addition to a defamation detection function for user input, a system is realized that more accurately recognizes the user's emotional state and provides appropriate interaction. This system includes an integrated process from the initial stage of user input through the terminal to the eventual display of warnings and feedback.

[0522] When a user enters text into their device, the data is encrypted and sent to the server. The server decrypts the received data and first analyzes the input using natural language processing (NLP) to determine if it contains defamation or libel. Simultaneously, an emotion engine is activated to analyze the emotions associated with the input.

[0523] The emotion engine utilizes machine learning algorithms to determine whether the input text evokes positive or negative emotions. This allows it to recognize the user's emotional state in real time and determine when attention is needed, especially if negative emotions are strong. For example, if a user enters the phrase "I really hate it," the emotion engine interprets this as an indication of heightened negative emotions.

[0524] Based on the results of the defamation detection and emotional recognition, the server generates a warning message. This message is then adjusted to be more appropriate and considerate, taking into account the user's emotional state. For example, a warning such as, "This expression may hurt others. Please reconsider," might be displayed.

[0525] Ultimately, the device presents the user with feedback received from the server, prompting the user to revise their input based on that feedback. Through this process, it becomes possible to prevent defamation and slander while also providing flexible responses that address the user's emotional needs.

[0526] The following describes the processing flow.

[0527] Step 1:

[0528] The device captures text data entered by the user using the keyboard in real time. This data is temporarily stored in the device's memory. During this process, the user can continue typing as usual.

[0529] Step 2:

[0530] The terminal encrypts the entered text data and sends it to the server using a secure communication protocol. This encryption process is crucial for maintaining data confidentiality.

[0531] Step 3:

[0532] The server receives the encrypted data from the terminal and decrypts it using the appropriate key. This allows the original text data entered by the user who sent the data to be reconstructed.

[0533] Step 4:

[0534] The server analyzes the decoded text data using natural language processing (NLP) to determine whether or not it contains defamation. During this process, a pre-trained algorithm detects specific language patterns.

[0535] Step 5:

[0536] The server activates the emotion engine and analyzes the emotional elements contained in the input. The emotion engine uses a machine learning model to determine whether the input represents a positive or negative emotion.

[0537] Step 6:

[0538] The server integrates the defamation detection results and the sentiment recognition results to generate an appropriate warning message. For example, if the text strongly expresses negative sentiment and is determined to be defamatory, the warning message will include the phrase, "This expression may offend others."

[0539] Step 7:

[0540] The terminal displays a warning message sent from the server to the user. This message is provided as a visual notification, such as a pop-up, giving the user an opportunity to review their input.

[0541] Step 8:

[0542] Users refer to the displayed warning messages and correct their input as needed. This feedback loop promotes interactive and secure communication.

[0543] (Example 2)

[0544] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0545] As information and communication environments develop, defamation and aggressive language have become a problem in online communication. Consequently, there is a growing need for systems that can appropriately recognize users' emotions and provide appropriate feedback in advance. This invention aims to prevent communication problems by accurately understanding users' emotional states and not only detecting aggressive language but also providing appropriate warnings tailored to their emotions.

[0546] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0547] In this invention, the server includes means for acquiring user input information, means for transmitting the input information to a communication device using data encryption technology, means for analyzing the text decrypted by the communication device and determining if it is an aggressive expression if it meets certain conditions, means for generating warning information based on the analysis results and notifying the user, means including an emotion analysis function that performs emotion analysis on the user's input text, means for identifying negative emotional states, and means for generating considerate warning information according to the emotional state. This makes it possible to analyze negative emotions and aggressive expressions in the text entered by the user in real time and provide appropriate feedback based on the results.

[0548] "User input information" refers to the text and data entered by the user through a terminal, before it is processed by the system.

[0549] "Data encryption technology" is a technology used to protect information from being deciphered by third parties when it is transmitted externally, and is used to ensure the confidentiality of information.

[0550] "Communication equipment" refers to devices and network environments used for sending and receiving data, and is used to exchange information between users and servers.

[0551] "Decryption" refers to the process of restoring encrypted information to its original state, a technique used to enable the recipient to read the data's contents.

[0552] "Analysis" refers to the process of analyzing data and information to extract useful information, and is performed in order for a system to understand the content of the input text.

[0553] "Specific conditions" refer to the criteria and rules set by the system to determine whether input data constitutes defamation or libel, and these are created based on past cases and statistical information.

[0554] "Aggressive language" refers to words or phrases that are offensive or potentially offensive to others, and can cause problems in online communication.

[0555] "Warning information" refers to a cautionary message that the system notifies the user of, intended to encourage them to review or improve their input.

[0556] "Emotional analysis function" refers to technology that analyzes the emotional state from text entered by the user and determines whether the emotion is positive or negative.

[0557] A "negative emotional state" refers to a negative emotional state detected by the system from user input, indicating a situation where a warning or follow-up is necessary.

[0558] "Considerate warning information" refers to warning information generated with the user's emotional state in mind, and is adjusted to provide more appropriate and emotionally sensitive content.

[0559] This invention provides a system that analyzes user input information and determines their emotional state in order to improve the quality of online communication. This system consists of a terminal, a communication device, and a server.

[0560] First, when a user enters text through their device, that input information is acquired in real time. At that time, the device encrypts the user's input information and sends it to the server while maintaining security. Common encryption methods such as AES (Advanced Encryption Standard) are used for encryption.

[0561] Next, the server decodes the received input information. It uses natural language processing libraries such as Python or TensorFlow to analyze the received text data. The purpose of the analysis is to detect offensive expressions contained in the input information, using a pre-configured terminology log.

[0562] The server also activates its sentiment analysis function, analyzing the user's emotions based on their input. Using machine learning algorithms, such as BERT (Bidirectional Encoder Representations from Transformers), it determines positive or negative emotions in real time. If strong negative emotions are detected, appropriate and considerate warning information is generated.

[0563] Finally, the warning information generated by the server is returned to the terminal and presented to the user visually. This encourages the user to review their input, thus preventing inappropriate online communication.

[0564] For example, if a user tries to post a negative comment on social media such as "I hate my job," the sentiment analysis function can identify this as a negative emotion and inform the user that the comment may be problematic.

[0565] An example of a prompt message is, "Analyze the sentiment contained in the text entered by the user and generate appropriate feedback. Text: 'XXX'." In this way, the present invention supports healthy user communication by integrating multiple technologies to provide appropriate feedback.

[0566] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0567] Step 1:

[0568] The user enters text.

[0569] The user enters text data such as comments and messages on the device, and this input information is captured by the device. This input information becomes the data for the next encryption step.

[0570] Step 2:

[0571] The terminal encrypts the input information and sends it to the server.

[0572] The terminal encrypts the acquired text data using encryption technologies such as AES. This encrypted data enables secure transfer to the server and guarantees the protection of the input information after transfer. The output is encrypted data.

[0573] Step 3:

[0574] The server decrypts the data.

[0575] The server performs a decryption process to return the received encrypted data back to its original text. After receiving the decrypted data, it becomes the input data for the next analysis step. The output is the original text data.

[0576] Step 4:

[0577] The server analyzes the text data and detects offensive expressions.

[0578] The server uses a natural language processing library to analyze text data. It determines whether specific keywords or phrases in the input text match past terminology records and generates output indicating whether they are offensive expressions.

[0579] Step 5:

[0580] The server performs sentiment analysis.

[0581] The server launches a machine learning model to analyze sentiment based on text data. It utilizes models such as BERT to determine whether the input represents positive or negative sentiment and outputs the result.

[0582] Step 6:

[0583] The server generates warning information and provides feedback to the user.

[0584] The server generates appropriate warning information based on the results of aggressive language and sentiment analysis, and sends it to the terminal as feedback. This feedback includes specific measures such as suggestions for improving language use, and the output is warning information notified to the user.

[0585] Step 7:

[0586] The device displays a warning message.

[0587] The terminal displays warning information received from the server to the user in a visible format. Here, the user can review their input and make corrections as needed, thus maintaining the health of online communication. The output is feedback that the user can see.

[0588] (Application Example 2)

[0589] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0590] In conventional electronic trading systems, users may conduct transactions while emotionally overwhelmed, potentially leading to inappropriate communication and defamation. To prevent such situations and promote appropriate communication, a system is needed that recognizes users' emotions in real time and provides appropriate feedback.

[0591] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0592] In this invention, the server includes means for acquiring user data input, means for encrypting the data input and transmitting it to an information processing device, means for analyzing the decrypted character data in the information processing device and determining defamation if certain conditions are met, means for analyzing the user's emotions based on the character data and determining the emotional state, means for generating an appropriate interaction based on the emotional state and notifying the user, and means for generating a warning message based on the determination result and notifying the user. This makes it possible to provide flexible and appropriate interactions according to the user's emotional state and prevent inappropriate communication.

[0593] "Means for obtaining user data input" refers to a function that receives data entered by a user into the system and collects that information for processing.

[0594] "Means of encrypting data input and transmitting it to an information processing device" refers to a method of protecting data input obtained from a user using encryption technology and securely delivering the data to the destination information processing device.

[0595] "A means of analyzing decrypted character data using an information processing device and determining if it constitutes defamation if it meets specific conditions" refers to a process of decrypting encrypted character data, analyzing its content, evaluating whether it matches pre-set criteria, and then considering it to be defamatory.

[0596] "A means of analyzing a user's emotions and determining their emotional state based on text data" refers to a function that analyzes the text data entered by the user to evaluate their emotions at that time and identify whether their emotional state is positive or negative.

[0597] "A means of generating appropriate interactions based on emotional state and notifying the user" refers to the process of creating and communicating messages and suggestions designed to allow the user to respond appropriately, based on the analyzed emotional state of the user.

[0598] "A means of generating a warning message based on the judgment result and notifying the user" refers to a function that, when something is judged to be defamatory, creates a warning message for the user based on that information and sends a notification.

[0599] The system for realizing this invention consists mainly of a user, a terminal, and a server. The user inputs data via the terminal. The terminal receives this data, encrypts it, and then sends it to the server.

[0600] The server first decodes the received data. Next, it analyzes the text data using natural language processing techniques and, if necessary, compares it against specific conditions to determine if it constitutes defamation. These conditions utilize a vocabulary list of defamatory terms based on past judgments. Simultaneously, it analyzes the user's emotional state using a machine learning algorithm based on the text data from the user. This allows it to determine if the user is emotionally agitated and generate appropriate feedback.

[0601] Feedback provides appropriate interactions based on the user's emotional state, including warning messages and correction suggestions. The generated warning messages also include suggestions for reviewing the user's input.

[0602] The implementation of this system can utilize Python libraries (e.g., Spacy, NLTK) and machine learning frameworks (e.g., TensorFlow) on the server side. These technologies enable efficient analysis of received data, allowing for sentiment analysis and feedback generation.

[0603] For example, if a user enters a negative phrase such as "Do something!" during an electronic transaction, the server can analyze this phrase to determine the user's emotional state and provide thoughtful feedback such as, "Could you please provide additional information so we can understand the situation better?"

[0604] An example of a prompt to input into a generative AI model is: "Classify the following user input as positive or negative, check for slander, and generate an appropriate feedback message: 'Do something!'" Using this prompt enables highly accurate feedback.

[0605] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0606] Step 1:

[0607] The user enters a message using the terminal. This input data is received by the terminal as text data, including the user's intentions and feelings. The terminal receives this data, encrypts it using an encryption algorithm, and sends it to the server for further processing.

[0608] Step 2:

[0609] The server receives encrypted data sent from the terminal. The original text data is extracted by decrypting the received data. The decrypted data is then analyzed using natural language processing (NLP) techniques to determine if it contains defamation. Specifically, words and phrases in the text are compared against a vocabulary list of defamatory terms.

[0610] Step 3:

[0611] The server utilizes machine learning algorithms to analyze emotions from the decoded data. It evaluates the emotional aspects of the input data and classifies them as positive or negative. This process determines the user's emotional state, and the result is reflected in the prompt text of the generating AI model.

[0612] Step 4:

[0613] The server generates feedback based on the analysis of emotions and slander. This feedback includes specific warning messages and messages suggesting further action. For example, if emotions are heightened, it will generate advice such as, "Let's calm down and think about the situation."

[0614] Step 5:

[0615] Finally, the server sends the generated feedback message to the device, notifying the user. The user can then review the message on their device and revise their input based on the feedback provided. This process gives the user an opportunity to avoid slander and maintain appropriate communication.

[0616] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0617] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0618] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0619] [Fourth Embodiment]

[0620] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0621] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0622] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0623] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0624] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0625] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0626] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0627] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0628] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0629] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0630] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0631] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0632] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0633] This embodiment provides a system aimed at preventing defamation and slander based on real-time input from users. This system includes a series of processes from the initial stage where the user inputs information via a terminal, through analysis by communication equipment, to the final display of a warning.

[0634] As a user begins typing on the terminal, the input is captured sequentially by the terminal. The terminal monitors this input data in real time and encrypts the captured data using a security protocol. The encrypted data is then transmitted to a communication device via a secure network connection. This communication device is typically a server located in a data center.

[0635] The server immediately decrypts the received data and analyzes it using natural language processing (NLP) techniques. This analysis employs machine learning algorithms to determine whether the data contains specific words or phrases related to defamation.

[0636] For example, if a user types "AA is stupid," the server analyzes this input and determines that the word "stupid" contributes to a negative rating. If this result exceeds the threshold, the server immediately generates feedback and sends the result back to the terminal. The feedback includes a warning message to inform the user that it may be defamatory. This warning encourages the user to review their input and try to change it to a more appropriate expression.

[0637] As described above, the present invention can improve the quality of communication and prevent problems on the internet by evaluating user input in a short time and immediately providing a response as needed.

[0638] The following describes the processing flow.

[0639] Step 1:

[0640] The terminal captures data entered by the user using the keyboard in real time. This input data is temporarily stored in a buffer sequentially.

[0641] Step 2:

[0642] The device encrypts the captured input data. Standard encryption algorithms are used to ensure data security. This encrypted data is then ready to be transmitted to communication devices over the network.

[0643] Step 3:

[0644] The server receives encrypted data sent from the terminal. The received data is immediately decrypted using the appropriate key and returned to the original text data.

[0645] Step 4:

[0646] The server analyzes the decrypted text data using natural language processing. This includes text mining using machine learning algorithms to detect words and phrases that constitute defamation or libel.

[0647] Step 5:

[0648] The server determines whether the input data is defamatory based on the analysis results. The algorithm considers it defamatory if it reaches a score that exceeds a pre-set threshold. In this case, evidence of the defamatory determination is also recorded.

[0649] Step 6:

[0650] The server generates feedback based on its judgment. This feedback includes a warning message for the user, informing them that the content contains defamatory language.

[0651] Step 7:

[0652] The terminal displays feedback received from the server to the user. The user sees a warning message and has an opportunity to review their input. This display usually appears as a pop-up next to the input field.

[0653] (Example 1)

[0654] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0655] Online defamation and slander degrade the quality of communication and infringe upon individual personality rights and human rights. However, current technology is insufficient to detect these in real time and issue warnings proactively. To address this challenge, there is a need for a system that effectively detects defamation and slander at the user input stage and provides a swift response.

[0656] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0657] In this invention, the server includes means for sequentially acquiring user input text, means for securely transmitting the input text to a communication device using an encryption protocol, and means for decrypting the data received by the communication device, analyzing its content using natural language processing technology, and identifying defamatory elements. This makes it possible to detect the risk of defamation in real time and immediately warn the user.

[0658] A "user" is the entity that operates the system and generates input data.

[0659] "Input text" refers to text data that a user provides to the system through their device.

[0660] An "encryption protocol" is a set of rules and techniques used to ensure the security of data.

[0661] "Communication equipment" refers to a device used to transmit data to another device or system.

[0662] "Natural language processing technology" is the technology that enables computers to understand and process human language.

[0663] "Defamatory elements" are words or phrases that may harm a specific individual or group.

[0664] "Warning information" refers to messages displayed to the user to alert them about the input data.

[0665] A "generative AI model" is an artificial intelligence model that has been trained using historical data and is used for analyzing and predicting text data.

[0666] This invention is a system that instantly detects whether defamatory elements are present in text input by a user in real time and displays warning information. This system consists of a user, a terminal, and a server.

[0667] When a user enters text data into a terminal, the terminal captures that data sequentially. The terminal encrypts the captured input text using AES (Advanced Encryption Standard) and sends it to a server, which is a communication device, using a secure protocol (e.g., TLS). This encryption ensures the confidentiality of the data.

[0668] The server receives encrypted data, verifies the digital signature, and then decrypts it. Afterward, it uses natural language processing techniques to analyze the defamatory elements within the text. Specifically, it uses a generative AI model to identify defamatory elements based on past data. This generative AI model utilizes a model like BERT (Bidirectional Encoder Representations from Transformers) to achieve highly accurate analysis.

[0669] If defamatory elements are detected, the server generates appropriate warning information for the user and sends it back to the terminal. The terminal immediately displays this warning information to the user, prompting them to correct their input. This allows the user to review their inappropriate language and improve the quality of the conversation.

[0670] For example, if a user enters "○○ is stupid" into a community site, the AI ​​model will analyze that the word "stupid" contains negative elements and generate a warning message. An example of a prompt message could be: "Please evaluate whether the entered text constitutes defamation. Text: '○○ is stupid'." In this way, a system is built to support smooth and healthy communication on the internet.

[0671] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0672] Step 1:

[0673] The user enters text into the device. The characters being entered are captured sequentially. This string data is temporarily stored in the device's memory.

[0674] Step 2:

[0675] The terminal encrypts the captured input text using AES. The input text is converted into secure binary data by the encryption algorithm, and this encrypted data is generated as output. The encrypted data is sent to the server using a secure protocol.

[0676] Step 3:

[0677] The server receives the encrypted data, verifies the digital signature, and then decrypts it. The input is encrypted binary data, and after the decryption process, human-readable string data is output.

[0678] Step 4:

[0679] The server analyzes the decrypted text data using natural language processing techniques. Here, a generative AI model is employed to score the likelihood of defamation based on the input text. The input is the decrypted text, and the output is the score and the analysis results of the defamatory elements.

[0680] Step 5:

[0681] If the score generated by the server exceeds a set threshold, it is judged to be defamation. Based on this analysis, warning information is generated. The input is the score and analysis result, and the output is a warning message to notify the user.

[0682] Step 6:

[0683] The server sends a warning message to the terminal. The terminal displays the received message to the user, prompting them to review their input. The input is the warning message data, and the output is the warning information displayed on the user's screen. This display gives the user an opportunity to improve their expression.

[0684] (Application Example 1)

[0685] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0686] In electronic transactions, the inclusion of potentially defamatory language in transaction memos and comment sections by users can cause problems and hinder safe and smooth transactions.

[0687] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0688] In this invention, the server includes a device for acquiring user input data, a device for encrypting the input data and transmitting it to a device having a communication function, a device for analyzing the text data decrypted by the device having a communication function and determining that it is defamatory if certain conditions are met, a device for generating a warning message based on the determination result and notifying the user, and a device for displaying the aforementioned warning message based on the input content in the transaction memo when the user is conducting an electronic transaction. This makes it possible for users to avoid defamation even during transactions and promotes safe and reliable communication.

[0689] The term "user" refers to a trader who uses this system to input data.

[0690] "Input data" refers to text information or strings of characters entered by a user using an electronic device.

[0691] "Encryption" is the process of transforming input data using a specific algorithm to protect it from unauthorized access and leakage.

[0692] A "device with communication capabilities" refers to a device that can send and receive data over a network, and generally includes servers and routers.

[0693] "Decryption" refers to the technique of restoring encrypted data to its original, readable format.

[0694] "Analysis" is the process of analyzing input data using specific algorithms and methods, and then evaluating the results.

[0695] "Specific conditions" refer to defining words, phrases, or patterns that serve as criteria for determining whether something constitutes defamation or libel.

[0696] "Judgment" is the process of determining whether the input content constitutes defamation or libel based on the analyzed data.

[0697] A "warning message" is a notification displayed as a warning when the content entered by the user may be inappropriate.

[0698] "Electronic transaction" is a term that refers to transactions conducted online for the purpose of exchanging goods and services.

[0699] "Transaction memo" refers to a field in electronic transactions where users can freely enter comments or notes.

[0700] The system implementing this invention provides a secure electronic transaction environment by analyzing user input data in real time and preventing defamatory expressions.

[0701] The server receives data entered by the user via the terminal and encrypts it using encryption technology. The encryption library "cryptography.fernet" is used for encryption. A secure network connection is established as the means of communication, and data is sent and received to the server using the "requests" library. After decrypting the received data, the server performs analysis using natural language processing technology. In this analysis, machine learning algorithms are used to determine whether certain conditions are met and to assess the possibility of defamation.

[0702] Users can enter notes or comments during transactions, but if the content is determined to be defamatory, the server immediately generates a warning message and notifies the user. This allows users to correct inappropriate language during transactions, ensuring safe and smooth transactions.

[0703] For example, if a user enters "This item is ridiculously overpriced" in the transaction memo, the server will detect this phrase and display a warning message, thus preventing misunderstandings and problems.

[0704] Thus, an example of a prompt message would be, "How should a warning message be displayed if a user might use inappropriate language in a remittance note in an electronic payment service?"

[0705] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0706] Step 1:

[0707] The device captures user input data. This input data consists of strings entered by the user, and the device monitors this data in real time and temporarily stores it as text data.

[0708] Step 2:

[0709] The terminal encrypts the input data. The terminal uses "cryptography.fernet" to encrypt this text data and generate encrypted data. This encrypted data is intended to prevent unauthorized access and information leakage from external sources.

[0710] Step 3:

[0711] The terminal sends encrypted data to a device with communication capabilities. This encrypted data is then sent to the server using the "requests" library via a secure network connection. The input here is the encrypted data, and the output is the status of the transmission to the server.

[0712] Step 4:

[0713] The server decrypts the received data. The server takes the encrypted data sent from the terminal, decrypts it, and reconstructs the original text data. In this decryption step, the input is the encrypted data and the output is the original text data.

[0714] Step 5:

[0715] The server analyzes the text data. The server uses natural language processing techniques to analyze the decoded text data. Using machine learning algorithms, it determines whether the text contains words or phrases related to defamation and generates the results. The input is text data, and the output is the analysis result.

[0716] Step 6:

[0717] The server generates a warning message based on the analysis results. If the analysis results meet certain conditions, the server creates a warning message and constructs data to present to the user. The input is the analysis results, and the output is the warning message.

[0718] Step 7:

[0719] The terminal displays a warning message received from the server to the user. The terminal receives this warning message and displays it on the user's screen to prompt correction of the input. The input is the data of the warning message, and the output is a visual warning display to the user.

[0720] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0721] In this embodiment, by integrating an emotion engine in addition to a defamation detection function for user input, a system is realized that more accurately recognizes the user's emotional state and provides appropriate interaction. This system includes an integrated process from the initial stage of user input through the terminal to the eventual display of warnings and feedback.

[0722] When a user enters text into their device, the data is encrypted and sent to the server. The server decrypts the received data and first analyzes the input using natural language processing (NLP) to determine if it contains defamation or libel. Simultaneously, an emotion engine is activated to analyze the emotions associated with the input.

[0723] The emotion engine utilizes machine learning algorithms to determine whether the input text evokes positive or negative emotions. This allows it to recognize the user's emotional state in real time and determine when attention is needed, especially if negative emotions are strong. For example, if a user enters the phrase "I really hate it," the emotion engine interprets this as an indication of heightened negative emotions.

[0724] Based on the results of the defamation detection and emotional recognition, the server generates a warning message. This message is then adjusted to be more appropriate and considerate, taking into account the user's emotional state. For example, a warning such as, "This expression may hurt others. Please reconsider," might be displayed.

[0725] Ultimately, the device presents the user with feedback received from the server, prompting the user to revise their input based on that feedback. Through this process, it becomes possible to prevent defamation and slander while also providing flexible responses that address the user's emotional needs.

[0726] The following describes the processing flow.

[0727] Step 1:

[0728] The device captures text data entered by the user using the keyboard in real time. This data is temporarily stored in the device's memory. During this process, the user can continue typing as usual.

[0729] Step 2:

[0730] The terminal encrypts the entered text data and sends it to the server using a secure communication protocol. This encryption process is crucial for maintaining data confidentiality.

[0731] Step 3:

[0732] The server receives the encrypted data from the terminal and decrypts it using the appropriate key. This allows the original text data entered by the user who sent the data to be reconstructed.

[0733] Step 4:

[0734] The server analyzes the decoded text data using natural language processing (NLP) to determine whether or not it contains defamation. During this process, a pre-trained algorithm detects specific language patterns.

[0735] Step 5:

[0736] The server activates the emotion engine and analyzes the emotional elements contained in the input. The emotion engine uses a machine learning model to determine whether the input represents a positive or negative emotion.

[0737] Step 6:

[0738] The server integrates the defamation detection results and the sentiment recognition results to generate an appropriate warning message. For example, if the text strongly expresses negative sentiment and is determined to be defamatory, the warning message will include the phrase, "This expression may offend others."

[0739] Step 7:

[0740] The terminal displays a warning message sent from the server to the user. This message is provided as a visual notification, such as a pop-up, giving the user an opportunity to review their input.

[0741] Step 8:

[0742] Users refer to the displayed warning messages and correct their input as needed. This feedback loop promotes interactive and secure communication.

[0743] (Example 2)

[0744] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0745] As information and communication environments develop, defamation and aggressive language have become a problem in online communication. Consequently, there is a growing need for systems that can appropriately recognize users' emotions and provide appropriate feedback in advance. This invention aims to prevent communication problems by accurately understanding users' emotional states and not only detecting aggressive language but also providing appropriate warnings tailored to their emotions.

[0746] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0747] In this invention, the server includes means for acquiring user input information, means for transmitting the input information to a communication device using data encryption technology, means for analyzing the text decrypted by the communication device and determining if it is an aggressive expression if it meets certain conditions, means for generating warning information based on the analysis results and notifying the user, means including an emotion analysis function that performs emotion analysis on the user's input text, means for identifying negative emotional states, and means for generating considerate warning information according to the emotional state. This makes it possible to analyze negative emotions and aggressive expressions in the text entered by the user in real time and provide appropriate feedback based on the results.

[0748] "User input information" refers to the text and data entered by the user through a terminal, before it is processed by the system.

[0749] "Data encryption technology" is a technology used to protect information from being deciphered by third parties when it is transmitted externally, and is used to ensure the confidentiality of information.

[0750] "Communication equipment" refers to devices and network environments used for sending and receiving data, and is used to exchange information between users and servers.

[0751] "Decryption" refers to the process of restoring encrypted information to its original state, a technique used to enable the recipient to read the data's contents.

[0752] "Analysis" refers to the process of analyzing data and information to extract useful information, and is performed in order for a system to understand the content of the input text.

[0753] "Specific conditions" refer to the criteria and rules set by the system to determine whether input data constitutes defamation or libel, and these are created based on past cases and statistical information.

[0754] "Aggressive language" refers to words or phrases that are offensive or potentially offensive to others, and can cause problems in online communication.

[0755] "Warning information" refers to a cautionary message that the system notifies the user of, intended to encourage them to review or improve their input.

[0756] "Emotional analysis function" refers to technology that analyzes the emotional state from text entered by the user and determines whether the emotion is positive or negative.

[0757] A "negative emotional state" refers to a negative emotional state detected by the system from user input, indicating a situation where a warning or follow-up is necessary.

[0758] "Considerate warning information" refers to warning information generated with the user's emotional state in mind, and is adjusted to provide more appropriate and emotionally sensitive content.

[0759] This invention provides a system that analyzes user input information and determines their emotional state in order to improve the quality of online communication. This system consists of a terminal, a communication device, and a server.

[0760] First, when a user enters text through their device, that input information is acquired in real time. At that time, the device encrypts the user's input information and sends it to the server while maintaining security. Common encryption methods such as AES (Advanced Encryption Standard) are used for encryption.

[0761] Next, the server decodes the received input information. It uses natural language processing libraries such as Python or TensorFlow to analyze the received text data. The purpose of the analysis is to detect offensive expressions contained in the input information, using a pre-configured terminology log.

[0762] The server also activates its sentiment analysis function, analyzing the user's emotions based on their input. Using machine learning algorithms, such as BERT (Bidirectional Encoder Representations from Transformers), it determines positive or negative emotions in real time. If strong negative emotions are detected, appropriate and considerate warning information is generated.

[0763] Finally, the warning information generated by the server is returned to the terminal and presented to the user visually. This encourages the user to review their input, thus preventing inappropriate online communication.

[0764] For example, if a user tries to post a negative comment on social media such as "I hate my job," the sentiment analysis function can identify this as a negative emotion and inform the user that the comment may be problematic.

[0765] An example of a prompt message is, "Analyze the sentiment contained in the text entered by the user and generate appropriate feedback. Text: 'XXX'." In this way, the present invention supports healthy user communication by integrating multiple technologies to provide appropriate feedback.

[0766] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0767] Step 1:

[0768] The user enters text.

[0769] The user enters text data such as comments and messages on the device, and this input information is captured by the device. This input information becomes the data for the next encryption step.

[0770] Step 2:

[0771] The terminal encrypts the input information and sends it to the server.

[0772] The terminal encrypts the acquired text data using encryption technologies such as AES. This encrypted data enables secure transfer to the server and guarantees the protection of the input information after transfer. The output is encrypted data.

[0773] Step 3:

[0774] The server decrypts the data.

[0775] The server performs a decryption process to return the received encrypted data back to its original text. After receiving the decrypted data, it becomes the input data for the next analysis step. The output is the original text data.

[0776] Step 4:

[0777] The server analyzes the text data and detects offensive expressions.

[0778] The server uses a natural language processing library to analyze text data. It determines whether specific keywords or phrases in the input text match past terminology records and generates output indicating whether they are offensive expressions.

[0779] Step 5:

[0780] The server performs sentiment analysis.

[0781] The server launches a machine learning model to analyze sentiment based on text data. It utilizes models such as BERT to determine whether the input represents positive or negative sentiment and outputs the result.

[0782] Step 6:

[0783] The server generates warning information and provides feedback to the user.

[0784] The server generates appropriate warning information based on the results of aggressive language and sentiment analysis, and sends it to the terminal as feedback. This feedback includes specific measures such as suggestions for improving language use, and the output is warning information notified to the user.

[0785] Step 7:

[0786] The device displays a warning message.

[0787] The terminal displays warning information received from the server to the user in a visible format. Here, the user can review their input and make corrections as needed, thus maintaining the health of online communication. The output is feedback that the user can see.

[0788] (Application Example 2)

[0789] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0790] In conventional electronic trading systems, users may conduct transactions while emotionally overwhelmed, potentially leading to inappropriate communication and defamation. To prevent such situations and promote appropriate communication, a system is needed that recognizes users' emotions in real time and provides appropriate feedback.

[0791] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0792] In this invention, the server includes means for acquiring user data input, means for encrypting the data input and transmitting it to an information processing device, means for analyzing the decrypted character data in the information processing device and determining defamation if certain conditions are met, means for analyzing the user's emotions based on the character data and determining the emotional state, means for generating an appropriate interaction based on the emotional state and notifying the user, and means for generating a warning message based on the determination result and notifying the user. This makes it possible to provide flexible and appropriate interactions according to the user's emotional state and prevent inappropriate communication.

[0793] "Means for obtaining user data input" refers to a function that receives data entered by a user into the system and collects that information for processing.

[0794] "Means of encrypting data input and transmitting it to an information processing device" refers to a method of protecting data input obtained from a user using encryption technology and securely delivering the data to the destination information processing device.

[0795] "A means of analyzing decrypted character data using an information processing device and determining if it constitutes defamation if it meets specific conditions" refers to a process of decrypting encrypted character data, analyzing its content, evaluating whether it matches pre-set criteria, and then considering it to be defamatory.

[0796] "A means of analyzing a user's emotions and determining their emotional state based on text data" refers to a function that analyzes the text data entered by the user to evaluate their emotions at that time and identify whether their emotional state is positive or negative.

[0797] "A means of generating appropriate interactions based on emotional state and notifying the user" refers to the process of creating and communicating messages and suggestions designed to allow the user to respond appropriately, based on the analyzed emotional state of the user.

[0798] "A means of generating a warning message based on the judgment result and notifying the user" refers to a function that, when something is judged to be defamatory, creates a warning message for the user based on that information and sends a notification.

[0799] The system for realizing this invention consists mainly of a user, a terminal, and a server. The user inputs data via the terminal. The terminal receives this data, encrypts it, and then sends it to the server.

[0800] The server first decodes the received data. Next, it analyzes the text data using natural language processing techniques and, if necessary, compares it against specific conditions to determine if it constitutes defamation. These conditions utilize a vocabulary list of defamatory terms based on past judgments. Simultaneously, it analyzes the user's emotional state using a machine learning algorithm based on the text data from the user. This allows it to determine if the user is emotionally agitated and generate appropriate feedback.

[0801] Feedback provides appropriate interactions based on the user's emotional state, including warning messages and correction suggestions. The generated warning messages also include suggestions for reviewing the user's input.

[0802] The implementation of this system can utilize Python libraries (e.g., Spacy, NLTK) and machine learning frameworks (e.g., TensorFlow) on the server side. These technologies enable efficient analysis of received data, allowing for sentiment analysis and feedback generation.

[0803] For example, if a user enters a negative phrase such as "Do something!" during an electronic transaction, the server can analyze this phrase to determine the user's emotional state and provide thoughtful feedback such as, "Could you please provide additional information so we can understand the situation better?"

[0804] An example of a prompt to input into a generative AI model is: "Classify the following user input as positive or negative, check for slander, and generate an appropriate feedback message: 'Do something!'" Using this prompt enables highly accurate feedback.

[0805] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0806] Step 1:

[0807] The user enters a message using the terminal. This input data is received by the terminal as text data, including the user's intentions and feelings. The terminal receives this data, encrypts it using an encryption algorithm, and sends it to the server for further processing.

[0808] Step 2:

[0809] The server receives encrypted data sent from the terminal. The original text data is extracted by decrypting the received data. The decrypted data is then analyzed using natural language processing (NLP) techniques to determine if it contains defamation. Specifically, words and phrases in the text are compared against a vocabulary list of defamatory terms.

[0810] Step 3:

[0811] The server utilizes machine learning algorithms to analyze emotions from the decoded data. It evaluates the emotional aspects of the input data and classifies them as positive or negative. This process determines the user's emotional state, and the result is reflected in the prompt text of the generating AI model.

[0812] Step 4:

[0813] The server generates feedback based on the analysis of emotions and slander. This feedback includes specific warning messages and messages suggesting further action. For example, if emotions are heightened, it will generate advice such as, "Let's calm down and think about the situation."

[0814] Step 5:

[0815] Finally, the server sends the generated feedback message to the device, notifying the user. The user can then review the message on their device and revise their input based on the feedback provided. This process gives the user an opportunity to avoid slander and maintain appropriate communication.

[0816] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0817] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0818] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0819] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0820] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0821] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0822] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0823] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0824] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0825] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0826] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0827] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0828] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0829] 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.

[0830] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0831] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0832] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0833] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0834] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0835] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0836] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0837] The following is further disclosed regarding the embodiments described above.

[0838] (Claim 1)

[0839] Means for obtaining user input data,

[0840] Means for encrypting the aforementioned input data and transmitting it to a communication device,

[0841] A means for analyzing text data decoded by the aforementioned communication device and determining that it constitutes defamation if certain conditions are met,

[0842] A means for generating a warning message based on the aforementioned judgment result and notifying the user,

[0843] A system that includes this.

[0844] (Claim 2)

[0845] The system according to claim 1, which includes, as a specific condition, means for making a defamation determination using a list of defamatory words based on past determinations.

[0846] (Claim 3)

[0847] The system according to claim 1, wherein the generated warning message includes a suggestion to correct the input content.

[0848] "Example 1"

[0849] (Claim 1)

[0850] A device that sequentially acquires user input text,

[0851] A device that securely transmits the aforementioned input statement to a communication device using an encryption protocol,

[0852] A device that decodes data received by the aforementioned communication device, analyzes its content using natural language processing technology, and identifies defamatory elements,

[0853] Based on the aforementioned analysis results, a device is provided that generates warning information and presents it to the user.

[0854] A system that includes this.

[0855] (Claim 2)

[0856] The system according to claim 1, which utilizes a generative AI model to determine whether something is defamatory by referring to a list of words and phrases based on past analysis data.

[0857] (Claim 3)

[0858] The system according to claim 1, wherein the warning information includes suggestions for improving the input text.

[0859] "Application Example 1"

[0860] (Claim 1)

[0861] A device for acquiring user input data,

[0862] A device that encrypts the aforementioned input data and transmits it to a device having a communication function,

[0863] A device that analyzes text data decoded by the aforementioned communication device and determines that it is defamatory if it meets certain conditions,

[0864] A device that generates a warning message based on the aforementioned judgment result and notifies the user,

[0865] A device that displays the aforementioned warning message based on the input content in the transaction memo when the user conducts an electronic transaction,

[0866] A system that includes this.

[0867] (Claim 2)

[0868] The system according to claim 1, which includes, as a specific condition, a device for determining defamation using a vocabulary set of defamatory terms based on past analysis results.

[0869] (Claim 3)

[0870] The system according to claim 1, wherein the generated warning message includes a suggestion to correct the input content and improves the security of electronic transactions.

[0871] "Example 2 of combining an emotion engine"

[0872] (Claim 1)

[0873] Means for obtaining user input information,

[0874] Means for transmitting the aforementioned input information to a communication device using data encryption technology,

[0875] A means for analyzing the text decoded by the aforementioned communication device and determining if it is an offensive expression if it meets certain conditions,

[0876] A means for generating warning information based on the analysis results and notifying the user,

[0877] A means including a sentiment analysis function that performs sentiment analysis on user input text,

[0878] Means for identifying negative emotional states,

[0879] A means for generating considerate warning information corresponding to the aforementioned emotional state,

[0880] A system that includes this.

[0881] (Claim 2)

[0882] The system according to claim 1, which includes means for making a determination using a record of offensive language terms based on past judgments as the aforementioned specific conditions.

[0883] (Claim 3)

[0884] The system according to claim 1, wherein the generated warning information includes suggestions for correcting the input content.

[0885] "Application example 2 when combining with an emotional engine"

[0886] (Claim 1)

[0887] Means for obtaining user data input,

[0888] Means for encrypting the aforementioned data input and transmitting it to an information processing device,

[0889] A means for analyzing the character data decoded by the aforementioned information processing device and determining that it constitutes defamation if certain conditions are met,

[0890] A means for analyzing the user's emotions and determining their emotional state based on the aforementioned text data,

[0891] A means for generating an appropriate interaction based on the aforementioned emotional state and notifying the user,

[0892] A means for generating a warning message based on the aforementioned judgment result and notifying the user,

[0893] A system that includes this.

[0894] (Claim 2)

[0895] The system according to claim 1, wherein, as a specific condition, a defamation determination is made using a vocabulary list of defamatory terms based on past determinations.

[0896] (Claim 3)

[0897] The system according to claim 1, wherein the generated warning message includes a suggestion to correct the data input. [Explanation of Symbols]

[0898] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A device for acquiring user input data, A device that encrypts the aforementioned input data and transmits it to a device having a communication function, A device that analyzes text data decoded by the aforementioned communication device and determines that it is defamatory if it meets certain conditions, A device that generates a warning message based on the aforementioned judgment result and notifies the user, A device that displays the aforementioned warning message based on the input content in the transaction memo when the user conducts an electronic transaction, A system that includes this.

2. The system according to claim 1, which includes, as a specific condition, a device for determining defamation using a vocabulary set of defamatory terms based on past analysis results.

3. The system according to claim 1, wherein the generated warning message includes a suggestion to correct the input content and improves the security of electronic transactions.

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