system

Abstract

This system provides a balance of transparency and data protection to address issues such as the lack of transparency in training datasets for large-scale language models and the potential exposure of copyrighted and personal information contained in those datasets, enabling users to confidently utilize AI model training data. [Solution] A means for searching for data in a database based on a data identifier provided by the user, A means for filtering confidential information and copyrighted content from the retrieved data, Means for providing the filtered data to the user, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a 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 a character of the chatbot, 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] Modern large-scale language models are facing problems such as the lack of transparency of training datasets and the disclosure of copyright-protected information and personal information that the datasets may contain. Such problems can damage the trust of data providers and users and may have an adverse impact on the popularization and use of AI. Furthermore, when the data disclosure method is inappropriate, the risks of copyright infringement and privacy infringement increase. Therefore, an object of this invention is to provide a system that achieves both transparency and data protection so that users can use the training data of AI models with confidence.

Means for Solving the Problems

[0005] The present invention solves the above problems by the following means: it provides a means for searching for data in a database based on a data identifier provided by the user; it also includes a means for filtering confidential information and copyrighted content from the retrieved data, thereby achieving transparency of the dataset and reducing legal risks; and it provides a means for providing the filtered data to the user. A system including these three means enables secure and transparent data provision. Furthermore, this system also includes a means for notifying the user if no corresponding data entry is found in the database. This allows the user to quickly confirm the existence of the data.

[0006] A "user" is an entity that uses the system to search for and retrieve data.

[0007] A "data identifier" is information used to uniquely identify a specific data entry.

[0008] A "database" is a storage device and its management system for storing and managing a large number of data entries.

[0009] "Means of retrieving data" refers to methods and devices for finding data entries within a database based on specific data identifiers.

[0010] "Confidential information" refers to information that should be restricted from being made public, such as personal information and information related to privacy.

[0011] "Copyright-protected content" refers to content that should be protected by copyright law and whose use or publication without permission is not permitted.

[0012] "Filtering means" refers to methods and apparatus for removing or concealing specific information from data entries.

[0013] "Filtered data" refers to data from which confidential information and copyrighted content have been removed, making it available for public release.

[0014] "Means of providing" refers to methods and apparatus for transmitting or displaying processed data to a user.

[0015] "Means for notifying that the relevant data does not exist" refers to methods and devices for informing a user of the fact that data corresponding to a specific data identifier cannot be found as a result of a database search. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 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 Embodiment 2 when the 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 the emotion engine is combined.

Mode for Carrying Out the Invention

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] To implement this invention, first, the user provides a specific data identifier and sends a request to the server. The details of the system's processing are described below.

[0038] System Configuration

[0039] Database settings:

[0040] The server sets up a database to store the training data. This database contains many data entries, each identified by a unique data identifier. For example, data ID "data1" contains the following information:

[0041] {

[0042] "content": "Sample text data",

[0043] "author": "Author A",

[0044] "personal_info": "Sensitive Info",

[0045] "copyrighted_content": "Some copyrighted content"

[0046] }

[0047] Processing user requests

[0048] User request:

[0049] The user sends a specific data identifier (for example, data ID "data1") to the server. Upon receiving the request, the server searches the database and retrieves the corresponding data.

[0050] Data acquisition and filtering

[0051] Data acquisition:

[0052] The server searches the database for the corresponding data entry based on the data identifier provided by the user. When the data entry is found, the server retrieves its details.

[0053] Filtering of confidential and copyrighted content:

[0054] The retrieved data entries may contain confidential information (e.g., "personal_info") or copyrighted content (e.g., "copyrighted_content"). To filter out this information, the server removes specific fields. The filtered data is then made publicly available.

[0055] Providing data to users

[0056] Data provided after filtering:

[0057] The filtered data is provided to the user. For example, if the data ID is "data1", the filtered data will look like this:

[0058] {

[0059] "content": "Sample text data",

[0060] "author": "Author A"

[0061] }

[0062] This will allow users to safely access data from which confidential and copyrighted information has been removed.

[0063] Handling when data is not found

[0064] Notification if data is not found:

[0065] If the database does not contain data corresponding to the data identifier provided by the user, the server will notify the user. This notification allows the user to immediately recognize that the relevant data does not exist.

[0066] Specific example

[0067] Specific example 1:

[0068] The user requests data ID "data1". The server searches the database and retrieves the following information.

[0069] {

[0070] "content": "Sample text data",

[0071] "author": "Author A",

[0072] "personal_info": "Sensitive Info",

[0073] "copyrighted_content": "Some copyrighted content"

[0074] }

[0075] The server performs filtering to remove confidential and copyrighted information. The filtered data will look like this:

[0076] {

[0077] "content": "Sample text data",

[0078] "author": "Author A"

[0079] }

[0080] The server then provides the filtered data to the user.

[0081] Specific example 2:

[0082] The user requests data with the non-existent data ID "data3". The server searches the database but cannot find the matching data, and therefore notifies the user.

[0083] In this way, this invention enables users to confidently utilize AI model training data, achieving both data transparency and protection.

[0084] The following describes the processing flow.

[0085] Step 1:

[0086] The user specifies a particular data identifier (e.g., data ID "data1") from their device and sends a request to the server to request data details.

[0087] Step 2:

[0088] The server extracts a data identifier from the received request and searches the database based on that identifier.

[0089] Step 3:

[0090] The server searches the database for a matching data identifier and retrieves the corresponding data entry. For example, it retrieves the data corresponding to data ID "data1".

[0091] Step 4:

[0092] The server identifies and filters out sensitive information (e.g., the "personal_info" field) and copyrighted content (e.g., the "copyrighted_content" field) from the retrieved data entries.

[0093] Step 5:

[0094] After the filtering process, the server generates data from which confidential and copyrighted information has been removed. Specifically, it creates a new data object with unnecessary fields deleted.

[0095] Step 6:

[0096] The server returns the filtered data to the user. This data does not contain confidential information or copyrighted material, so it can be used with confidence.

[0097] Step 7:

[0098] If a data entry corresponding to a data identifier does not exist in the database, the server will notify the user that "the data does not exist."

[0099] Step 8:

[0100] Users can receive and use data sent from the server. If the data does not exist, they can take action such as specifying a different data identifier.

[0101] (Example 1)

[0102] 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."

[0103] The problem that this invention aims to solve is to achieve both data transparency and protection simultaneously by securely filtering out data containing confidential information and copyrighted content when searching for data in a database based on a data identifier provided by the user, and then providing that data to the user. Another objective is to improve the user experience by immediately notifying the user if the relevant data does not exist.

[0104] 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.

[0105] In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for filtering confidential information and copyrighted content from the searched data, means for providing the filtered data to the user, and means for notifying the user if no matching data exists in the database. As a result, the user can use the data from which confidential information and copyrighted content have been removed with peace of mind, and can also immediately recognize if the data does not exist.

[0106] A "user" is an individual, legal entity, or other entity that uses the system to provide a data identifier and seek to retrieve information.

[0107] A "data identifier" is a string or number used to uniquely identify a specific data entry within a database.

[0108] A "server" is a computer system responsible for managing a database, retrieving data, filtering data, and providing data to users.

[0109] A "database" is an information system that stores multiple data entries and allows them to be searched and managed in response to queries.

[0110] "Confidential information" refers to sensitive information such as personal information and trade secrets that should not be made public.

[0111] "Copyright-protected content" refers to creations and content protected by copyright law.

[0112] "Filtering" is the process of removing unnecessary information from data based on specific criteria.

[0113] "Searching" is the process of finding data entries within a database based on a specific data identifier.

[0114] "Notification" is the act of conveying specific information to a user, and it is performed by a system.

[0115] "Providing" refers to the act of the server sending filtered data back to the user.

[0116] To implement this invention, a user, a server, and a database are used. A detailed embodiment of this system is described below.

[0117] First, the user uses a device (e.g., computer, smartphone, tablet) to enter a specific data identifier. This data identifier is a string or number used to identify a unique data entry in the database. The data identifier entered by the user via a web browser or dedicated application is sent to the server over the internet. An example of a prompt message is, "Please search the database using data ID 'data1'."

[0118] When the server receives a request, it searches the database based on the data identifier. Database management systems used by the server include, for example, MySQL® and PostgreSQL. The server executes an SQL query to find the data entry corresponding to the specified data identifier. If no matching data entry is found, the server notifies the user accordingly.

[0119] The server loads data entries retrieved from the database into memory and then filters them for confidential and copyrighted information. The filtering process removes specific fields such as "personal_info" and "copyrighted_content" from the retrieved data entries. This data analysis and removal is performed using programming languages ​​such as Python and Java.

[0120] The filtered data does not contain confidential or copyrighted information, so it can be safely provided to users. The server returns the filtered data as an HTTP response and displays it on the user's device. This allows users to access safe and transparent data.

[0121] Specific example 1:

[0122] The user requests data ID "data1". This data identifier is sent to the database via the server. The server retrieves the data, filters it, and finally provides the filtered data to the user. The data will be in the following format.

[0123] {

[0124] "content": "Sample text data",

[0125] "author": "Author A"

[0126] }

[0127] An example of a prompt message is, "Please search for data ID 'data1' and provide the filtered data."

[0128] Specific example 2:

[0129] A user requests data with the non-existent data ID "data3". The server searches the database but cannot find the corresponding data entry, so it notifies the user with the message "The specified data could not be found."

[0130] This system allows users to access securely filtered data based on provided data identifiers, while also promptly notifying them if data is unavailable. This embodiment of the invention makes it possible to achieve both data transparency and protection.

[0131] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0132] Step 1:

[0133] User enters and submits data identifier

[0134] The user uses their device to enter a specific data identifier (e.g., data ID "data1") and sends a request to the server. The data identifier entered at this time becomes the input data. The interface used by the user is often a web browser or a dedicated application. Specifically, the user enters "data1" into the input form of the web browser and clicks the "Submit" button. As output, a request containing the data identifier is sent to the server.

[0135] Step 2:

[0136] The server receives the request.

[0137] The server receives a request from the user. The input here is an HTTP request containing a data identifier sent by the user. The server parses this request and extracts the data identifier. Specifically, the server receives a GET or POST request and parses the data identifier "data1" within the request. The output is the data identifier to be searched for.

[0138] Step 3:

[0139] The server searches the database.

[0140] The server searches the database based on a data identifier. The input is the extracted data identifier "data1". The server executes an SQL query to find the corresponding data entry in the database. Specifically, the server executes a query like "SELECT FROM dataset WHERE data_id='data1'". The output is the data entry retrieved from the database.

[0141] Step 4:

[0142] The server retrieves the data.

[0143] The server retrieves the relevant data entries from the database and loads them into memory. The input here is the data entries retrieved from the database. Specifically, the database management system (e.g., MySQL, PostgreSQL) returns the search results. The output is the retrieved data entries, and for example, it takes the following format:

[0144] json

[0145] {

[0146] "content": "Sample text data",

[0147] "author": "Author A",

[0148] "personal_info": "Sensitive Info",

[0149] "copyrighted_content": "Some copyrighted content"

[0150] }

[0151] Step 5:

[0152] The server filters out confidential and copyrighted content.

[0153] The server filters out confidential and copyrighted content from the retrieved data entries. The input is the original retrieved data entry. Specifically, the server parses the JSON data and removes the specific fields "personal_info" and "copyrighted_content". The output is the filtered data entry, which has the following format as an example.

[0154] json

[0155] {

[0156] "content": "Sample text data",

[0157] "author": "Author A"

[0158] }

[0159] Step 6:

[0160] The server provides the filtered data to the user.

[0161] The server returns filtered data to the user. The input is the filtered data entry. Specifically, the server returns the filtered data as an HTTP response and displays it on the user's terminal. The output is the filtered data that the user can see on their terminal.

[0162] Step 7:

[0163] The server will notify if data cannot be found.

[0164] If no data corresponding to the specified data identifier exists in the database, the server will notify the user. The input is the case where the database search results are found to be empty. Specifically, the server will return an HTTP response with a message such as "The specified data was not found." The output is the error message displayed to the user.

[0165] (Application Example 1)

[0166] 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."

[0167] When using data in a database, it is crucial to ensure the security and transparency of data, including confidential information and copyrighted material. However, many current systems have insufficient filtering capabilities, resulting in an environment where users cannot use data with confidence. Furthermore, there is a lack of established methods for providing filtered data to users quickly and appropriately. Additionally, there is a lack of proper notification mechanisms when data cannot be found. These problems need to be addressed to provide users with a reliable data delivery service.

[0168] 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.

[0169] In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for filtering confidential information and copyrighted content from the searched data, means for providing the filtered data to the user, and means for notifying the user if the data is not found. This allows the user to quickly and securely obtain data from which confidential information and copyrighted content have been removed, as well as receive appropriate notification if the data does not exist.

[0170] A "user" is a person or entity that uses a system to request data.

[0171] A "data identifier" is a piece of identification information used to uniquely identify a specific data entry within a database.

[0172] A "database" is a system that stores a large number of data entries and manages them using specific identifiers.

[0173] "Confidential information" refers to information that is not disclosed to anyone other than specific users in order to prevent unauthorized use.

[0174] "Copyright-protected content" refers to content that is protected by copyright law and cannot be used without permission.

[0175] "Filtering" is the process of removing specific information from data.

[0176] "Means of providing" refers to means of displaying or transmitting acquired data to the user.

[0177] "Means of notification" refers to a means of informing the user if data cannot be found.

[0178] A "smartphone" is a type of mobile phone, an electronic device capable of running a variety of applications.

[0179] "Smart glasses" are glasses-type wearable devices that have the function of displaying visual information.

[0180] This invention is a system that searches a database for data based on a data identifier provided by the user, filters the data, and provides it to the user. Specifically, it is implemented via a smartphone application or smart glasses.

[0181] The server has a means of searching for data entries in the database. When a user submits a data identifier, the server searches the database based on that identifier and retrieves the corresponding data entry.

[0182] The server then filters the retrieved data entries for confidential and copyrighted information. This filtering process involves deleting specific fields. For example, the "personal_info" and "copyrighted_content" fields might be removed, leaving only publicly available information.

[0183] The filtered data is provided to the user. Users can receive the data via their smartphone or smart glasses. If data corresponding to a data identifier is not found, the server will notify the user.

[0184] The hardware used includes smartphones (iOS and Android® devices) and smart glasses (e.g., Google® Glass®). The software used is Flask, a Python web framework, for data processing and filtering.

[0185] Software and hardware usage examples

[0186] 1. Database Setup: Data is stored in a JSON database on the server.

[0187] 2. Processing User Requests: Users enter a data identifier using a smartphone app or smart glasses and send a request to the server.

[0188] 3. Data Retrieval and Filtering: The server retrieves the corresponding data entries from the database and filters out confidential information and copyrighted content.

[0189] 4. Data Provision: Filtered data will be displayed on the user's smartphone or smart glasses. This ensures that users can use the data with peace of mind.

[0190] Specific example

[0191] Example 1:

[0192] The user requests data identifier "data1" using their smartphone. The server retrieves the following data entry from the database.

[0193] json

[0194] {

[0195] "content": "Sample text data",

[0196] "author": "Author A",

[0197] "personal_info": "Sensitive Info",

[0198] "copyrighted_content": "Some copyrighted content"

[0199] }

[0200] The server performs filtering and provides the following data to the user.

[0201] json

[0202] {

[0203] "content": "Sample text data",

[0204] "author": "Author A"

[0205] }

[0206] Example 2:

[0207] A user requests data identifier "data3" using smart glasses. The server searches the database but cannot find the matching data. The server notifies the user of this.

[0208] Example of a prompt:

[0209] "We have specified 'data1' as the identifier for the training data. Please provide the data for the entry corresponding to this data identifier, with all confidential and copyrighted information removed."

[0210] In this way, this invention provides an environment in which users can use data with peace of mind, and realizes a system that achieves both data transparency and protection.

[0211] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0212] Step 1:

[0213] The user enters a specific data identifier using a smartphone or smart glasses. This input is then sent to the server via the application.

[0214] Input: Data identifier (e.g., "data1")

[0215] Specific action: The user enters a data identifier into the application's input field and taps the submit button.

[0216] Step 2:

[0217] The server receives a data identifier provided by the user. Based on the received data identifier, it searches the database and retrieves the corresponding data entry.

[0218] Input: Data identifier submitted by the user

[0219] Data processing: The server searches the database and retrieves the corresponding data entries.

[0220] Output: Data entry (Example: {

[0221] "content": "Sample text data",

[0222] "author": "Author A",

[0223] "personal_info": "Sensitive Info",

[0224] "copyrighted_content": "Some copyrighted content"

[0225] })

[0226] Specific operation: The server executes a database query and loads the corresponding data entries into memory.

[0227] Step 3:

[0228] The server filters out confidential and copyrighted content from the retrieved data entries. Specifically, it removes specified fields (e.g., "personal_info" and "copyrighted_content").

[0229] Input: Retrieved data entries

[0230] Data processing: Filter the data to remove the specified fields.

[0231] Output: Filtered data (Example: {

[0232] "content": "Sample text data",

[0233] "author": "Author A"

[0234] })

[0235] Specific operation: The server parses the JSON structure of the data entry and removes unnecessary fields.

[0236] Step 4:

[0237] The server provides the filtered data to the user. The user can view the filtered data through the application.

[0238] Input: Filtered data

[0239] Output: Data displayed on the user's application screen.

[0240] Specific operation: The server generates filtered data in JSON format and sends it to the user's device. The user's device displays the received data on the screen.

[0241] Step 5:

[0242] If the data corresponding to the data identifier is not found in the database, the server will notify the user accordingly.

[0243] Input: Data identifier provided by the user

[0244] Output: Notification message when data is not found (e.g., "Data not found")

[0245] Specific operation: If the server does not find the data as a result of the database search, it generates an appropriate notification message and sends it to the user's device. The user's device displays the notification message on the screen.

[0246] These steps enable the system to filter and provide data efficiently and securely.

[0247] 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.

[0248] To implement this invention, it is necessary to construct a system that recognizes the user's emotions and dynamically adjusts data filtering based on those emotions. The details of this system's processing are described below.

[0249] System Configuration

[0250] Database settings:

[0251] The server sets up a database to store the training data. This database contains many data entries, each identified by a unique data identifier. For example, data ID "data1" contains the following information:

[0252] {

[0253] "content": "Sample text data",

[0254] "author": "Author A",

[0255] "personal_info": "Sensitive Info",

[0256] "copyrighted_content": "Some copyrighted content"

[0257] }

[0258] Emotion engine settings:

[0259] The server has an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's text and voice input to identify the user's emotions.

[0260] Processing user requests

[0261] User request:

[0262] The user sends a specific data identifier (for example, data ID "data1") to the server. Simultaneously, the emotion engine recognizes emotions from the user's input. Upon receiving a request, the server searches its database and retrieves the corresponding data.

[0263] Data acquisition and filtering

[0264] Data acquisition:

[0265] The server searches the database for the corresponding data entry based on the data identifier provided by the user. When the data entry is found, the server retrieves its details.

[0266] Adjusting emotion-based filtering:

[0267] The server adjusts the strictness of its filtering process based on the user's emotions recognized by the emotion engine. For example, if a user expresses emotions such as "anxiety" or "worry," the server will more strictly filter out confidential and copyrighted content. On the other hand, if a user expresses emotions such as "reassurance" or "trust," the filtering strictness will be reduced.

[0268] Filtering process:

[0269] The server identifies and filters out confidential information (e.g., the "personal_info" field) and copyrighted content (e.g., the "copyrighted_content" field). The filtered data is then made publicly available.

[0270] Providing data to users

[0271] Data provided after filtering:

[0272] The filtered data is provided to the user. After adjustment according to the user's emotions, for example, in the case of data ID "data1", the data after filtering changes as follows.

[0273] {

[0274] "content": "Sample text data",

[0275] "author": "Author A"

[0276] }

[0277] Handling when data is not found

[0278] Notification when data is not found:

[0279] If there is no data corresponding to the data identifier provided by the user in the database, the server notifies the user to that effect. With this notification, the user can immediately recognize that the corresponding data does not exist.

[0280] Specific example

[0281] Specific example 1:

[0282] The user requests data ID "data" and shows the emotion of "uneasy" at that time. The server searches the database and obtains the following information.

[0283] {

[0284] "content": "Sample text data",

[0285] <00009​​​​​​ "copyrighted_content": "Some copyrighted content"

[0288] }

[0289] The server performs filtering to more strictly remove confidential information and copyrighted content. The filtered data will look like this:

[0290] {

[0291] "content": "Sample text data",

[0292] "author": "Author A"

[0293] }

[0294] The server then provides the filtered data to the user, ensuring they can use it with confidence.

[0295] Specific example 2:

[0296] The user requests data ID "data2" and expresses the emotion of "peace of mind." The server searches the database and retrieves the following information.

[0297] {

[0298] "content": "Another sample text",

[0299] "author": "Author B"

[0300] }

[0301] In this case, filtering is performed as usual because the data does not contain confidential information or copyrighted material. The server provides this data directly to the user.

[0302] In this way, the present invention provides a system that achieves both transparency and security by recognizing the user's emotions and dynamically adjusting data filtering based on them.

[0303] The processing flow will be described below.

[0304] Step 1:

[0305] The user specifies a data identifier (e.g., data ID "data1") from the terminal and sends a request to the server to request data details. At the same time, through the user's input (text or voice), the emotion engine analyzes the user's emotions.

[0306] Step 2:

[0307] The server extracts the data identifier from the received request and searches the database based on that identifier.

[0308] Step 3:

[0309] The server finds the matching data identifier in the database and retrieves the data entry. For example, it retrieves the data corresponding to the data ID "data1".

[0310] Step 4:

[0311] The emotion engine recognizes the emotion from the user's input. For example, it identifies emotions such as "uneasy", "at ease", "worried", etc.

[0312] Step 5:

[0313] The server adjusts the strictness of the filtering process based on the user's emotion recognized by the emotion engine. For example, if the user shows "uneasy", the filtering process is carried out strictly.

[0314] Step 6:

[0315] The server identifies and filters out sensitive information (e.g., "personal_info") and copyrighted content (e.g., "copyrighted_content") from the retrieved data entries.

[0316] Step 7:

[0317] After the filtering process is performed, the server generates data from which confidential information and copyrighted content have been removed. For example, in the case of data ID "data1", the filtered data will look like this:

[0318] {

[0319] "content": "Sample text data",

[0320] "author": "Author A"

[0321] }

[0322] Step 8:

[0323] The server returns the filtered data to the user. The user receives and uses this data on their device.

[0324] Step 9:

[0325] If a data entry corresponding to a data identifier does not exist in the database, the server will notify the user that "the data does not exist." The user will then receive this notification and take appropriate action, such as specifying a new data identifier.

[0326] (Example 2)

[0327] 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".

[0328] Traditional data filtering systems rely on simple rule-based filtering, uniformly removing confidential and copyrighted information without considering user emotions or circumstances. This lack of flexibility in responding to user needs is a major challenge. In particular, providing appropriate information in situations where emotionally and contextually relevant data is required can be difficult, leading to decreased user satisfaction.

[0329] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for filtering confidential information and copyrighted content from the retrieved data, means for recognizing the user's emotions and dynamically adjusting the strictness of the filtering based on those emotions, and means for providing the filtered data to the user. This enables flexible data provision in response to the user's emotions, thereby improving user satisfaction.

[0330] A "user" is an individual or organization that uses the system to search for and retrieve data.

[0331] A "data identifier" is an identifier used to uniquely identify a specific data entry within a database.

[0332] A "database" is a storage system for storing and managing multiple data entries.

[0333] "Confidential information" refers to sensitive information that should not be made public and should be protected.

[0334] "Copyright-protected content" refers to works or content that should be protected under copyright law.

[0335] "Filtering" is the process of removing unnecessary or inappropriate parts from data based on specific conditions.

[0336] "Emotion" refers to the psychological and emotional state that a user exhibits towards the system.

[0337] An "emotion engine" is software or hardware that analyzes user input (text or voice) and identifies their emotions.

[0338] "Dynamic adjustment" means changing the strictness or parameters of a process in real time or as needed, depending on the conditions and circumstances.

[0339] "Searching" means retrieving data within a database based on specified conditions.

[0340] This invention relates to a system that recognizes user emotions and filters data based on those emotions. A detailed embodiment of the system is described below.

[0341] Database settings

[0342] The server configures a database that stores multiple data entries. Each entry in the database is identified by a unique data identifier and contains information such as the following:

[0343] {

[0344] "dataID": "data1",

[0345] "content": "Sample text data",

[0346] "author": "Author A",

[0347] "personal_info": "Sensitive Info",

[0348] "copyrighted_content": "Some copyrighted content"

[0349] }

[0350] Emotion Engine Settings

[0351] The server sets up an emotion engine to recognize the user's emotions. The emotion engine uses NLP (Natural Language Processing) libraries and speech recognition software (e.g., Google Cloud Speech-to-Text, IBM Watson® Natural Language Understanding).

[0352] Receiving user requests

[0353] The user sends a specific data identifier (e.g., data ID "data1") from their device to the server. Simultaneously, the emotion engine analyzes the user's input (text or voice) to identify the user's emotion. When the request reaches the server, the server searches its database and retrieves the corresponding data entry.

[0354] Data acquisition and filtering

[0355] The server searches the database for the corresponding data entry based on the data identifier and retrieves detailed information. It then filters the retrieved data for confidential and copyrighted content. This filtering is dynamically adjusted based on the user's emotions as perceived by the emotion engine.

[0356] Filtering process

[0357] The filtering process identifies and removes confidential information (e.g., the "personal_info" field) and copyrighted content (e.g., the "copyrighted_content" field).

[0358] Providing data to users

[0359] The filtered data is provided to the user through their device. This allows the user to use the filtered data with peace of mind.

[0360] Specific example

[0361] Specific example 1:

[0362] The user requests data ID "data1" and indicates the emotion "anxiety". The server searches the database and retrieves the following information.

[0363] {

[0364] "content": "Sample text data",

[0365] "author": "Author A",

[0366] "personal_info": "Sensitive Info",

[0367] "copyrighted_content": "Some copyrighted content"

[0368] }

[0369] The server performs filtering to strictly remove confidential information and copyrighted content. The filtered data will look like this:

[0370] {

[0371] "content": "Sample text data",

[0372] "author": "Author A"

[0373] }

[0374] Specific example 2:

[0375] The user requests data ID "data2" and expresses the emotion of "peace of mind." The server searches the database and retrieves the following information.

[0376] {

[0377] "content": "Another sample text",

[0378] "author": "Author B"

[0379] }

[0380] In this case, filtering is not necessary, and the server provides this data directly to the user.

[0381] Example of a prompt

[0382] 1. Prompt message when the user is experiencing feelings of "anxiety":

[0383] "Emotion: Anxiety. Data ID: data1. Please strictly remove confidential information and copyrighted content from the retrieved data."

[0384] 2. Prompt message to use when the user feels "reassured":

[0385] "Emotion: Relief. Data ID: data2. Please provide this data directly."

[0386] This system enables flexible data filtering and delivery tailored to the user's emotions.

[0387] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0388] Step 1:

[0389] Database settings:

[0390] The server configures a database to store training data. It receives JSON data containing data entries as input. These data entries are identified by unique data identifiers, each with fields such as "content," "author," "personal_info," and "copyrighted_content." The server saves these data entries to the database. The configured database is generated as output.

[0391] Step 2:

[0392] Preparing the emotional engine:

[0393] The server sets up an emotion engine to recognize the user's emotions. As input, the server receives configuration files and API keys for NLP (Natural Language Processing) libraries and speech recognition software (e.g., Google Cloud Speech-to-Text, IBM Watson Natural Language Understanding). The server installs this software and applies its configuration. As output, the emotion engine becomes available for use.

[0394] Step 3:

[0395] Receiving user requests:

[0396] The user sends a specific data identifier (e.g., data ID "data1") to the server via their device. The server receives the user's request data and text or audio data for emotion recognition as input. The server parses these inputs and sends them, along with the data identifier, to the emotion engine. The output is the recognition of the user's emotion, ready for processing based on that emotion.

[0397] Step 4:

[0398] Searching and retrieving data:

[0399] The server searches the database based on the data identifier received from the user. It receives the data identifier as input and generates a database search query. The server searches for the corresponding data entry in the database and retrieves detailed information. The data entry is retrieved as output.

[0400] Step 5:

[0401] Adjusting emotion-based filtering:

[0402] The server dynamically adjusts the filtering strictness based on the user's emotions recognized by the emotion engine. It receives user emotion data and retrieved data entries as input. The server analyzes the emotion data and, for example, sets stricter filtering criteria if the user indicates emotions such as "anxiety" or "worry." The output is the adjusted filtering settings.

[0403] Step 6:

[0404] Data filtering process:

[0405] The server removes sensitive and copyrighted content from data entries based on the specified filtering settings. It receives filtering settings and data entries as input. The server filters fields such as "personal_info" and "copyrighted_content" to remove unwanted information. The filtered data is then generated as output.

[0406] Step 7:

[0407] Providing filtered data:

[0408] The server sends filtered data to the user. It receives filtered data as input and sends it to the user's terminal. As output, the user can receive the filtered data through their terminal.

[0409] Step 8:

[0410] Notification if data is not found:

[0411] The server notifies the user if data corresponding to the specified data identifier does not exist in the database. The input confirms that the search results are empty. The server generates an error message stating "no matching data found" and sends it to the user's terminal. The output informs the user that the specified data does not exist.

[0412] (Application Example 2)

[0413] 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".

[0414] Traditional systems lacked dynamic data filtering based on individual user emotional states, instead applying uniform filtering rules to all users. This meant they couldn't consider the anxiety or reassurance specific users felt regarding the data. As a result, providing flexible data tailored to user emotions was difficult, hindering improvements in the user experience.

[0415] 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.

[0416] In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for analyzing the user's emotions using an emotion engine that recognizes the user's emotions, means for dynamically adjusting and filtering confidential information and copyrighted content from the retrieved data based on the user's emotions, and means for providing the filtered data to the user. This allows for dynamic adjustment of the filtering strictness according to the user's emotions, enabling flexible data provision based on the emotions of individual users.

[0417] "User" refers to an individual or group that uses the system.

[0418] A "data identifier" is information that uniquely identifies a specific data entry within a database.

[0419] A "database" is a system or device for systematically storing and managing data.

[0420] An "emotion engine" is software or hardware that analyzes and identifies emotions from user input such as facial expressions and voice.

[0421] "Emotions" refer to the user's psychological state, including states such as "reassurance" and "anxiety."

[0422] "Confidential information" refers to personal information or important information that should not be made public.

[0423] "Copyright-protected content" refers to creative content and materials that should be protected under copyright law.

[0424] "Dynamic adjustment" means changing settings and behavior in real time according to conditions and circumstances.

[0425] "Filtering" is the process of selecting or deleting data based on specific conditions.

[0426] A "data entry" is a single unit of data stored within a database.

[0427] "To analyze" means to examine data in detail and clarify its structure and meaning.

[0428] "To provide" means to deliver data or services to a user or make them available for use.

[0429] In order to implement this invention, it is necessary to build a system that recognizes the user's emotions and dynamically adjusts data filtering based on those emotions.

[0430] System Configuration

[0431] Database settings:

[0432] The server sets up a database to store the training data. This database contains many data entries, each identified by a unique data identifier.

[0433] Emotion engine settings:

[0434] The server uses an emotion engine to recognize the user's emotions. This emotion engine analyzes the user's text, voice, or image input to identify their emotions. Specifically, it utilizes TENSORFLOW® and OpenCV to recognize emotions in real time.

[0435] Processing user requests

[0436] User request:

[0437] The user sends a specific data identifier to the server. Simultaneously, the sentiment engine analyzes the user's emotions. Upon receiving a request, the server searches its database and retrieves the corresponding data.

[0438] Data acquisition and filtering

[0439] Data acquisition:

[0440] The server searches the database for the corresponding data entry based on the data identifier provided by the user and retrieves its details.

[0441] Adjusting emotion-based filtering:

[0442] The server adjusts the strictness of filtering based on the user's emotions recognized by the emotion engine. For example, if the user indicates "anxiety" or "worry," the server strictly filters out confidential and copyrighted content. On the other hand, if the user indicates "reassurance" or "trust," the filtering strictness is relaxed.

[0443] Filtering process:

[0444] The server identifies and filters out confidential and copyrighted information. After filtering, the data is converted into a format that can be publicly released.

[0445] Providing data to users

[0446] Data provided after filtering:

[0447] The filtered data is provided to the user. For example, if the data ID is "data1", the filtered data will change as follows:

[0448] json

[0449] {

[0450] "content": "Sample text data",

[0451] "author": "Author A"

[0452] }

[0453] Specific example

[0454] Specific example 1:

[0455] The user requests data ID "data1" and indicates an emotion of "anxiety." The server searches the database and retrieves the following information:

[0456] json

[0457] {

[0458] "content": "Sample text data",

[0459] "author": "Author A",

[0460] "personal_info": "Sensitive Info",

[0461] "copyrighted_content": "Some copyrighted content"

[0462] }

[0463] The server performs filtering to completely remove confidential and copyrighted information. The filtered data will look like this:

[0464] json

[0465] {

[0466] "content": "Sample text data",

[0467] "author": "Author A"

[0468] }

[0469] Specific example 2:

[0470] When a user requests data ID "data2" and expresses the emotion of "peace of mind," the server searches the database and retrieves the following information:

[0471] json

[0472] {

[0473] "content": "Another sample text",

[0474] "author": "Author B"

[0475] }

[0476] Since this data does not contain any confidential information or copyrighted material, it will be processed as usual and provided to the user as is.

[0477] The data provided to users can be filtered based on emotions, allowing for a balance between transparency and security of information for the user.

[0478] Example of a prompt:

[0479] "Please provide information based on data ID 'data1'. Analyze and filter the sentiment of this image."

[0480] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0481] Step 1:

[0482] The user sends a data identifier and image data from their device to the server. The input includes the data identifier and image data used for emotion recognition. The output is the server receiving the data identifier and image data.

[0483] Step 2:

[0484] The server searches the database based on the received data identifier. The input is the data identifier provided by the user, and the output is the retrieved data entry. For example, if "data1" exists in the database, its details are retrieved.

[0485] Step 3:

[0486] The server uses the received image data to activate the emotion engine and analyze the user's emotions. The input is image data, and the output is the user's emotions identified by the emotion engine. Specifically, the server uses TensorFlow and OpenCV to perform image processing and classify emotions.

[0487] Step 4:

[0488] The server dynamically adjusts the strictness of data filtering based on the analyzed emotions. The input is the user's emotions and the searched data entries, while the output is the filtered data. For example, if the emotion "anxiety" is detected, confidential information and copyrighted content will be strictly filtered.

[0489] Step 5:

[0490] The server performs data filtering. The input is the original data entries retrieved from the database along with the adjusted filtering conditions, and the output is the filtered data. Specifically, the server deletes or masks specified fields from the data entries.

[0491] Step 6:

[0492] The server provides the filtered data to the user. The input is the filtered data, and the output is the data sent back to the user's terminal. Specifically, the server creates an HTTP response that includes the filtered data.

[0493] Step 7:

[0494] The server notifies the user if a corresponding data entry does not exist in the database. The input is the database search result, and the output is a notification message stating "data not found." Specifically, the server creates an HTTP response containing an appropriate error message.

[0495] 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.

[0496] 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.

[0497] 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.

[0498] [Second Embodiment]

[0499] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0500] 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.

[0501] 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).

[0502] 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.

[0503] 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.

[0504] 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).

[0505] 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.

[0506] 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.

[0507] 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.

[0508] 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.

[0509] 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.

[0510] 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".

[0511] To implement this invention, first, the user provides a specific data identifier and sends a request to the server. The details of the system's processing are described below.

[0512] System Configuration

[0513] Database settings:

[0514] The server sets up a database to store the training data. This database contains many data entries, each identified by a unique data identifier. For example, data ID "data1" contains the following information:

[0515] {

[0516] "content": "Sample text data",

[0517] "author": "Author A",

[0518] "personal_info": "Sensitive Info",

[0519] "copyrighted_content": "Some copyrighted content"

[0520] }

[0521] Processing user requests

[0522] User request:

[0523] The user sends a specific data identifier (for example, data ID "data1") to the server. Upon receiving the request, the server searches the database and retrieves the corresponding data.

[0524] Data acquisition and filtering

[0525] Data acquisition:

[0526] The server searches the database for the corresponding data entry based on the data identifier provided by the user. When the data entry is found, the server retrieves its details.

[0527] Filtering of confidential and copyrighted content:

[0528] The retrieved data entries may contain confidential information (e.g., "personal_info") or copyrighted content (e.g., "copyrighted_content"). To filter out this information, the server removes specific fields. The filtered data is then made publicly available.

[0529] Providing data to users

[0530] Data provided after filtering:

[0531] The filtered data is provided to the user. For example, if the data ID is "data1", the filtered data will look like this:

[0532] {

[0533] "content": "Sample text data",

[0534] "author": "Author A"

[0535] }

[0536] This will allow users to safely access data from which confidential and copyrighted information has been removed.

[0537] Handling when data is not found

[0538] Notification if data is not found:

[0539] If the database does not contain data corresponding to the data identifier provided by the user, the server will notify the user. This notification allows the user to immediately recognize that the relevant data does not exist.

[0540] Specific example

[0541] Specific example 1:

[0542] The user requests data ID "data1". The server searches the database and retrieves the following information.

[0543] {

[0544] "content": "Sample text data",

[0545] "author": "Author A",

[0546] "personal_info": "Sensitive Info",

[0547] "copyrighted_content": "Some copyrighted content"

[0548] }

[0549] The server performs filtering to remove confidential and copyrighted information. The filtered data will look like this:

[0550] {

[0551] "content": "Sample text data",

[0552] "author": "Author A"

[0553] }

[0554] The server then provides the filtered data to the user.

[0555] Specific example 2:

[0556] The user requests data with the non-existent data ID "data3". The server searches the database but cannot find the matching data, and therefore notifies the user.

[0557] In this way, this invention enables users to confidently utilize AI model training data, achieving both data transparency and protection.

[0558] The following describes the processing flow.

[0559] Step 1:

[0560] The user specifies a particular data identifier (e.g., data ID "data1") from their device and sends a request to the server to request data details.

[0561] Step 2:

[0562] The server extracts a data identifier from the received request and searches the database based on that identifier.

[0563] Step 3:

[0564] The server searches the database for a matching data identifier and retrieves the corresponding data entry. For example, it retrieves the data corresponding to data ID "data1".

[0565] Step 4:

[0566] The server identifies and filters out sensitive information (e.g., the "personal_info" field) and copyrighted content (e.g., the "copyrighted_content" field) from the retrieved data entries.

[0567] Step 5:

[0568] After the filtering process, the server generates data from which confidential and copyrighted information has been removed. Specifically, it creates a new data object with unnecessary fields deleted.

[0569] Step 6:

[0570] The server returns the filtered data to the user. This data does not contain confidential information or copyrighted material, so it can be used with confidence.

[0571] Step 7:

[0572] If a data entry corresponding to a data identifier does not exist in the database, the server will notify the user that "the data does not exist."

[0573] Step 8:

[0574] Users can receive and use data sent from the server. If the data does not exist, they can take action such as specifying a different data identifier.

[0575] (Example 1)

[0576] 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".

[0577] The problem that this invention aims to solve is to achieve both data transparency and protection simultaneously by securely filtering out data containing confidential information and copyrighted content when searching for data in a database based on a data identifier provided by the user, and then providing that data to the user. Another objective is to improve the user experience by immediately notifying the user if the relevant data does not exist.

[0578] 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.

[0579] In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for filtering confidential information and copyrighted content from the searched data, means for providing the filtered data to the user, and means for notifying the user if no matching data exists in the database. As a result, the user can use the data from which confidential information and copyrighted content have been removed with peace of mind, and can also immediately recognize if the data does not exist.

[0580] A "user" is an individual, legal entity, or other entity that uses the system to provide a data identifier and seek to retrieve information.

[0581] A "data identifier" is a string or number used to uniquely identify a specific data entry within a database.

[0582] A "server" is a computer system responsible for managing a database, retrieving data, filtering data, and providing data to users.

[0583] A "database" is an information system that stores multiple data entries and allows them to be searched and managed in response to queries.

[0584] "Confidential information" refers to sensitive information such as personal information and trade secrets that should not be made public.

[0585] "Copyright-protected content" refers to creations and content protected by copyright law.

[0586] "Filtering" is the process of removing unnecessary information from data based on specific criteria.

[0587] "Searching" is the process of finding data entries within a database based on a specific data identifier.

[0588] "Notification" is the act of conveying specific information to a user, and it is performed by a system.

[0589] "Providing" refers to the act of the server sending filtered data back to the user.

[0590] To implement this invention, a user, a server, and a database are used. A detailed embodiment of this system is described below.

[0591] First, the user uses a device (e.g., computer, smartphone, tablet) to enter a specific data identifier. This data identifier is a string or number used to identify a unique data entry in the database. The data identifier entered by the user via a web browser or dedicated application is sent to the server over the internet. An example of a prompt message is, "Please search the database using data ID 'data1'."

[0592] When the server receives a request, it searches the database based on the data identifier. Database management systems used by the server include, for example, MySQL and PostgreSQL. The server executes an SQL query to find the data entry corresponding to the specified data identifier. If no matching data entry is found, the server notifies the user accordingly.

[0593] The server loads data entries retrieved from the database into memory and then filters them for confidential and copyrighted information. The filtering process removes specific fields such as "personal_info" and "copyrighted_content" from the retrieved data entries. This data analysis and removal is performed using programming languages ​​such as Python or Java.

[0594] The filtered data does not contain confidential or copyrighted information, so it can be safely provided to users. The server returns the filtered data as an HTTP response and displays it on the user's device. This allows users to access safe and transparent data.

[0595] Specific example 1:

[0596] The user requests data ID "data1". This data identifier is sent to the database via the server. The server retrieves the data, filters it, and finally provides the filtered data to the user. The data will be in the following format.

[0597] {

[0598] "content": "Sample text data",

[0599] "author": "Author A"

[0600] }

[0601] An example of a prompt message is, "Please search for data ID 'data1' and provide the filtered data."

[0602] Specific example 2:

[0603] A user requests data with the non-existent data ID "data3". The server searches the database but cannot find the corresponding data entry, so it notifies the user with the message "The specified data could not be found."

[0604] This system allows users to access securely filtered data based on provided data identifiers, while also promptly notifying them if data is unavailable. This embodiment of the invention makes it possible to achieve both data transparency and protection.

[0605] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0606] Step 1:

[0607] User enters and submits data identifier

[0608] The user uses their device to enter a specific data identifier (e.g., data ID "data1") and sends a request to the server. The data identifier entered at this time becomes the input data. The interface used by the user is often a web browser or a dedicated application. Specifically, the user enters "data1" into the input form of the web browser and clicks the "Submit" button. As output, a request containing the data identifier is sent to the server.

[0609] Step 2:

[0610] The server receives the request.

[0611] The server receives a request from the user. The input here is an HTTP request containing a data identifier sent by the user. The server parses this request and extracts the data identifier. Specifically, the server receives a GET or POST request and parses the data identifier "data1" within the request. The output is the data identifier to be searched for.

[0612] Step 3:

[0613] The server searches the database.

[0614] The server searches the database based on a data identifier. The input is the extracted data identifier "data1". The server executes an SQL query to find the corresponding data entry in the database. Specifically, the server executes a query like "SELECT FROM dataset WHERE data_id='data1'". The output is the data entry retrieved from the database.

[0615] Step 4:

[0616] The server retrieves the data.

[0617] The server retrieves the relevant data entries from the database and loads them into memory. The input here is the data entries retrieved from the database. Specifically, the database management system (e.g., MySQL, PostgreSQL) returns the search results. The output is the retrieved data entries, and for example, it takes the following format:

[0618] json

[0619] {

[0620] "content": "Sample text data",

[0621] "author": "Author A",

[0622] "personal_info": "Sensitive Info",

[0623] "copyrighted_content": "Some copyrighted content"

[0624] }

[0625] Step 5:

[0626] The server filters out confidential and copyrighted content.

[0627] The server filters out confidential and copyrighted content from the retrieved data entries. The input is the original retrieved data entry. Specifically, the server parses the JSON data and removes the specific fields "personal_info" and "copyrighted_content". The output is the filtered data entry, which has the following format as an example.

[0628] json

[0629] {

[0630] "content": "Sample text data",

[0631] "author": "Author A"

[0632] }

[0633] Step 6:

[0634] The server provides the filtered data to the user.

[0635] The server returns filtered data to the user. The input is the filtered data entry. Specifically, the server returns the filtered data as an HTTP response and displays it on the user's terminal. The output is the filtered data that the user can see on their terminal.

[0636] Step 7:

[0637] The server will notify if data cannot be found.

[0638] If no data corresponding to the specified data identifier exists in the database, the server will notify the user. The input is the case where the database search results are found to be empty. Specifically, the server will return an HTTP response with a message such as "The specified data was not found." The output is the error message displayed to the user.

[0639] (Application Example 1)

[0640] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0641] When using data in a database, it is crucial to ensure the security and transparency of data, including confidential information and copyrighted material. However, many current systems have insufficient filtering capabilities, resulting in an environment where users cannot use data with confidence. Furthermore, there is a lack of established methods for providing filtered data to users quickly and appropriately. Additionally, there is a lack of proper notification mechanisms when data cannot be found. These problems need to be addressed to provide users with a reliable data delivery service.

[0642] 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.

[0643] In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for filtering confidential information and copyrighted content from the searched data, means for providing the filtered data to the user, and means for notifying the user if the data is not found. This allows the user to quickly and securely obtain data from which confidential information and copyrighted content have been removed, as well as receive appropriate notification if the data does not exist.

[0644] A "user" is a person or entity that uses a system to request data.

[0645] A "data identifier" is a piece of identification information used to uniquely identify a specific data entry within a database.

[0646] A "database" is a system that stores a large number of data entries and manages them using specific identifiers.

[0647] "Confidential information" refers to information that is not disclosed to anyone other than specific users in order to prevent unauthorized use.

[0648] "Copyright-protected content" refers to content that is protected by copyright law and cannot be used without permission.

[0649] "Filtering" is the process of removing specific information from data.

[0650] "Means of providing" refers to means of displaying or transmitting acquired data to the user.

[0651] "Means of notification" refers to a means of informing the user if data cannot be found.

[0652] A "smartphone" is a type of mobile phone, an electronic device capable of running a variety of applications.

[0653] "Smart glasses" are glasses-type wearable devices that have the function of displaying visual information.

[0654] This invention is a system that searches a database for data based on a data identifier provided by the user, filters the data, and provides it to the user. Specifically, it is implemented via a smartphone application or smart glasses.

[0655] The server has a means of searching for data entries in the database. When a user submits a data identifier, the server searches the database based on that identifier and retrieves the corresponding data entry.

[0656] The server then filters the retrieved data entries for confidential and copyrighted information. This filtering process involves deleting specific fields. For example, the "personal_info" and "copyrighted_content" fields might be removed, leaving only publicly available information.

[0657] The filtered data is provided to the user. Users can receive the data via their smartphone or smart glasses. If data corresponding to a data identifier is not found, the server will notify the user.

[0658] The hardware used includes smartphones (iOS and Android devices) and smart glasses (such as Google Glass). The software used is Flask, a Python web framework, for data processing and filtering.

[0659] Software and hardware usage examples

[0660] 1. Database Setup: Data is stored in a JSON database on the server.

[0661] 2. Processing User Requests: Users enter a data identifier using a smartphone app or smart glasses and send a request to the server.

[0662] 3. Data Retrieval and Filtering: The server retrieves the corresponding data entries from the database and filters out confidential information and copyrighted content.

[0663] 4. Data Provision: Filtered data will be displayed on the user's smartphone or smart glasses. This ensures that users can use the data with peace of mind.

[0664] Specific example

[0665] Example 1:

[0666] The user requests data identifier "data1" using their smartphone. The server retrieves the following data entry from the database.

[0667] json

[0668] {

[0669] "content": "Sample text data",

[0670] "author": "Author A",

[0671] "personal_info": "Sensitive Info",

[0672] "copyrighted_content": "Some copyrighted content"

[0673] }

[0674] The server performs filtering and provides the following data to the user.

[0675] json

[0676] {

[0677] "content": "Sample text data",

[0678] "author": "Author A"

[0679] }

[0680] Example 2:

[0681] A user requests data identifier "data3" using smart glasses. The server searches the database but cannot find the matching data. The server notifies the user of this.

[0682] Example of a prompt:

[0683] "We have specified 'data1' as the identifier for the training data. Please provide the data for the entry corresponding to this data identifier, with all confidential and copyrighted information removed."

[0684] In this way, this invention provides an environment in which users can use data with peace of mind, and realizes a system that achieves both data transparency and protection.

[0685] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0686] Step 1:

[0687] The user enters a specific data identifier using a smartphone or smart glasses. This input is then sent to the server via the application.

[0688] Input: Data identifier (e.g., "data1")

[0689] Specific action: The user enters a data identifier into the application's input field and taps the submit button.

[0690] Step 2:

[0691] The server receives a data identifier provided by the user. Based on the received data identifier, it searches the database and retrieves the corresponding data entry.

[0692] Input: Data identifier submitted by the user

[0693] Data processing: The server searches the database and retrieves the corresponding data entries.

[0694] Output: Data entry (Example: {

[0695] "content": "Sample text data",

[0696] "author": "Author A",

[0697] "personal_info": "Sensitive Info",

[0698] "copyrighted_content": "Some copyrighted content"

[0699] })

[0700] Specific operation: The server executes a database query and loads the corresponding data entries into memory.

[0701] Step 3:

[0702] The server filters out confidential and copyrighted content from the retrieved data entries. Specifically, it removes specified fields (e.g., "personal_info" and "copyrighted_content").

[0703] Input: Retrieved data entries

[0704] Data processing: Filter the data to remove the specified fields.

[0705] Output: Filtered data (Example: {

[0706] "content": "Sample text data",

[0707] "author": "Author A"

[0708] })

[0709] Specific operation: The server parses the JSON structure of the data entry and removes unnecessary fields.

[0710] Step 4:

[0711] The server provides the filtered data to the user. The user can view the filtered data through the application.

[0712] Input: Filtered data

[0713] Output: Data displayed on the user's application screen.

[0714] Specific operation: The server generates filtered data in JSON format and sends it to the user's device. The user's device displays the received data on the screen.

[0715] Step 5:

[0716] If the data corresponding to the data identifier is not found in the database, the server will notify the user accordingly.

[0717] Input: Data identifier provided by the user

[0718] Output: Notification message when data is not found (e.g., "Data not found")

[0719] Specific operation: If the server does not find the data as a result of the database search, it generates an appropriate notification message and sends it to the user's device. The user's device displays the notification message on the screen.

[0720] These steps enable the system to filter and provide data efficiently and securely.

[0721] 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.

[0722] To implement this invention, it is necessary to construct a system that recognizes the user's emotions and dynamically adjusts data filtering based on those emotions. The details of this system's processing are described below.

[0723] System Configuration

[0724] Database settings:

[0725] The server sets up a database to store the training data. This database contains many data entries, each identified by a unique data identifier. For example, data ID "data1" contains the following information:

[0726] {

[0727] "content": "Sample text data",

[0728] "author": "Author A",

[0729] "personal_info": "Sensitive Info",

[0730] "copyrighted_content": "Some copyrighted content"

[0731] }

[0732] Emotion engine settings:

[0733] The server has an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's text and voice input to identify the user's emotions.

[0734] Processing user requests

[0735] User request:

[0736] The user sends a specific data identifier (for example, data ID "data1") to the server. Simultaneously, the emotion engine recognizes emotions from the user's input. Upon receiving a request, the server searches its database and retrieves the corresponding data.

[0737] Data acquisition and filtering

[0738] Data acquisition:

[0739] The server searches the database for the corresponding data entry based on the data identifier provided by the user. When the data entry is found, the server retrieves its details.

[0740] Adjusting emotion-based filtering:

[0741] The server adjusts the strictness of its filtering process based on the user's emotions recognized by the emotion engine. For example, if a user expresses emotions such as "anxiety" or "worry," the server will more strictly filter out confidential and copyrighted content. On the other hand, if a user expresses emotions such as "reassurance" or "trust," the filtering strictness will be reduced.

[0742] Filtering process:

[0743] The server identifies and filters out confidential information (e.g., the "personal_info" field) and copyrighted content (e.g., the "copyrighted_content" field). The filtered data is then made publicly available.

[0744] Providing data to users

[0745] Data provided after filtering:

[0746] The filtered data is provided to the user. After adjustments are made according to the user's sentiment, for example, in the case of data ID "data1", the filtered data changes as follows:

[0747] {

[0748] "content": "Sample text data",

[0749] "author": "Author A"

[0750] }

[0751] Handling when data is not found

[0752] Notification if data is not found:

[0753] If the database does not contain data corresponding to the data identifier provided by the user, the server will notify the user. This notification allows the user to immediately recognize that the relevant data does not exist.

[0754] Specific example

[0755] Specific example 1:

[0756] The user requests data ID "data1" and indicates the emotion "anxiety". The server searches the database and retrieves the following information.

[0757] {

[0758] "content": "Sample text data",

[0759] "author": "Author A",

[0760] "personal_info": "Sensitive Info",

[0761] "copyrighted_content": "Some copyrighted content"

[0762] }

[0763] The server performs filtering to more strictly remove confidential information and copyrighted content. The filtered data will look like this:

[0764] {

[0765] "content": "Sample text data",

[0766] "author": "Author A"

[0767] }

[0768] The server then provides the filtered data to the user, ensuring they can use it with confidence.

[0769] Specific example 2:

[0770] The user requests data ID "data2" and expresses the emotion of "peace of mind." The server searches the database and retrieves the following information.

[0771] {

[0772] "content": "Another sample text",

[0773] "author": "Author B"

[0774] }

[0775] In this case, filtering is performed as usual because the data does not contain confidential information or copyrighted material. The server provides this data directly to the user.

[0776] In this way, the invention provides a system that achieves both transparency and security by recognizing the user's emotions and dynamically adjusting data filtering based on those emotions.

[0777] The following describes the processing flow.

[0778] Step 1:

[0779] The user specifies a data identifier (e.g., data ID "data1") from their device and sends a request to the server for data details. Simultaneously, the emotion engine analyzes the user's emotions through user input (text or voice).

[0780] Step 2:

[0781] The server extracts a data identifier from the received request and searches the database based on that identifier.

[0782] Step 3:

[0783] The server finds a matching data identifier in the database and retrieves the corresponding data entry. For example, it retrieves the data corresponding to data ID "data1".

[0784] Step 4:

[0785] The emotion engine recognizes emotions from user input. For example, it identifies emotions such as "anxiety," "relief," and "worry."

[0786] Step 5:

[0787] The server adjusts the strictness of the filtering process based on the user's emotions recognized by the emotion engine. For example, if the user indicates "anxiety," the filtering process will be made stricter.

[0788] Step 6:

[0789] The server identifies and filters out sensitive information (e.g., "personal_info") and copyrighted content (e.g., "copyrighted_content") from the retrieved data entries.

[0790] Step 7:

[0791] After the filtering process is performed, the server generates data from which confidential information and copyrighted content have been removed. For example, in the case of data ID "data1", the filtered data will look like this:

[0792] {

[0793] "content": "Sample text data",

[0794] "author": "Author A"

[0795] }

[0796] Step 8:

[0797] The server returns the filtered data to the user. The user receives and uses this data on their device.

[0798] Step 9:

[0799] If a data entry corresponding to a data identifier does not exist in the database, the server will notify the user that "the data does not exist." The user will then receive this notification and take appropriate action, such as specifying a new data identifier.

[0800] (Example 2)

[0801] 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".

[0802] Traditional data filtering systems rely on simple rule-based filtering, uniformly removing confidential and copyrighted information without considering user emotions or circumstances. This lack of flexibility in responding to user needs is a major challenge. In particular, providing appropriate information in situations where emotionally and contextually relevant data is required can be difficult, leading to decreased user satisfaction.

[0803] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for filtering confidential information and copyrighted content from the retrieved data, means for recognizing the user's emotions and dynamically adjusting the strictness of the filtering based on those emotions, and means for providing the filtered data to the user. This enables flexible data provision in response to the user's emotions, thereby improving user satisfaction.

[0804] A "user" is an individual or organization that uses the system to search for and retrieve data.

[0805] A "data identifier" is an identifier used to uniquely identify a specific data entry within a database.

[0806] A "database" is a storage system for storing and managing multiple data entries.

[0807] "Confidential information" refers to sensitive information that should not be made public and should be protected.

[0808] "Copyright-protected content" refers to works or content that should be protected under copyright law.

[0809] "Filtering" is the process of removing unnecessary or inappropriate parts from data based on specific conditions.

[0810] "Emotion" refers to the psychological and emotional state that a user exhibits towards the system.

[0811] An "emotion engine" is software or hardware that analyzes user input (text or voice) and identifies their emotions.

[0812] "Dynamic adjustment" means changing the strictness or parameters of a process in real time or as needed, depending on the conditions and circumstances.

[0813] "Searching" means retrieving data within a database based on specified conditions.

[0814] This invention relates to a system that recognizes user emotions and filters data based on those emotions. A detailed embodiment of the system is described below.

[0815] Database settings

[0816] The server configures a database that stores multiple data entries. Each entry in the database is identified by a unique data identifier and contains information such as the following:

[0817] {

[0818] "dataID": "data1",

[0819] "content": "Sample text data",

[0820] "author": "Author A",

[0821] "personal_info": "Sensitive Info",

[0822] "copyrighted_content": "Some copyrighted content"

[0823] }

[0824] Emotion Engine Settings

[0825] The server sets up an emotion engine to recognize the user's emotions. The emotion engine uses NLP (Natural Language Processing) libraries and speech recognition software (e.g., Google Cloud Speech-to-Text, IBM Watson Natural Language Understanding).

[0826] Receiving user requests

[0827] The user sends a specific data identifier (e.g., data ID "data1") from their device to the server. Simultaneously, the emotion engine analyzes the user's input (text or voice) to identify the user's emotion. When the request reaches the server, the server searches its database and retrieves the corresponding data entry.

[0828] Data acquisition and filtering

[0829] The server searches the database for the corresponding data entry based on the data identifier and retrieves detailed information. It then filters the retrieved data for confidential and copyrighted content. This filtering is dynamically adjusted based on the user's emotions as perceived by the emotion engine.

[0830] Filtering process

[0831] The filtering process identifies and removes confidential information (e.g., the "personal_info" field) and copyrighted content (e.g., the "copyrighted_content" field).

[0832] Providing data to users

[0833] The filtered data is provided to the user through their device. This allows the user to use the filtered data with peace of mind.

[0834] Specific example

[0835] Specific example 1:

[0836] The user requests data ID "data1" and indicates the emotion "anxiety". The server searches the database and retrieves the following information.

[0837] {

[0838] "content": "Sample text data",

[0839] "author": "Author A",

[0840] "personal_info": "Sensitive Info",

[0841] "copyrighted_content": "Some copyrighted content"

[0842] }

[0843] The server performs filtering to strictly remove confidential information and copyrighted content. The filtered data will look like this:

[0844] {

[0845] "content": "Sample text data",

[0846] "author": "Author A"

[0847] }

[0848] Specific example 2:

[0849] The user requests data ID "data2" and expresses the emotion of "peace of mind." The server searches the database and retrieves the following information.

[0850] {

[0851] "content": "Another sample text",

[0852] "author": "Author B"

[0853] }

[0854] In this case, filtering is not necessary, and the server provides this data directly to the user.

[0855] Example of a prompt

[0856] 1. Prompt message when the user is experiencing feelings of "anxiety":

[0857] "Emotion: Anxiety. Data ID: data1. Please strictly remove confidential information and copyrighted content from the retrieved data."

[0858] 2. Prompt message to use when the user feels "reassured":

[0859] "Emotion: Relief. Data ID: data2. Please provide this data directly."

[0860] This system enables flexible data filtering and delivery tailored to the user's emotions.

[0861] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0862] Step 1:

[0863] Database settings:

[0864] The server configures a database to store training data. It receives JSON data containing data entries as input. These data entries are identified by unique data identifiers, each with fields such as "content," "author," "personal_info," and "copyrighted_content." The server saves these data entries to the database. The configured database is generated as output.

[0865] Step 2:

[0866] Preparing the emotional engine:

[0867] The server sets up an emotion engine to recognize the user's emotions. As input, the server receives configuration files and API keys for NLP (Natural Language Processing) libraries and speech recognition software (e.g., Google Cloud Speech-to-Text, IBM Watson Natural Language Understanding). The server installs this software and applies its configuration. As output, the emotion engine becomes available for use.

[0868] Step 3:

[0869] Receiving user requests:

[0870] The user sends a specific data identifier (e.g., data ID "data1") to the server via their device. The server receives the user's request data and text or audio data for emotion recognition as input. The server parses these inputs and sends them, along with the data identifier, to the emotion engine. The output is the recognition of the user's emotion, ready for processing based on that emotion.

[0871] Step 4:

[0872] Searching and retrieving data:

[0873] The server searches the database based on the data identifier received from the user. It receives the data identifier as input and generates a database search query. The server searches for the corresponding data entry in the database and retrieves detailed information. The data entry is retrieved as output.

[0874] Step 5:

[0875] Adjusting emotion-based filtering:

[0876] The server dynamically adjusts the filtering strictness based on the user's emotions recognized by the emotion engine. It receives user emotion data and retrieved data entries as input. The server analyzes the emotion data and, for example, sets stricter filtering criteria if the user indicates emotions such as "anxiety" or "worry." The output is the adjusted filtering settings.

[0877] Step 6:

[0878] Data filtering process:

[0879] The server removes sensitive and copyrighted content from data entries based on the specified filtering settings. It receives filtering settings and data entries as input. The server filters fields such as "personal_info" and "copyrighted_content" to remove unwanted information. The filtered data is then generated as output.

[0880] Step 7:

[0881] Providing filtered data:

[0882] The server sends filtered data to the user. It receives filtered data as input and sends it to the user's terminal. As output, the user can receive the filtered data through their terminal.

[0883] Step 8:

[0884] Notification if data is not found:

[0885] The server notifies the user if data corresponding to the specified data identifier does not exist in the database. The input confirms that the search results are empty. The server generates an error message stating "no matching data found" and sends it to the user's terminal. The output informs the user that the specified data does not exist.

[0886] (Application Example 2)

[0887] 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."

[0888] Traditional systems lacked dynamic data filtering based on individual user emotional states, instead applying uniform filtering rules to all users. This meant they couldn't consider the anxiety or reassurance specific users felt regarding the data. As a result, providing flexible data tailored to user emotions was difficult, hindering improvements in the user experience.

[0889] 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.

[0890] In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for analyzing the user's emotions using an emotion engine that recognizes the user's emotions, means for dynamically adjusting and filtering confidential information and copyrighted content from the retrieved data based on the user's emotions, and means for providing the filtered data to the user. This allows for dynamic adjustment of the filtering strictness according to the user's emotions, enabling flexible data provision based on the emotions of individual users.

[0891] "User" refers to an individual or group that uses the system.

[0892] A "data identifier" is information that uniquely identifies a specific data entry within a database.

[0893] A "database" is a system or device for systematically storing and managing data.

[0894] An "emotion engine" is software or hardware that analyzes and identifies emotions from user input such as facial expressions and voice.

[0895] "Emotions" refer to the user's psychological state, including states such as "reassurance" and "anxiety."

[0896] "Confidential information" refers to personal information or important information that should not be made public.

[0897] "Copyright-protected content" refers to creative content and materials that should be protected under copyright law.

[0898] "Dynamic adjustment" means changing settings and behavior in real time according to conditions and circumstances.

[0899] "Filtering" is the process of selecting or deleting data based on specific conditions.

[0900] A "data entry" is a single unit of data stored within a database.

[0901] "To analyze" means to examine data in detail and clarify its structure and meaning.

[0902] "To provide" means to deliver data or services to a user or make them available for use.

[0903] In order to implement this invention, it is necessary to build a system that recognizes the user's emotions and dynamically adjusts data filtering based on those emotions.

[0904] System Configuration

[0905] Database settings:

[0906] The server sets up a database to store the training data. This database contains many data entries, each identified by a unique data identifier.

[0907] Emotion engine settings:

[0908] The server uses an emotion engine to recognize the user's emotions. This emotion engine analyzes the user's text, voice, or image input to identify their emotions. Specifically, it utilizes TensorFlow and OpenCV to recognize emotions in real time.

[0909] Processing user requests

[0910] User request:

[0911] The user sends a specific data identifier to the server. Simultaneously, the sentiment engine analyzes the user's emotions. Upon receiving a request, the server searches its database and retrieves the corresponding data.

[0912] Data acquisition and filtering

[0913] Data acquisition:

[0914] The server searches the database for the corresponding data entry based on the data identifier provided by the user and retrieves its details.

[0915] Adjusting emotion-based filtering:

[0916] The server adjusts the strictness of filtering based on the user's emotions recognized by the emotion engine. For example, if the user indicates "anxiety" or "worry," the server strictly filters out confidential and copyrighted content. On the other hand, if the user indicates "reassurance" or "trust," the filtering strictness is relaxed.

[0917] Filtering process:

[0918] The server identifies and filters out confidential and copyrighted information. After filtering, the data is converted into a format that can be publicly released.

[0919] Providing data to users

[0920] Data provided after filtering:

[0921] The filtered data is provided to the user. For example, if the data ID is "data1", the filtered data will change as follows:

[0922] json

[0923] {

[0924] "content": "Sample text data",

[0925] "author": "Author A"

[0926] }

[0927] Specific example

[0928] Specific example 1:

[0929] The user requests data ID "data1" and indicates an emotion of "anxiety." The server searches the database and retrieves the following information:

[0930] json

[0931] {

[0932] "content": "Sample text data",

[0933] "author": "Author A",

[0934] "personal_info": "Sensitive Info",

[0935] "copyrighted_content": "Some copyrighted content"

[0936] }

[0937] The server performs filtering to completely remove confidential and copyrighted information. The filtered data will look like this:

[0938] json

[0939] {

[0940] "content": "Sample text data",

[0941] "author": "Author A"

[0942] }

[0943] Specific example 2:

[0944] When a user requests data ID "data2" and expresses the emotion of "peace of mind," the server searches the database and retrieves the following information:

[0945] json

[0946] {

[0947] "content": "Another sample text",

[0948] "author": "Author B"

[0949] }

[0950] Since this data does not contain any confidential information or copyrighted material, it will be processed as usual and provided to the user as is.

[0951] The data provided to users can be filtered based on emotions, allowing for a balance between transparency and security of information for the user.

[0952] Example of a prompt:

[0953] "Please provide information based on data ID 'data1'. Analyze and filter the sentiment of this image."

[0954] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0955] Step 1:

[0956] The user sends a data identifier and image data from their device to the server. The input includes the data identifier and image data used for emotion recognition. The output is the server receiving the data identifier and image data.

[0957] Step 2:

[0958] The server searches the database based on the received data identifier. The input is the data identifier provided by the user, and the output is the retrieved data entry. For example, if "data1" exists in the database, its details are retrieved.

[0959] Step 3:

[0960] The server uses the received image data to activate the emotion engine and analyze the user's emotions. The input is image data, and the output is the user's emotions identified by the emotion engine. Specifically, the server uses TensorFlow and OpenCV to perform image processing and classify emotions.

[0961] Step 4:

[0962] The server dynamically adjusts the strictness of data filtering based on the analyzed emotions. The input is the user's emotions and the searched data entries, while the output is the filtered data. For example, if the emotion "anxiety" is detected, confidential information and copyrighted content will be strictly filtered.

[0963] Step 5:

[0964] The server performs data filtering. The input is the original data entries retrieved from the database along with the adjusted filtering conditions, and the output is the filtered data. Specifically, the server deletes or masks specified fields from the data entries.

[0965] Step 6:

[0966] The server provides the filtered data to the user. The input is the filtered data, and the output is the data sent back to the user's terminal. Specifically, the server creates an HTTP response that includes the filtered data.

[0967] Step 7:

[0968] The server notifies the user if a corresponding data entry does not exist in the database. The input is the database search result, and the output is a notification message stating "data not found." Specifically, the server creates an HTTP response containing an appropriate error message.

[0969] 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.

[0970] 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.

[0971] 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.

[0972] [Third Embodiment]

[0973] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0974] 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.

[0975] 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).

[0976] 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.

[0977] 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.

[0978] 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).

[0979] 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.

[0980] 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.

[0981] 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.

[0982] 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.

[0983] 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.

[0984] 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".

[0985] To implement this invention, first, the user provides a specific data identifier and sends a request to the server. The details of the system's processing are described below.

[0986] System Configuration

[0987] Database settings:

[0988] The server sets up a database to store the training data. This database contains many data entries, each identified by a unique data identifier. For example, data ID "data1" contains the following information:

[0989] {

[0990] "content": "Sample text data",

[0991] "author": "Author A",

[0992] "personal_info": "Sensitive Info",

[0993] "copyrighted_content": "Some copyrighted content"

[0994] }

[0995] Processing user requests

[0996] User request:

[0997] The user sends a specific data identifier (for example, data ID "data1") to the server. Upon receiving the request, the server searches the database and retrieves the corresponding data.

[0998] Data acquisition and filtering

[0999] Data acquisition:

[1000] The server searches the database for the corresponding data entry based on the data identifier provided by the user. When the data entry is found, the server retrieves its details.

[1001] Filtering of confidential and copyrighted content:

[1002] The retrieved data entries may contain confidential information (e.g., "personal_info") or copyrighted content (e.g., "copyrighted_content"). To filter out this information, the server removes specific fields. The filtered data is then made publicly available.

[1003] Providing data to users

[1004] Data provided after filtering:

[1005] The filtered data is provided to the user. For example, if the data ID is "data1", the filtered data will look like this:

[1006] {

[1007] "content": "Sample text data",

[1008] "author": "Author A"

[1009] }

[1010] This will allow users to safely access data from which confidential and copyrighted information has been removed.

[1011] Handling when data is not found

[1012] Notification if data is not found:

[1013] If the database does not contain data corresponding to the data identifier provided by the user, the server will notify the user. This notification allows the user to immediately recognize that the relevant data does not exist.

[1014] Specific example

[1015] Specific example 1:

[1016] The user requests data ID "data1". The server searches the database and retrieves the following information.

[1017] {

[1018] "content": "Sample text data",

[1019] "author": "Author A",

[1020] "personal_info": "Sensitive Info",

[1021] "copyrighted_content": "Some copyrighted content"

[1022] }

[1023] The server performs filtering to remove confidential and copyrighted information. The filtered data will look like this:

[1024] {

[1025] "content": "Sample text data",

[1026] "author": "Author A"

[1027] }

[1028] The server then provides the filtered data to the user.

[1029] Specific example 2:

[1030] The user requests data with the non-existent data ID "data3". The server searches the database but cannot find the matching data, and therefore notifies the user.

[1031] In this way, this invention enables users to confidently utilize AI model training data, achieving both data transparency and protection.

[1032] The following describes the processing flow.

[1033] Step 1:

[1034] The user specifies a particular data identifier (e.g., data ID "data1") from their device and sends a request to the server to request data details.

[1035] Step 2:

[1036] The server extracts a data identifier from the received request and searches the database based on that identifier.

[1037] Step 3:

[1038] The server searches the database for a matching data identifier and retrieves the corresponding data entry. For example, it retrieves the data corresponding to data ID "data1".

[1039] Step 4:

[1040] The server identifies and filters out sensitive information (e.g., the "personal_info" field) and copyrighted content (e.g., the "copyrighted_content" field) from the retrieved data entries.

[1041] Step 5:

[1042] After the filtering process, the server generates data from which confidential and copyrighted information has been removed. Specifically, it creates a new data object with unnecessary fields deleted.

[1043] Step 6:

[1044] The server returns the filtered data to the user. This data does not contain confidential information or copyrighted material, so it can be used with confidence.

[1045] Step 7:

[1046] If a data entry corresponding to a data identifier does not exist in the database, the server will notify the user that "the data does not exist."

[1047] Step 8:

[1048] Users can receive and use data sent from the server. If the data does not exist, they can take action such as specifying a different data identifier.

[1049] (Example 1)

[1050] 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."

[1051] The problem that this invention aims to solve is to achieve both data transparency and protection simultaneously by securely filtering out data containing confidential information and copyrighted content when searching for data in a database based on a data identifier provided by the user, and then providing that data to the user. Another objective is to improve the user experience by immediately notifying the user if the relevant data does not exist.

[1052] 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.

[1053] In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for filtering confidential information and copyrighted content from the searched data, means for providing the filtered data to the user, and means for notifying the user if no matching data exists in the database. As a result, the user can use the data from which confidential information and copyrighted content have been removed with peace of mind, and can also immediately recognize if the data does not exist.

[1054] A "user" is an individual, legal entity, or other entity that uses the system to provide a data identifier and seek to retrieve information.

[1055] A "data identifier" is a string or number used to uniquely identify a specific data entry within a database.

[1056] A "server" is a computer system responsible for managing a database, retrieving data, filtering data, and providing data to users.

[1057] A "database" is an information system that stores multiple data entries and allows them to be searched and managed in response to queries.

[1058] "Confidential information" refers to sensitive information such as personal information and trade secrets that should not be made public.

[1059] "Copyright-protected content" refers to creations and content protected by copyright law.

[1060] "Filtering" is the process of removing unnecessary information from data based on specific criteria.

[1061] "Searching" is the process of finding data entries within a database based on a specific data identifier.

[1062] "Notification" is the act of conveying specific information to a user, and it is performed by a system.

[1063] "Providing" refers to the act of the server sending filtered data back to the user.

[1064] To implement this invention, a user, a server, and a database are used. A detailed embodiment of this system is described below.

[1065] First, the user uses a device (e.g., computer, smartphone, tablet) to enter a specific data identifier. This data identifier is a string or number used to identify a unique data entry in the database. The data identifier entered by the user via a web browser or dedicated application is sent to the server over the internet. An example of a prompt message is, "Please search the database using data ID 'data1'."

[1066] When the server receives a request, it searches the database based on the data identifier. Database management systems used by the server include, for example, MySQL and PostgreSQL. The server executes an SQL query to find the data entry corresponding to the specified data identifier. If no matching data entry is found, the server notifies the user accordingly.

[1067] The server loads data entries retrieved from the database into memory and then filters them for confidential and copyrighted information. The filtering process removes specific fields such as "personal_info" and "copyrighted_content" from the retrieved data entries. This data analysis and removal is performed using programming languages ​​such as Python or Java.

[1068] The filtered data does not contain confidential or copyrighted information, so it can be safely provided to users. The server returns the filtered data as an HTTP response and displays it on the user's device. This allows users to access safe and transparent data.

[1069] Specific example 1:

[1070] The user requests data ID "data1". This data identifier is sent to the database via the server. The server retrieves the data, filters it, and finally provides the filtered data to the user. The data will be in the following format.

[1071] {

[1072] "content": "Sample text data",

[1073] "author": "Author A"

[1074] }

[1075] An example of a prompt message is, "Please search for data ID 'data1' and provide the filtered data."

[1076] Specific example 2:

[1077] A user requests data with the non-existent data ID "data3". The server searches the database but cannot find the corresponding data entry, so it notifies the user with the message "The specified data could not be found."

[1078] This system allows users to access securely filtered data based on provided data identifiers, while also promptly notifying them if data is unavailable. This embodiment of the invention makes it possible to achieve both data transparency and protection.

[1079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1080] Step 1:

[1081] User enters and submits data identifier

[1082] The user uses their device to enter a specific data identifier (e.g., data ID "data1") and sends a request to the server. The data identifier entered at this time becomes the input data. The interface used by the user is often a web browser or a dedicated application. Specifically, the user enters "data1" into the input form of the web browser and clicks the "Submit" button. As output, a request containing the data identifier is sent to the server.

[1083] Step 2:

[1084] The server receives the request.

[1085] The server receives a request from the user. The input here is an HTTP request containing a data identifier sent by the user. The server parses this request and extracts the data identifier. Specifically, the server receives a GET or POST request and parses the data identifier "data1" within the request. The output is the data identifier to be searched for.

[1086] Step 3:

[1087] The server searches the database.

[1088] The server searches the database based on a data identifier. The input is the extracted data identifier "data1". The server executes an SQL query to find the corresponding data entry in the database. Specifically, the server executes a query like "SELECT FROM dataset WHERE data_id='data1'". The output is the data entry retrieved from the database.

[1089] Step 4:

[1090] The server retrieves the data.

[1091] The server retrieves the relevant data entries from the database and loads them into memory. The input here is the data entries retrieved from the database. Specifically, the database management system (e.g., MySQL, PostgreSQL) returns the search results. The output is the retrieved data entries, and for example, it takes the following format:

[1092] json

[1093] {

[1094] "content": "Sample text data",

[1095] "author": "Author A",

[1096] "personal_info": "Sensitive Info",

[1097] "copyrighted_content": "Some copyrighted content"

[1098] }

[1099] Step 5:

[1100] The server filters out confidential and copyrighted content.

[1101] The server filters out confidential and copyrighted content from the retrieved data entries. The input is the original retrieved data entry. Specifically, the server parses the JSON data and removes the specific fields "personal_info" and "copyrighted_content". The output is the filtered data entry, which has the following format as an example.

[1102] json

[1103] {

[1104] "content": "Sample text data",

[1105] "author": "Author A"

[1106] }

[1107] Step 6:

[1108] The server provides the filtered data to the user.

[1109] The server returns filtered data to the user. The input is the filtered data entry. Specifically, the server returns the filtered data as an HTTP response and displays it on the user's terminal. The output is the filtered data that the user can see on their terminal.

[1110] Step 7:

[1111] The server will notify if data cannot be found.

[1112] If no data corresponding to the specified data identifier exists in the database, the server will notify the user. The input is the case where the database search results are found to be empty. Specifically, the server will return an HTTP response with a message such as "The specified data was not found." The output is the error message displayed to the user.

[1113] (Application Example 1)

[1114] 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."

[1115] When using data in a database, it is crucial to ensure the security and transparency of data, including confidential information and copyrighted material. However, many current systems have insufficient filtering capabilities, resulting in an environment where users cannot use data with confidence. Furthermore, there is a lack of established methods for providing filtered data to users quickly and appropriately. Additionally, there is a lack of proper notification mechanisms when data cannot be found. These problems need to be addressed to provide users with a reliable data delivery service.

[1116] 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.

[1117] In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for filtering confidential information and copyrighted content from the searched data, means for providing the filtered data to the user, and means for notifying the user if the data is not found. This allows the user to quickly and securely obtain data from which confidential information and copyrighted content have been removed, as well as receive appropriate notification if the data does not exist.

[1118] A "user" is a person or entity that uses a system to request data.

[1119] A "data identifier" is a piece of identification information used to uniquely identify a specific data entry within a database.

[1120] A "database" is a system that stores a large number of data entries and manages them using specific identifiers.

[1121] "Confidential information" refers to information that is not disclosed to anyone other than specific users in order to prevent unauthorized use.

[1122] "Copyright-protected content" refers to content that is protected by copyright law and cannot be used without permission.

[1123] "Filtering" is the process of removing specific information from data.

[1124] "Means of providing" refers to means of displaying or transmitting acquired data to the user.

[1125] "Means of notification" refers to a means of informing the user if data cannot be found.

[1126] A "smartphone" is a type of mobile phone, an electronic device capable of running a variety of applications.

[1127] "Smart glasses" are glasses-type wearable devices that have the function of displaying visual information.

[1128] This invention is a system that searches a database for data based on a data identifier provided by the user, filters the data, and provides it to the user. Specifically, it is implemented via a smartphone application or smart glasses.

[1129] The server has a means of searching for data entries in the database. When a user submits a data identifier, the server searches the database based on that identifier and retrieves the corresponding data entry.

[1130] The server then filters the retrieved data entries for confidential and copyrighted information. This filtering process involves deleting specific fields. For example, the "personal_info" and "copyrighted_content" fields might be removed, leaving only publicly available information.

[1131] The filtered data is provided to the user. Users can receive the data via their smartphone or smart glasses. If data corresponding to a data identifier is not found, the server will notify the user.

[1132] The hardware used includes smartphones (iOS and Android devices) and smart glasses (such as Google Glass). The software used is Flask, a Python web framework, for data processing and filtering.

[1133] Software and hardware usage examples

[1134] 1. Database Setup: Data is stored in a JSON database on the server.

[1135] 2. Processing User Requests: Users enter a data identifier using a smartphone app or smart glasses and send a request to the server.

[1136] 3. Data Retrieval and Filtering: The server retrieves the corresponding data entries from the database and filters out confidential information and copyrighted content.

[1137] 4. Data Provision: Filtered data will be displayed on the user's smartphone or smart glasses. This ensures that users can use the data with peace of mind.

[1138] Specific example

[1139] Example 1:

[1140] The user requests data identifier "data1" using their smartphone. The server retrieves the following data entry from the database.

[1141] json

[1142] {

[1143] "content": "Sample text data",

[1144] "author": "Author A",

[1145] "personal_info": "Sensitive Info",

[1146] "copyrighted_content": "Some copyrighted content"

[1147] }

[1148] The server performs filtering and provides the following data to the user.

[1149] json

[1150] {

[1151] "content": "Sample text data",

[1152] "author": "Author A"

[1153] }

[1154] Example 2:

[1155] A user requests data identifier "data3" using smart glasses. The server searches the database but cannot find the matching data. The server notifies the user of this.

[1156] Example of a prompt:

[1157] "We have specified 'data1' as the identifier for the training data. Please provide the data for the entry corresponding to this data identifier, with all confidential and copyrighted information removed."

[1158] In this way, this invention provides an environment in which users can use data with peace of mind, and realizes a system that achieves both data transparency and protection.

[1159] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1160] Step 1:

[1161] The user enters a specific data identifier using a smartphone or smart glasses. This input is then sent to the server via the application.

[1162] Input: Data identifier (e.g., "data1")

[1163] Specific action: The user enters a data identifier into the application's input field and taps the submit button.

[1164] Step 2:

[1165] The server receives a data identifier provided by the user. Based on the received data identifier, it searches the database and retrieves the corresponding data entry.

[1166] Input: Data identifier submitted by the user

[1167] Data processing: The server searches the database and retrieves the corresponding data entries.

[1168] Output: Data entry (Example: {

[1169] "content": "Sample text data",

[1170] "author": "Author A",

[1171] "personal_info": "Sensitive Info",

[1172] "copyrighted_content": "Some copyrighted content"

[1173] })

[1174] Specific operation: The server executes a database query and loads the corresponding data entries into memory.

[1175] Step 3:

[1176] The server filters out confidential and copyrighted content from the retrieved data entries. Specifically, it removes specified fields (e.g., "personal_info" and "copyrighted_content").

[1177] Input: Retrieved data entries

[1178] Data processing: Filter the data to remove the specified fields.

[1179] Output: Filtered data (Example: {

[1180] "content": "Sample text data",

[1181] "author": "Author A"

[1182] })

[1183] Specific operation: The server parses the JSON structure of the data entry and removes unnecessary fields.

[1184] Step 4:

[1185] The server provides the filtered data to the user. The user can view the filtered data through the application.

[1186] Input: Filtered data

[1187] Output: Data displayed on the user's application screen.

[1188] Specific operation: The server generates filtered data in JSON format and sends it to the user's device. The user's device displays the received data on the screen.

[1189] Step 5:

[1190] If the data corresponding to the data identifier is not found in the database, the server will notify the user accordingly.

[1191] Input: Data identifier provided by the user

[1192] Output: Notification message when data is not found (e.g., "Data not found")

[1193] Specific operation: If the server does not find the data as a result of the database search, it generates an appropriate notification message and sends it to the user's device. The user's device displays the notification message on the screen.

[1194] These steps enable the system to filter and provide data efficiently and securely.

[1195] 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.

[1196] To implement this invention, it is necessary to construct a system that recognizes the user's emotions and dynamically adjusts data filtering based on those emotions. The details of this system's processing are described below.

[1197] System Configuration

[1198] Database settings:

[1199] The server sets up a database to store the training data. This database contains many data entries, each identified by a unique data identifier. For example, data ID "data1" contains the following information:

[1200] {

[1201] "content": "Sample text data",

[1202] "author": "Author A",

[1203] "personal_info": "Sensitive Info",

[1204] "copyrighted_content": "Some copyrighted content"

[1205] }

[1206] Emotion engine settings:

[1207] The server has an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's text and voice input to identify the user's emotions.

[1208] Processing user requests

[1209] User request:

[1210] The user sends a specific data identifier (for example, data ID "data1") to the server. Simultaneously, the emotion engine recognizes emotions from the user's input. Upon receiving a request, the server searches its database and retrieves the corresponding data.

[1211] Data acquisition and filtering

[1212] Data acquisition:

[1213] The server searches the database for the corresponding data entry based on the data identifier provided by the user. When the data entry is found, the server retrieves its details.

[1214] Adjusting emotion-based filtering:

[1215] The server adjusts the strictness of its filtering process based on the user's emotions recognized by the emotion engine. For example, if a user expresses emotions such as "anxiety" or "worry," the server will more strictly filter out confidential and copyrighted content. On the other hand, if a user expresses emotions such as "reassurance" or "trust," the filtering strictness will be reduced.

[1216] Filtering process:

[1217] The server identifies and filters out confidential information (e.g., the "personal_info" field) and copyrighted content (e.g., the "copyrighted_content" field). The filtered data is then made publicly available.

[1218] Providing data to users

[1219] Data provided after filtering:

[1220] The filtered data is provided to the user. After adjustments are made according to the user's sentiment, for example, in the case of data ID "data1", the filtered data changes as follows:

[1221] {

[1222] "content": "Sample text data",

[1223] "author": "Author A"

[1224] }

[1225] Handling when data is not found

[1226] Notification if data is not found:

[1227] If the database does not contain data corresponding to the data identifier provided by the user, the server will notify the user. This notification allows the user to immediately recognize that the relevant data does not exist.

[1228] Specific example

[1229] Specific example 1:

[1230] The user requests data ID "data1" and indicates the emotion "anxiety". The server searches the database and retrieves the following information.

[1231] {

[1232] "content": "Sample text data",

[1233] "author": "Author A",

[1234] "personal_info": "Sensitive Info",

[1235] "copyrighted_content": "Some copyrighted content"

[1236] }

[1237] The server performs filtering to more strictly remove confidential information and copyrighted content. The filtered data will look like this:

[1238] {

[1239] "content": "Sample text data",

[1240] "author": "Author A"

[1241] }

[1242] The server then provides the filtered data to the user, ensuring they can use it with confidence.

[1243] Specific example 2:

[1244] The user requests data ID "data2" and expresses the emotion of "peace of mind." The server searches the database and retrieves the following information.

[1245] {

[1246] "content": "Another sample text",

[1247] "author": "Author B"

[1248] }

[1249] In this case, filtering is performed as usual because the data does not contain confidential information or copyrighted material. The server provides this data directly to the user.

[1250] In this way, the invention provides a system that achieves both transparency and security by recognizing the user's emotions and dynamically adjusting data filtering based on those emotions.

[1251] The following describes the processing flow.

[1252] Step 1:

[1253] The user specifies a data identifier (e.g., data ID "data1") from their device and sends a request to the server for data details. Simultaneously, the emotion engine analyzes the user's emotions through user input (text or voice).

[1254] Step 2:

[1255] The server extracts a data identifier from the received request and searches the database based on that identifier.

[1256] Step 3:

[1257] The server finds a matching data identifier in the database and retrieves the corresponding data entry. For example, it retrieves the data corresponding to data ID "data1".

[1258] Step 4:

[1259] The emotion engine recognizes emotions from user input. For example, it identifies emotions such as "anxiety," "relief," and "worry."

[1260] Step 5:

[1261] The server adjusts the strictness of the filtering process based on the user's emotions recognized by the emotion engine. For example, if the user indicates "anxiety," the filtering process will be made stricter.

[1262] Step 6:

[1263] The server identifies and filters out sensitive information (e.g., "personal_info") and copyrighted content (e.g., "copyrighted_content") from the retrieved data entries.

[1264] Step 7:

[1265] After the filtering process is performed, the server generates data from which confidential information and copyrighted content have been removed. For example, in the case of data ID "data1", the filtered data will look like this:

[1266] {

[1267] "content": "Sample text data",

[1268] "author": "Author A"

[1269] }

[1270] Step 8:

[1271] The server returns the filtered data to the user. The user receives and uses this data on their device.

[1272] Step 9:

[1273] If a data entry corresponding to a data identifier does not exist in the database, the server will notify the user that "the data does not exist." The user will then receive this notification and take appropriate action, such as specifying a new data identifier.

[1274] (Example 2)

[1275] 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."

[1276] Traditional data filtering systems rely on simple rule-based filtering, uniformly removing confidential and copyrighted information without considering user emotions or circumstances. This lack of flexibility in responding to user needs is a major challenge. In particular, providing appropriate information in situations where emotionally and contextually relevant data is required can be difficult, leading to decreased user satisfaction.

[1277] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for filtering confidential information and copyrighted content from the retrieved data, means for recognizing the user's emotions and dynamically adjusting the strictness of the filtering based on those emotions, and means for providing the filtered data to the user. This enables flexible data provision in response to the user's emotions, thereby improving user satisfaction.

[1278] A "user" is an individual or organization that uses the system to search for and retrieve data.

[1279] A "data identifier" is an identifier used to uniquely identify a specific data entry within a database.

[1280] A "database" is a storage system for storing and managing multiple data entries.

[1281] "Confidential information" refers to sensitive information that should not be made public and should be protected.

[1282] "Copyright-protected content" refers to works or content that should be protected under copyright law.

[1283] "Filtering" is the process of removing unnecessary or inappropriate parts from data based on specific conditions.

[1284] "Emotion" refers to the psychological and emotional state that a user exhibits towards the system.

[1285] An "emotion engine" is software or hardware that analyzes user input (text or voice) and identifies their emotions.

[1286] "Dynamic adjustment" means changing the strictness or parameters of a process in real time or as needed, depending on the conditions and circumstances.

[1287] "Searching" means retrieving data within a database based on specified conditions.

[1288] This invention relates to a system that recognizes user emotions and filters data based on those emotions. A detailed embodiment of the system is described below.

[1289] Database settings

[1290] The server configures a database that stores multiple data entries. Each entry in the database is identified by a unique data identifier and contains information such as the following:

[1291] {

[1292] "dataID": "data1",

[1293] "content": "Sample text data",

[1294] "author": "Author A",

[1295] "personal_info": "Sensitive Info",

[1296] "copyrighted_content": "Some copyrighted content"

[1297] }

[1298] Emotion Engine Settings

[1299] The server sets up an emotion engine to recognize the user's emotions. The emotion engine uses NLP (Natural Language Processing) libraries and speech recognition software (e.g., Google Cloud Speech-to-Text, IBM Watson Natural Language Understanding).

[1300] Receiving user requests

[1301] The user sends a specific data identifier (e.g., data ID "data1") from their device to the server. Simultaneously, the emotion engine analyzes the user's input (text or voice) to identify the user's emotion. When the request reaches the server, the server searches its database and retrieves the corresponding data entry.

[1302] Data acquisition and filtering

[1303] The server searches the database for the corresponding data entry based on the data identifier and retrieves detailed information. It then filters the retrieved data for confidential and copyrighted content. This filtering is dynamically adjusted based on the user's emotions as perceived by the emotion engine.

[1304] Filtering process

[1305] The filtering process identifies and removes confidential information (e.g., the "personal_info" field) and copyrighted content (e.g., the "copyrighted_content" field).

[1306] Providing data to users

[1307] The filtered data is provided to the user through their device. This allows the user to use the filtered data with peace of mind.

[1308] Specific example

[1309] Specific example 1:

[1310] The user requests data ID "data1" and indicates the emotion "anxiety". The server searches the database and retrieves the following information.

[1311] {

[1312] "content": "Sample text data",

[1313] "author": "Author A",

[1314] "personal_info": "Sensitive Info",

[1315] "copyrighted_content": "Some copyrighted content"

[1316] }

[1317] The server performs filtering to strictly remove confidential information and copyrighted content. The filtered data will look like this:

[1318] {

[1319] "content": "Sample text data",

[1320] "author": "Author A"

[1321] }

[1322] Specific example 2:

[1323] The user requests data ID "data2" and expresses the emotion of "peace of mind." The server searches the database and retrieves the following information.

[1324] {

[1325] "content": "Another sample text",

[1326] "author": "Author B"

[1327] }

[1328] In this case, filtering is not necessary, and the server provides this data directly to the user.

[1329] Example of a prompt

[1330] 1. Prompt message when the user is experiencing feelings of "anxiety":

[1331] "Emotion: Anxiety. Data ID: data1. Please strictly remove confidential information and copyrighted content from the retrieved data."

[1332] 2. Prompt message to use when the user feels "reassured":

[1333] "Emotion: Relief. Data ID: data2. Please provide this data directly."

[1334] This system enables flexible data filtering and delivery tailored to the user's emotions.

[1335] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1336] Step 1:

[1337] Database settings:

[1338] The server configures a database to store training data. It receives JSON data containing data entries as input. These data entries are identified by unique data identifiers, each with fields such as "content," "author," "personal_info," and "copyrighted_content." The server saves these data entries to the database. The configured database is generated as output.

[1339] Step 2:

[1340] Preparing the emotional engine:

[1341] The server sets up an emotion engine to recognize the user's emotions. As input, the server receives configuration files and API keys for NLP (Natural Language Processing) libraries and speech recognition software (e.g., Google Cloud Speech-to-Text, IBM Watson Natural Language Understanding). The server installs this software and applies its configuration. As output, the emotion engine becomes available for use.

[1342] Step 3:

[1343] Receiving user requests:

[1344] The user sends a specific data identifier (e.g., data ID "data1") to the server via their device. The server receives the user's request data and text or audio data for emotion recognition as input. The server parses these inputs and sends them, along with the data identifier, to the emotion engine. The output is the recognition of the user's emotion, ready for processing based on that emotion.

[1345] Step 4:

[1346] Searching and retrieving data:

[1347] The server searches the database based on the data identifier received from the user. It receives the data identifier as input and generates a database search query. The server searches for the corresponding data entry in the database and retrieves detailed information. The data entry is retrieved as output.

[1348] Step 5:

[1349] Adjusting emotion-based filtering:

[1350] The server dynamically adjusts the filtering strictness based on the user's emotions recognized by the emotion engine. It receives user emotion data and retrieved data entries as input. The server analyzes the emotion data and, for example, sets stricter filtering criteria if the user indicates emotions such as "anxiety" or "worry." The output is the adjusted filtering settings.

[1351] Step 6:

[1352] Data filtering process:

[1353] The server removes sensitive and copyrighted content from data entries based on the specified filtering settings. It receives filtering settings and data entries as input. The server filters fields such as "personal_info" and "copyrighted_content" to remove unwanted information. The filtered data is then generated as output.

[1354] Step 7:

[1355] Providing filtered data:

[1356] The server sends filtered data to the user. It receives filtered data as input and sends it to the user's terminal. As output, the user can receive the filtered data through their terminal.

[1357] Step 8:

[1358] Notification if data is not found:

[1359] The server notifies the user if data corresponding to the specified data identifier does not exist in the database. The input confirms that the search results are empty. The server generates an error message stating "no matching data found" and sends it to the user's terminal. The output informs the user that the specified data does not exist.

[1360] (Application Example 2)

[1361] 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."

[1362] Traditional systems lacked dynamic data filtering based on individual user emotional states, instead applying uniform filtering rules to all users. This meant they couldn't consider the anxiety or reassurance specific users felt regarding the data. As a result, providing flexible data tailored to user emotions was difficult, hindering improvements in the user experience.

[1363] 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.

[1364] In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for analyzing the user's emotions using an emotion engine that recognizes the user's emotions, means for dynamically adjusting and filtering confidential information and copyrighted content from the retrieved data based on the user's emotions, and means for providing the filtered data to the user. This allows for dynamic adjustment of the filtering strictness according to the user's emotions, enabling flexible data provision based on the emotions of individual users.

[1365] "User" refers to an individual or group that uses the system.

[1366] A "data identifier" is information that uniquely identifies a specific data entry within a database.

[1367] A "database" is a system or device for systematically storing and managing data.

[1368] An "emotion engine" is software or hardware that analyzes and identifies emotions from user input such as facial expressions and voice.

[1369] "Emotions" refer to the user's psychological state, including states such as "reassurance" and "anxiety."

[1370] "Confidential information" refers to personal information or important information that should not be made public.

[1371] "Copyright-protected content" refers to creative content and materials that should be protected under copyright law.

[1372] "Dynamic adjustment" means changing settings and behavior in real time according to conditions and circumstances.

[1373] "Filtering" is the process of selecting or deleting data based on specific conditions.

[1374] A "data entry" is a single unit of data stored within a database.

[1375] "To analyze" means to examine data in detail and clarify its structure and meaning.

[1376] "To provide" means to deliver data or services to a user or make them available for use.

[1377] In order to implement this invention, it is necessary to build a system that recognizes the user's emotions and dynamically adjusts data filtering based on those emotions.

[1378] System Configuration

[1379] Database settings:

[1380] The server sets up a database to store the training data. This database contains many data entries, each identified by a unique data identifier.

[1381] Emotion engine settings:

[1382] The server uses an emotion engine to recognize the user's emotions. This emotion engine analyzes the user's text, voice, or image input to identify their emotions. Specifically, it utilizes TensorFlow and OpenCV to recognize emotions in real time.

[1383] Processing user requests

[1384] User request:

[1385] The user sends a specific data identifier to the server. Simultaneously, the sentiment engine analyzes the user's emotions. Upon receiving a request, the server searches its database and retrieves the corresponding data.

[1386] Data acquisition and filtering

[1387] Data acquisition:

[1388] The server searches the database for the corresponding data entry based on the data identifier provided by the user and retrieves its details.

[1389] Adjusting emotion-based filtering:

[1390] The server adjusts the strictness of filtering based on the user's emotions recognized by the emotion engine. For example, if the user indicates "anxiety" or "worry," the server strictly filters out confidential and copyrighted content. On the other hand, if the user indicates "reassurance" or "trust," the filtering strictness is relaxed.

[1391] Filtering process:

[1392] The server identifies and filters out confidential and copyrighted information. After filtering, the data is converted into a format that can be publicly released.

[1393] Providing data to users

[1394] Data provided after filtering:

[1395] The filtered data is provided to the user. For example, if the data ID is "data1", the filtered data will change as follows:

[1396] json

[1397] {

[1398] "content": "Sample text data",

[1399] "author": "Author A"

[1400] }

[1401] Specific example

[1402] Specific example 1:

[1403] The user requests data ID "data1" and indicates an emotion of "anxiety." The server searches the database and retrieves the following information:

[1404] json

[1405] {

[1406] "content": "Sample text data",

[1407] "author": "Author A",

[1408] "personal_info": "Sensitive Info",

[1409] "copyrighted_content": "Some copyrighted content"

[1410] }

[1411] The server performs filtering to completely remove confidential and copyrighted information. The filtered data will look like this:

[1412] json

[1413] {

[1414] "content": "Sample text data",

[1415] "author": "Author A"

[1416] }

[1417] Specific example 2:

[1418] When a user requests data ID "data2" and expresses the emotion of "peace of mind," the server searches the database and retrieves the following information:

[1419] json

[1420] {

[1421] "content": "Another sample text",

[1422] "author": "Author B"

[1423] }

[1424] Since this data does not contain any confidential information or copyrighted material, it will be processed as usual and provided to the user as is.

[1425] The data provided to users can be filtered based on emotions, allowing for a balance between transparency and security of information for the user.

[1426] Example of a prompt:

[1427] "Please provide information based on data ID 'data1'. Analyze and filter the sentiment of this image."

[1428] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1429] Step 1:

[1430] The user sends a data identifier and image data from their device to the server. The input includes the data identifier and image data used for emotion recognition. The output is the server receiving the data identifier and image data.

[1431] Step 2:

[1432] The server searches the database based on the received data identifier. The input is the data identifier provided by the user, and the output is the retrieved data entry. For example, if "data1" exists in the database, its details are retrieved.

[1433] Step 3:

[1434] The server uses the received image data to activate the emotion engine and analyze the user's emotions. The input is image data, and the output is the user's emotions identified by the emotion engine. Specifically, the server uses TensorFlow and OpenCV to perform image processing and classify emotions.

[1435] Step 4:

[1436] The server dynamically adjusts the strictness of data filtering based on the analyzed emotions. The input is the user's emotions and the searched data entries, while the output is the filtered data. For example, if the emotion "anxiety" is detected, confidential information and copyrighted content will be strictly filtered.

[1437] Step 5:

[1438] The server performs data filtering. The input is the original data entries retrieved from the database along with the adjusted filtering conditions, and the output is the filtered data. Specifically, the server deletes or masks specified fields from the data entries.

[1439] Step 6:

[1440] The server provides the filtered data to the user. The input is the filtered data, and the output is the data sent back to the user's terminal. Specifically, the server creates an HTTP response that includes the filtered data.

[1441] Step 7:

[1442] The server notifies the user if a corresponding data entry does not exist in the database. The input is the database search result, and the output is a notification message stating "data not found." Specifically, the server creates an HTTP response containing an appropriate error message.

[1443] 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.

[1444] 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.

[1445] 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.

[1446] [Fourth Embodiment]

[1447] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1448] 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.

[1449] 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).

[1450] 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.

[1451] 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.

[1452] 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).

[1453] 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.

[1454] 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.

[1455] 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.

[1456] 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.

[1457] 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.

[1458] 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.

[1459] 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".

[1460] To implement this invention, first, the user provides a specific data identifier and sends a request to the server. The details of the system's processing are described below.

[1461] System Configuration

[1462] Database settings:

[1463] The server sets up a database to store the training data. This database contains many data entries, each identified by a unique data identifier. For example, data ID "data1" contains the following information:

[1464] {

[1465] "content": "Sample text data",

[1466] "author": "Author A",

[1467] "personal_info": "Sensitive Info",

[1468] "copyrighted_content": "Some copyrighted content"

[1469] }

[1470] Processing user requests

[1471] User request:

[1472] The user sends a specific data identifier (for example, data ID "data1") to the server. Upon receiving the request, the server searches the database and retrieves the corresponding data.

[1473] Data acquisition and filtering

[1474] Data acquisition:

[1475] The server searches the database for the corresponding data entry based on the data identifier provided by the user. When the data entry is found, the server retrieves its details.

[1476] Filtering of confidential and copyrighted content:

[1477] The retrieved data entries may contain confidential information (e.g., "personal_info") or copyrighted content (e.g., "copyrighted_content"). To filter out this information, the server removes specific fields. The filtered data is then made publicly available.

[1478] Providing data to users

[1479] Data provided after filtering:

[1480] The filtered data is provided to the user. For example, if the data ID is "data1", the filtered data will look like this:

[1481] {

[1482] "content": "Sample text data",

[1483] "author": "Author A"

[1484] }

[1485] This will allow users to safely access data from which confidential and copyrighted information has been removed.

[1486] Handling when data is not found

[1487] Notification if data is not found:

[1488] If the database does not contain data corresponding to the data identifier provided by the user, the server will notify the user. This notification allows the user to immediately recognize that the relevant data does not exist.

[1489] Specific example

[1490] Specific example 1:

[1491] The user requests data ID "data1". The server searches the database and retrieves the following information.

[1492] {

[1493] "content": "Sample text data",

[1494] "author": "Author A",

[1495] "personal_info": "Sensitive Info",

[1496] "copyrighted_content": "Some copyrighted content"

[1497] }

[1498] The server performs filtering to remove confidential and copyrighted information. The filtered data will look like this:

[1499] {

[1500] "content": "Sample text data",

[1501] "author": "Author A"

[1502] }

[1503] The server then provides the filtered data to the user.

[1504] Specific example 2:

[1505] The user requests data with the non-existent data ID "data3". The server searches the database but cannot find the matching data, and therefore notifies the user.

[1506] In this way, this invention enables users to confidently utilize AI model training data, achieving both data transparency and protection.

[1507] The following describes the processing flow.

[1508] Step 1:

[1509] The user specifies a particular data identifier (e.g., data ID "data1") from their device and sends a request to the server to request data details.

[1510] Step 2:

[1511] The server extracts a data identifier from the received request and searches the database based on that identifier.

[1512] Step 3:

[1513] The server searches the database for a matching data identifier and retrieves the corresponding data entry. For example, it retrieves the data corresponding to data ID "data1".

[1514] Step 4:

[1515] The server identifies and filters out sensitive information (e.g., the "personal_info" field) and copyrighted content (e.g., the "copyrighted_content" field) from the retrieved data entries.

[1516] Step 5:

[1517] After the filtering process, the server generates data from which confidential and copyrighted information has been removed. Specifically, it creates a new data object with unnecessary fields deleted.

[1518] Step 6:

[1519] The server returns the filtered data to the user. This data does not contain confidential information or copyrighted material, so it can be used with confidence.

[1520] Step 7:

[1521] If a data entry corresponding to a data identifier does not exist in the database, the server will notify the user that "the data does not exist."

[1522] Step 8:

[1523] Users can receive and use data sent from the server. If the data does not exist, they can take action such as specifying a different data identifier.

[1524] (Example 1)

[1525] 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".

[1526] The problem that this invention aims to solve is to achieve both data transparency and protection simultaneously by securely filtering out data containing confidential information and copyrighted content when searching for data in a database based on a data identifier provided by the user, and then providing that data to the user. Another objective is to improve the user experience by immediately notifying the user if the relevant data does not exist.

[1527] 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.

[1528] In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for filtering confidential information and copyrighted content from the searched data, means for providing the filtered data to the user, and means for notifying the user if no matching data exists in the database. As a result, the user can use the data from which confidential information and copyrighted content have been removed with peace of mind, and can also immediately recognize if the data does not exist.

[1529] A "user" is an individual, legal entity, or other entity that uses the system to provide a data identifier and seek to retrieve information.

[1530] A "data identifier" is a string or number used to uniquely identify a specific data entry within a database.

[1531] A "server" is a computer system responsible for managing a database, retrieving data, filtering data, and providing data to users.

[1532] A "database" is an information system that stores multiple data entries and allows them to be searched and managed in response to queries.

[1533] "Confidential information" refers to sensitive information such as personal information and trade secrets that should not be made public.

[1534] "Copyright-protected content" refers to creations and content protected by copyright law.

[1535] "Filtering" is the process of removing unnecessary information from data based on specific criteria.

[1536] "Searching" is the process of finding data entries within a database based on a specific data identifier.

[1537] "Notification" is the act of conveying specific information to a user, and it is performed by a system.

[1538] "Providing" refers to the act of the server sending filtered data back to the user.

[1539] To implement this invention, a user, a server, and a database are used. A detailed embodiment of this system is described below.

[1540] First, the user uses a device (e.g., computer, smartphone, tablet) to enter a specific data identifier. This data identifier is a string or number used to identify a unique data entry in the database. The data identifier entered by the user via a web browser or dedicated application is sent to the server over the internet. An example of a prompt message is, "Please search the database using data ID 'data1'."

[1541] When the server receives a request, it searches the database based on the data identifier. Database management systems used by the server include, for example, MySQL and PostgreSQL. The server executes an SQL query to find the data entry corresponding to the specified data identifier. If no matching data entry is found, the server notifies the user accordingly.

[1542] The server loads data entries retrieved from the database into memory and then filters them for confidential and copyrighted information. The filtering process removes specific fields such as "personal_info" and "copyrighted_content" from the retrieved data entries. This data analysis and removal is performed using programming languages ​​such as Python or Java.

[1543] The filtered data does not contain confidential or copyrighted information, so it can be safely provided to users. The server returns the filtered data as an HTTP response and displays it on the user's device. This allows users to access safe and transparent data.

[1544] Specific example 1:

[1545] The user requests data ID "data1". This data identifier is sent to the database via the server. The server retrieves the data, filters it, and finally provides the filtered data to the user. The data will be in the following format.

[1546] {

[1547] "content": "Sample text data",

[1548] "author": "Author A"

[1549] }

[1550] An example of a prompt message is, "Please search for data ID 'data1' and provide the filtered data."

[1551] Specific example 2:

[1552] A user requests data with the non-existent data ID "data3". The server searches the database but cannot find the corresponding data entry, so it notifies the user with the message "The specified data could not be found."

[1553] This system allows users to access securely filtered data based on provided data identifiers, while also promptly notifying them if data is unavailable. This embodiment of the invention makes it possible to achieve both data transparency and protection.

[1554] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1555] Step 1:

[1556] User enters and submits data identifier

[1557] The user uses their device to enter a specific data identifier (e.g., data ID "data1") and sends a request to the server. The data identifier entered at this time becomes the input data. The interface used by the user is often a web browser or a dedicated application. Specifically, the user enters "data1" into the input form of the web browser and clicks the "Submit" button. As output, a request containing the data identifier is sent to the server.

[1558] Step 2:

[1559] The server receives the request.

[1560] The server receives a request from the user. The input here is an HTTP request containing a data identifier sent by the user. The server parses this request and extracts the data identifier. Specifically, the server receives a GET or POST request and parses the data identifier "data1" within the request. The output is the data identifier to be searched for.

[1561] Step 3:

[1562] The server searches the database.

[1563] The server searches the database based on a data identifier. The input is the extracted data identifier "data1". The server executes an SQL query to find the corresponding data entry in the database. Specifically, the server executes a query like "SELECT FROM dataset WHERE data_id='data1'". The output is the data entry retrieved from the database.

[1564] Step 4:

[1565] The server retrieves the data.

[1566] The server retrieves the relevant data entries from the database and loads them into memory. The input here is the data entries retrieved from the database. Specifically, the database management system (e.g., MySQL, PostgreSQL) returns the search results. The output is the retrieved data entries, and for example, it takes the following format:

[1567] json

[1568] {

[1569] "content": "Sample text data",

[1570] "author": "Author A",

[1571] "personal_info": "Sensitive Info",

[1572] "copyrighted_content": "Some copyrighted content"

[1573] }

[1574] Step 5:

[1575] The server filters out confidential and copyrighted content.

[1576] The server filters out confidential and copyrighted content from the retrieved data entries. The input is the original retrieved data entry. Specifically, the server parses the JSON data and removes the specific fields "personal_info" and "copyrighted_content". The output is the filtered data entry, which has the following format as an example.

[1577] json

[1578] {

[1579] "content": "Sample text data",

[1580] "author": "Author A"

[1581] }

[1582] Step 6:

[1583] The server provides the filtered data to the user.

[1584] The server returns filtered data to the user. The input is the filtered data entry. Specifically, the server returns the filtered data as an HTTP response and displays it on the user's terminal. The output is the filtered data that the user can see on their terminal.

[1585] Step 7:

[1586] The server will notify if data cannot be found.

[1587] If no data corresponding to the specified data identifier exists in the database, the server will notify the user. The input is the case where the database search results are found to be empty. Specifically, the server will return an HTTP response with a message such as "The specified data was not found." The output is the error message displayed to the user.

[1588] (Application Example 1)

[1589] 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".

[1590] When using data in a database, it is crucial to ensure the security and transparency of data, including confidential information and copyrighted material. However, many current systems have insufficient filtering capabilities, resulting in an environment where users cannot use data with confidence. Furthermore, there is a lack of established methods for providing filtered data to users quickly and appropriately. Additionally, there is a lack of proper notification mechanisms when data cannot be found. These problems need to be addressed to provide users with a reliable data delivery service.

[1591] 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.

[1592] In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for filtering confidential information and copyrighted content from the searched data, means for providing the filtered data to the user, and means for notifying the user if the data is not found. This allows the user to quickly and securely obtain data from which confidential information and copyrighted content have been removed, as well as receive appropriate notification if the data does not exist.

[1593] A "user" is a person or entity that uses a system to request data.

[1594] A "data identifier" is a piece of identification information used to uniquely identify a specific data entry within a database.

[1595] A "database" is a system that stores a large number of data entries and manages them using specific identifiers.

[1596] "Confidential information" refers to information that is not disclosed to anyone other than specific users in order to prevent unauthorized use.

[1597] "Copyright-protected content" refers to content that is protected by copyright law and cannot be used without permission.

[1598] "Filtering" is the process of removing specific information from data.

[1599] "Means of providing" refers to means of displaying or transmitting acquired data to the user.

[1600] "Means of notification" refers to a means of informing the user if data cannot be found.

[1601] A "smartphone" is a type of mobile phone, an electronic device capable of running a variety of applications.

[1602] "Smart glasses" are glasses-type wearable devices that have the function of displaying visual information.

[1603] This invention is a system that searches a database for data based on a data identifier provided by the user, filters the data, and provides it to the user. Specifically, it is implemented via a smartphone application or smart glasses.

[1604] The server has a means of searching for data entries in the database. When a user submits a data identifier, the server searches the database based on that identifier and retrieves the corresponding data entry.

[1605] The server then filters the retrieved data entries for confidential and copyrighted information. This filtering process involves deleting specific fields. For example, the "personal_info" and "copyrighted_content" fields might be removed, leaving only publicly available information.

[1606] The filtered data is provided to the user. Users can receive the data via their smartphone or smart glasses. If data corresponding to a data identifier is not found, the server will notify the user.

[1607] The hardware used includes smartphones (iOS and Android devices) and smart glasses (such as Google Glass). The software used is Flask, a Python web framework, for data processing and filtering.

[1608] Software and hardware usage examples

[1609] 1. Database Setup: Data is stored in a JSON database on the server.

[1610] 2. Processing User Requests: Users enter a data identifier using a smartphone app or smart glasses and send a request to the server.

[1611] 3. Data Retrieval and Filtering: The server retrieves the corresponding data entries from the database and filters out confidential information and copyrighted content.

[1612] 4. Data Provision: Filtered data will be displayed on the user's smartphone or smart glasses. This ensures that users can use the data with peace of mind.

[1613] Specific example

[1614] Example 1:

[1615] The user requests data identifier "data1" using their smartphone. The server retrieves the following data entry from the database.

[1616] json

[1617] {

[1618] "content": "Sample text data",

[1619] "author": "Author A",

[1620] "personal_info": "Sensitive Info",

[1621] "copyrighted_content": "Some copyrighted content"

[1622] }

[1623] The server performs filtering and provides the following data to the user.

[1624] json

[1625] {

[1626] "content": "Sample text data",

[1627] "author": "Author A"

[1628] }

[1629] Example 2:

[1630] A user requests data identifier "data3" using smart glasses. The server searches the database but cannot find the matching data. The server notifies the user of this.

[1631] Example of a prompt:

[1632] "We have specified 'data1' as the identifier for the training data. Please provide the data for the entry corresponding to this data identifier, with all confidential and copyrighted information removed."

[1633] In this way, this invention provides an environment in which users can use data with peace of mind, and realizes a system that achieves both data transparency and protection.

[1634] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1635] Step 1:

[1636] The user enters a specific data identifier using a smartphone or smart glasses. This input is then sent to the server via the application.

[1637] Input: Data identifier (e.g., "data1")

[1638] Specific action: The user enters a data identifier into the application's input field and taps the submit button.

[1639] Step 2:

[1640] The server receives a data identifier provided by the user. Based on the received data identifier, it searches the database and retrieves the corresponding data entry.

[1641] Input: Data identifier submitted by the user

[1642] Data processing: The server searches the database and retrieves the corresponding data entries.

[1643] Output: Data entry (Example: {

[1644] "content": "Sample text data",

[1645] "author": "Author A",

[1646] "personal_info": "Sensitive Info",

[1647] "copyrighted_content": "Some copyrighted content"

[1648] })

[1649] Specific operation: The server executes a database query and loads the corresponding data entries into memory.

[1650] Step 3:

[1651] The server filters out confidential and copyrighted content from the retrieved data entries. Specifically, it removes specified fields (e.g., "personal_info" and "copyrighted_content").

[1652] Input: Retrieved data entries

[1653] Data processing: Filter the data to remove the specified fields.

[1654] Output: Filtered data (Example: {

[1655] "content": "Sample text data",

[1656] "author": "Author A"

[1657] })

[1658] Specific operation: The server parses the JSON structure of the data entry and removes unnecessary fields.

[1659] Step 4:

[1660] The server provides the filtered data to the user. The user can view the filtered data through the application.

[1661] Input: Filtered data

[1662] Output: Data displayed on the user's application screen.

[1663] Specific operation: The server generates filtered data in JSON format and sends it to the user's device. The user's device displays the received data on the screen.

[1664] Step 5:

[1665] If the data corresponding to the data identifier is not found in the database, the server will notify the user accordingly.

[1666] Input: Data identifier provided by the user

[1667] Output: Notification message when data is not found (e.g., "Data not found")

[1668] Specific operation: If the server does not find the data as a result of the database search, it generates an appropriate notification message and sends it to the user's device. The user's device displays the notification message on the screen.

[1669] These steps enable the system to filter and provide data efficiently and securely.

[1670] 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.

[1671] To implement this invention, it is necessary to construct a system that recognizes the user's emotions and dynamically adjusts data filtering based on those emotions. The details of this system's processing are described below.

[1672] System Configuration

[1673] Database settings:

[1674] The server sets up a database to store the training data. This database contains many data entries, each identified by a unique data identifier. For example, data ID "data1" contains the following information:

[1675] {

[1676] "content": "Sample text data",

[1677] "author": "Author A",

[1678] "personal_info": "Sensitive Info",

[1679] "copyrighted_content": "Some copyrighted content"

[1680] }

[1681] Emotion engine settings:

[1682] The server has an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's text and voice input to identify the user's emotions.

[1683] Processing user requests

[1684] User request:

[1685] The user sends a specific data identifier (for example, data ID "data1") to the server. Simultaneously, the emotion engine recognizes emotions from the user's input. Upon receiving a request, the server searches its database and retrieves the corresponding data.

[1686] Data acquisition and filtering

[1687] Data acquisition:

[1688] The server searches the database for the corresponding data entry based on the data identifier provided by the user. When the data entry is found, the server retrieves its details.

[1689] Adjusting emotion-based filtering:

[1690] The server adjusts the strictness of its filtering process based on the user's emotions recognized by the emotion engine. For example, if a user expresses emotions such as "anxiety" or "worry," the server will more strictly filter out confidential and copyrighted content. On the other hand, if a user expresses emotions such as "reassurance" or "trust," the filtering strictness will be reduced.

[1691] Filtering process:

[1692] The server identifies and filters out confidential information (e.g., the "personal_info" field) and copyrighted content (e.g., the "copyrighted_content" field). The filtered data is then made publicly available.

[1693] Providing data to users

[1694] Data provided after filtering:

[1695] The filtered data is provided to the user. After adjustments are made according to the user's sentiment, for example, in the case of data ID "data1", the filtered data changes as follows:

[1696] {

[1697] "content": "Sample text data",

[1698] "author": "Author A"

[1699] }

[1700] Handling when data is not found

[1701] Notification if data is not found:

[1702] If the database does not contain data corresponding to the data identifier provided by the user, the server will notify the user. This notification allows the user to immediately recognize that the relevant data does not exist.

[1703] Specific example

[1704] Specific example 1:

[1705] The user requests data ID "data1" and indicates the emotion "anxiety". The server searches the database and retrieves the following information.

[1706] {

[1707] "content": "Sample text data",

[1708] "author": "Author A",

[1709] "personal_info": "Sensitive Info",

[1710] "copyrighted_content": "Some copyrighted content"

[1711] }

[1712] The server performs filtering to more strictly remove confidential information and copyrighted content. The filtered data will look like this:

[1713] {

[1714] "content": "Sample text data",

[1715] "author": "Author A"

[1716] }

[1717] The server then provides the filtered data to the user, ensuring they can use it with confidence.

[1718] Specific example 2:

[1719] The user requests data ID "data2" and expresses the emotion of "peace of mind." The server searches the database and retrieves the following information.

[1720] {

[1721] "content": "Another sample text",

[1722] "author": "Author B"

[1723] }

[1724] In this case, filtering is performed as usual because the data does not contain confidential information or copyrighted material. The server provides this data directly to the user.

[1725] In this way, the invention provides a system that achieves both transparency and security by recognizing the user's emotions and dynamically adjusting data filtering based on those emotions.

[1726] The following describes the processing flow.

[1727] Step 1:

[1728] The user specifies a data identifier (e.g., data ID "data1") from their device and sends a request to the server for data details. Simultaneously, the emotion engine analyzes the user's emotions through user input (text or voice).

[1729] Step 2:

[1730] The server extracts a data identifier from the received request and searches the database based on that identifier.

[1731] Step 3:

[1732] The server finds a matching data identifier in the database and retrieves the corresponding data entry. For example, it retrieves the data corresponding to data ID "data1".

[1733] Step 4:

[1734] The emotion engine recognizes emotions from user input. For example, it identifies emotions such as "anxiety," "relief," and "worry."

[1735] Step 5:

[1736] The server adjusts the strictness of the filtering process based on the user's emotions recognized by the emotion engine. For example, if the user indicates "anxiety," the filtering process will be made stricter.

[1737] Step 6:

[1738] The server identifies and filters out sensitive information (e.g., "personal_info") and copyrighted content (e.g., "copyrighted_content") from the retrieved data entries.

[1739] Step 7:

[1740] After the filtering process is performed, the server generates data from which confidential information and copyrighted content have been removed. For example, in the case of data ID "data1", the filtered data will look like this:

[1741] {

[1742] "content": "Sample text data",

[1743] "author": "Author A"

[1744] }

[1745] Step 8:

[1746] The server returns the filtered data to the user. The user receives and uses this data on their device.

[1747] Step 9:

[1748] If a data entry corresponding to a data identifier does not exist in the database, the server will notify the user that "the data does not exist." The user will then receive this notification and take appropriate action, such as specifying a new data identifier.

[1749] (Example 2)

[1750] 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".

[1751] Traditional data filtering systems rely on simple rule-based filtering, uniformly removing confidential and copyrighted information without considering user emotions or circumstances. This lack of flexibility in responding to user needs is a major challenge. In particular, providing appropriate information in situations where emotionally and contextually relevant data is required can be difficult, leading to decreased user satisfaction.

[1752] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for filtering confidential information and copyrighted content from the retrieved data, means for recognizing the user's emotions and dynamically adjusting the strictness of the filtering based on those emotions, and means for providing the filtered data to the user. This enables flexible data provision in response to the user's emotions, thereby improving user satisfaction.

[1753] A "user" is an individual or organization that uses the system to search for and retrieve data.

[1754] A "data identifier" is an identifier used to uniquely identify a specific data entry within a database.

[1755] A "database" is a storage system for storing and managing multiple data entries.

[1756] "Confidential information" refers to sensitive information that should not be made public and should be protected.

[1757] "Copyright-protected content" refers to works or content that should be protected under copyright law.

[1758] "Filtering" is the process of removing unnecessary or inappropriate parts from data based on specific conditions.

[1759] "Emotion" refers to the psychological and emotional state that a user exhibits towards the system.

[1760] An "emotion engine" is software or hardware that analyzes user input (text or voice) and identifies their emotions.

[1761] "Dynamic adjustment" means changing the strictness or parameters of a process in real time or as needed, depending on the conditions and circumstances.

[1762] "Searching" means retrieving data within a database based on specified conditions.

[1763] This invention relates to a system that recognizes user emotions and filters data based on those emotions. A detailed embodiment of the system is described below.

[1764] Database settings

[1765] The server configures a database that stores multiple data entries. Each entry in the database is identified by a unique data identifier and contains information such as the following:

[1766] {

[1767] "dataID": "data1",

[1768] "content": "Sample text data",

[1769] "author": "Author A",

[1770] "personal_info": "Sensitive Info",

[1771] "copyrighted_content": "Some copyrighted content"

[1772] }

[1773] Emotion Engine Settings

[1774] The server sets up an emotion engine to recognize the user's emotions. The emotion engine uses NLP (Natural Language Processing) libraries and speech recognition software (e.g., Google Cloud Speech-to-Text, IBM Watson Natural Language Understanding).

[1775] Receiving user requests

[1776] The user sends a specific data identifier (e.g., data ID "data1") from their device to the server. Simultaneously, the emotion engine analyzes the user's input (text or voice) to identify the user's emotion. When the request reaches the server, the server searches its database and retrieves the corresponding data entry.

[1777] Data acquisition and filtering

[1778] The server searches the database for the corresponding data entry based on the data identifier and retrieves detailed information. It then filters the retrieved data for confidential and copyrighted content. This filtering is dynamically adjusted based on the user's emotions as perceived by the emotion engine.

[1779] Filtering process

[1780] The filtering process identifies and removes confidential information (e.g., the "personal_info" field) and copyrighted content (e.g., the "copyrighted_content" field).

[1781] Providing data to users

[1782] The filtered data is provided to the user through their device. This allows the user to use the filtered data with peace of mind.

[1783] Specific example

[1784] Specific example 1:

[1785] The user requests data ID "data1" and indicates the emotion "anxiety". The server searches the database and retrieves the following information.

[1786] {

[1787] "content": "Sample text data",

[1788] "author": "Author A",

[1789] "personal_info": "Sensitive Info",

[1790] "copyrighted_content": "Some copyrighted content"

[1791] }

[1792] The server performs filtering to strictly remove confidential information and copyrighted content. The filtered data will look like this:

[1793] {

[1794] "content": "Sample text data",

[1795] "author": "Author A"

[1796] }

[1797] Specific example 2:

[1798] The user requests data ID "data2" and expresses the emotion of "peace of mind." The server searches the database and retrieves the following information.

[1799] {

[1800] "content": "Another sample text",

[1801] "author": "Author B"

[1802] }

[1803] In this case, filtering is not necessary, and the server provides this data directly to the user.

[1804] Example of a prompt

[1805] 1. Prompt message when the user is experiencing feelings of "anxiety":

[1806] "Emotion: Anxiety. Data ID: data1. Please strictly remove confidential information and copyrighted content from the retrieved data."

[1807] 2. Prompt message to use when the user feels "reassured":

[1808] "Emotion: Relief. Data ID: data2. Please provide this data directly."

[1809] This system enables flexible data filtering and delivery tailored to the user's emotions.

[1810] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1811] Step 1:

[1812] Database settings:

[1813] The server configures a database to store training data. It receives JSON data containing data entries as input. These data entries are identified by unique data identifiers, each with fields such as "content," "author," "personal_info," and "copyrighted_content." The server saves these data entries to the database. The configured database is generated as output.

[1814] Step 2:

[1815] Preparing the emotional engine:

[1816] The server sets up an emotion engine to recognize the user's emotions. As input, the server receives configuration files and API keys for NLP (Natural Language Processing) libraries and speech recognition software (e.g., Google Cloud Speech-to-Text, IBM Watson Natural Language Understanding). The server installs this software and applies its configuration. As output, the emotion engine becomes available for use.

[1817] Step 3:

[1818] Receiving user requests:

[1819] The user sends a specific data identifier (e.g., data ID "data1") to the server via their device. The server receives the user's request data and text or audio data for emotion recognition as input. The server parses these inputs and sends them, along with the data identifier, to the emotion engine. The output is the recognition of the user's emotion, ready for processing based on that emotion.

[1820] Step 4:

[1821] Searching and retrieving data:

[1822] The server searches the database based on the data identifier received from the user. It receives the data identifier as input and generates a database search query. The server searches for the corresponding data entry in the database and retrieves detailed information. The data entry is retrieved as output.

[1823] Step 5:

[1824] Adjusting emotion-based filtering:

[1825] The server dynamically adjusts the filtering strictness based on the user's emotions recognized by the emotion engine. It receives user emotion data and retrieved data entries as input. The server analyzes the emotion data and, for example, sets stricter filtering criteria if the user indicates emotions such as "anxiety" or "worry." The output is the adjusted filtering settings.

[1826] Step 6:

[1827] Data filtering process:

[1828] The server removes sensitive and copyrighted content from data entries based on the specified filtering settings. It receives filtering settings and data entries as input. The server filters fields such as "personal_info" and "copyrighted_content" to remove unwanted information. The filtered data is then generated as output.

[1829] Step 7:

[1830] Providing filtered data:

[1831] The server sends filtered data to the user. It receives filtered data as input and sends it to the user's terminal. As output, the user can receive the filtered data through their terminal.

[1832] Step 8:

[1833] Notification if data is not found:

[1834] The server notifies the user if data corresponding to the specified data identifier does not exist in the database. The input confirms that the search results are empty. The server generates an error message stating "no matching data found" and sends it to the user's terminal. The output informs the user that the specified data does not exist.

[1835] (Application Example 2)

[1836] 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".

[1837] Traditional systems lacked dynamic data filtering based on individual user emotional states, instead applying uniform filtering rules to all users. This meant they couldn't consider the anxiety or reassurance specific users felt regarding the data. As a result, providing flexible data tailored to user emotions was difficult, hindering improvements in the user experience.

[1838] 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.

[1839] In this invention, the server includes means for searching for data in a database based on a data identifier provided by the user, means for analyzing the user's emotions using an emotion engine that recognizes the user's emotions, means for dynamically adjusting and filtering confidential information and copyrighted content from the retrieved data based on the user's emotions, and means for providing the filtered data to the user. This allows for dynamic adjustment of the filtering strictness according to the user's emotions, enabling flexible data provision based on the emotions of individual users.

[1840] "User" refers to an individual or group that uses the system.

[1841] A "data identifier" is information that uniquely identifies a specific data entry within a database.

[1842] A "database" is a system or device for systematically storing and managing data.

[1843] An "emotion engine" is software or hardware that analyzes and identifies emotions from user input such as facial expressions and voice.

[1844] "Emotions" refer to the user's psychological state, including states such as "reassurance" and "anxiety."

[1845] "Confidential information" refers to personal information or important information that should not be made public.

[1846] "Copyright-protected content" refers to creative content and materials that should be protected under copyright law.

[1847] "Dynamic adjustment" means changing settings and behavior in real time according to conditions and circumstances.

[1848] "Filtering" is the process of selecting or deleting data based on specific conditions.

[1849] A "data entry" is a single unit of data stored within a database.

[1850] "To analyze" means to examine data in detail and clarify its structure and meaning.

[1851] "To provide" means to deliver data or services to a user or make them available for use.

[1852] In order to implement this invention, it is necessary to build a system that recognizes the user's emotions and dynamically adjusts data filtering based on those emotions.

[1853] System Configuration

[1854] Database settings:

[1855] The server sets up a database to store the training data. This database contains many data entries, each identified by a unique data identifier.

[1856] Emotion engine settings:

[1857] The server uses an emotion engine to recognize the user's emotions. This emotion engine analyzes the user's text, voice, or image input to identify their emotions. Specifically, it utilizes TensorFlow and OpenCV to recognize emotions in real time.

[1858] Processing user requests

[1859] User request:

[1860] The user sends a specific data identifier to the server. Simultaneously, the sentiment engine analyzes the user's emotions. Upon receiving a request, the server searches its database and retrieves the corresponding data.

[1861] Data acquisition and filtering

[1862] Data acquisition:

[1863] The server searches the database for the corresponding data entry based on the data identifier provided by the user and retrieves its details.

[1864] Adjusting emotion-based filtering:

[1865] The server adjusts the strictness of filtering based on the user's emotions recognized by the emotion engine. For example, if the user indicates "anxiety" or "worry," the server strictly filters out confidential and copyrighted content. On the other hand, if the user indicates "reassurance" or "trust," the filtering strictness is relaxed.

[1866] Filtering process:

[1867] The server identifies and filters out confidential and copyrighted information. After filtering, the data is converted into a format that can be publicly released.

[1868] Providing data to users

[1869] Data provided after filtering:

[1870] The filtered data is provided to the user. For example, if the data ID is "data1", the filtered data will change as follows:

[1871] json

[1872] {

[1873] "content": "Sample text data",

[1874] "author": "Author A"

[1875] }

[1876] Specific example

[1877] Specific example 1:

[1878] The user requests data ID "data1" and indicates an emotion of "anxiety." The server searches the database and retrieves the following information:

[1879] json

[1880] {

[1881] "content": "Sample text data",

[1882] "author": "Author A",

[1883] "personal_info": "Sensitive Info",

[1884] "copyrighted_content": "Some copyrighted content"

[1885] }

[1886] The server performs filtering to completely remove confidential and copyrighted information. The filtered data will look like this:

[1887] json

[1888] {

[1889] "content": "Sample text data",

[1890] "author": "Author A"

[1891] }

[1892] Specific example 2:

[1893] When a user requests data ID "data2" and expresses the emotion of "peace of mind," the server searches the database and retrieves the following information:

[1894] json

[1895] {

[1896] "content": "Another sample text",

[1897] "author": "Author B"

[1898] }

[1899] Since this data does not contain any confidential information or copyrighted material, it will be processed as usual and provided to the user as is.

[1900] The data provided to users can be filtered based on emotions, allowing for a balance between transparency and security of information for the user.

[1901] Example of a prompt:

[1902] "Please provide information based on data ID 'data1'. Analyze and filter the sentiment of this image."

[1903] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1904] Step 1:

[1905] The user sends a data identifier and image data from their device to the server. The input includes the data identifier and image data used for emotion recognition. The output is the server receiving the data identifier and image data.

[1906] Step 2:

[1907] The server searches the database based on the received data identifier. The input is the data identifier provided by the user, and the output is the retrieved data entry. For example, if "data1" exists in the database, its details are retrieved.

[1908] Step 3:

[1909] The server uses the received image data to activate the emotion engine and analyze the user's emotions. The input is image data, and the output is the user's emotions identified by the emotion engine. Specifically, the server uses TensorFlow and OpenCV to perform image processing and classify emotions.

[1910] Step 4:

[1911] The server dynamically adjusts the strictness of data filtering based on the analyzed emotions. The input is the user's emotions and the searched data entries, while the output is the filtered data. For example, if the emotion "anxiety" is detected, confidential information and copyrighted content will be strictly filtered.

[1912] Step 5:

[1913] The server performs data filtering. The input is the original data entries retrieved from the database along with the adjusted filtering conditions, and the output is the filtered data. Specifically, the server deletes or masks specified fields from the data entries.

[1914] Step 6:

[1915] The server provides the filtered data to the user. The input is the filtered data, and the output is the data sent back to the user's terminal. Specifically, the server creates an HTTP response that includes the filtered data.

[1916] Step 7:

[1917] The server notifies the user if a corresponding data entry does not exist in the database. The input is the database search result, and the output is a notification message stating "data not found." Specifically, the server creates an HTTP response containing an appropriate error message.

[1918] 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.

[1919] 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.

[1920] 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.

[1921] 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.

[1922] 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.

[1923] 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.

[1924] 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.

[1925] 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.

[1926] 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."

[1927] 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.

[1928] 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.

[1929] 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.

[1930] 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.

[1931] 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.

[1932] 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.

[1933] 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.

[1934] 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.

[1935] 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.

[1936] 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.

[1937] 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.

[1938] 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.

[1939] The following is further disclosed regarding the embodiments described above.

[1940] (Claim 1)

[1941] A means of searching for data in a database based on a data identifier provided by the user,

[1942] A means for filtering confidential information and copyrighted content from the retrieved data,

[1943] Means for providing the filtered data to the user,

[1944] A system that includes this.

[1945] (Claim 2)

[1946] The filtering of confidential information and copyrighted content is characterized by deleting specified fields in the database, as described in claim 1.

[1947] (Claim 3)

[1948] The system according to claim 1, further comprising means for notifying the user that no data exists if no data entry is found in the database.

[1949] "Example 1"

[1950] (Claim 1)

[1951] A means of searching for data in a database based on a data identifier provided by the user,

[1952] A means for filtering confidential information and copyrighted content from the retrieved data,

[1953] Means for providing the filtered data to the user,

[1954] A means of notifying the user if the relevant data does not exist in the database,

[1955] A system that includes this.

[1956] (Claim 2)

[1957] The filtering of confidential information and copyrighted content is characterized by deleting specified fields in the database, as described in claim 1.

[1958] (Claim 3)

[1959] The system according to claim 1, characterized in that a user enters a data identifier via a web browser or application and sends a request to a server.

[1960] "Application Example 1"

[1961] (Claim 1)

[1962] A means of searching for data in a database based on a data identifier provided by the user,

[1963] A means for filtering confidential information and copyrighted content from the retrieved data,

[1964] Means for providing the filtered data to the user,

[1965] A means of notifying the user if data cannot be found,

[1966] A system that includes this.

[1967] (Claim 2)

[1968] The filtering of confidential information and copyrighted content is characterized by deleting specified fields in the database, as described in claim 1.

[1969] (Claim 3)

[1970] The system according to claim 1, characterized in that it receives data requests from users via a smartphone or smart glasses and provides filtered data.

[1971] "Example 2 of combining an emotion engine"

[1972] (Claim 1)

[1973] A means of searching for data in a database based on a data identifier provided by the user,

[1974] A means for filtering confidential information and copyrighted content from the retrieved data,

[1975] A means of recognizing the user's emotions and dynamically adjusting the filtering strictness based on those emotions,

[1976] Means for providing the filtered data to the user,

[1977] A system that includes this.

[1978] (Claim 2)

[1979] The filtering of confidential information and copyrighted content is characterized by deleting specified fields in the database, as described in claim 1.

[1980] (Claim 3)

[1981] The system according to claim 1, further comprising means for notifying the user that no data exists if no data entry is found in the database.

[1982] "Application example 2 when combining with an emotional engine"

[1983] (Claim 1)

[1984] A means of searching for data in a database based on a data identifier provided by the user,

[1985] A means of analyzing user emotions using an emotion engine that recognizes user emotions,

[1986] A means for dynamically adjusting and filtering confidential information and copyrighted content from the retrieved data based on the user's sentiment,

[1987] Means for providing the filtered data to the user,

[1988] A system that includes this.

[1989] (Claim 2)

[1990] The system according to claim 1, wherein the filtering of confidential information and copyrighted content is characterized by deleting specified fields in the database, and the strictness of the filtering is adjusted according to the user's sentiment.

[1991] (Claim 3)

[1992] The system according to claim 1, further comprising means for notifying the user that no data exists if no data entry is found in the database. [Explanation of Symbols]

[1993] 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 means of searching for data in a database based on a data identifier provided by the user, A means for filtering confidential information and copyrighted content from the retrieved data, Means for providing the filtered data to the user, A system that includes this.

2. The filtering of confidential information and copyrighted content is characterized by deleting specified fields in the database, as described in claim 1.

3. The system according to claim 1, further comprising means for notifying the user that no data exists if no data entry is found in the database.

Images