System

Abstract

A system is provided.SOLUTION: The system includes a request analysis means, a retrieval means for retrieving content data up to a designated position, a filter means for applying a spoiler prevention filter to a retrieval result, a shaping means for shaping filtered data as response data, and a transmission means for transmitting the response data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] While watching content such as novels or movies, the following problems may arise. Specifically, users may lose track of the relationships between characters or forget the plot as it unfolds. In such cases, users may search the Internet to confirm the content, but there is a risk that they may unintentionally encounter spoilers. The purpose of this invention is to provide a means for users to avoid spoilers while checking the plot and character relationships up to a specific point. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means. First, a request analysis means analyzes the content of a question entered by a user. Next, a search means is used to search content data up to a specified position, and the relevant data is obtained. Spoiler information is removed or masked by a filter means that applies a spoiler prevention filter to the obtained data. After that, the filtered data is formatted by a formatting means that formats the data as response data, and the response data is sent to a terminal using a transmission means. A user can input and send a question through an interface means, receive a response from the server, and check the answer on a display means. This allows the user to obtain the necessary information while avoiding spoilers.

[0006] The "request analysis means" is a means for analyzing request data sent from a user and extracting the content of the question.

[0007] The "search means" is a means for searching and acquiring content data up to a specified position from a database.

[0008] The "filtering means" is a means for applying a spoiler prevention filter to the acquired data to remove or mask spoiler information.

[0009] The "formatting means" is a means for formatting the filtered data into a format that is easy for the user to understand and preparing it as response data.

[0010] The "transmission means" is a means for transmitting the formatted response data to the user's terminal.

[0011] The "interface means" is a means for providing an interface for a user to input a question and send a request to a server.

[0012] The "display means" is a means for displaying the response data received from the server to the user so that the user can check the contents.

[0013] A "database" is a storage device that stores content data and allows it to be searched and retrieved. [Brief explanation of the drawings]

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

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

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

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

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

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

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

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

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

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

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

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0035] This invention relates to a system that allows users to check the ongoing content and character relationships while watching content such as novels or movies. In particular, this system, which can provide information while reducing the risk of spoilers, is composed of request analysis means, search means, filter means, formatting means, and transmission means. Interface means and display means that constitute the user interface are also part of this system.

[0036] System Overview

[0037] The basic flow of the system is that the device accepts a question from the user and sends it to the server. The server analyzes the user's question and searches the database for content data up to the specified position. It then applies a spoiler prevention filter to the search results, formats the filtered data, and sends it to the user's device. Finally, the device displays the response data to the user.

[0038] Basic processing explanation

[0039] 1. Enter your question and submit your request

[0040] The terminal provides an interface where the user can enter a question. The user enters a question about the content up to a specific position through the interface and clicks the submit button. The terminal receives the user's input and sends it to the server as a request.

[0041] 2. Receiving and parsing the request

[0042] The server receives the request sent from the terminal, analyzes the request data sent by the user using the request analysis means, and extracts the question content.

[0043] 3. Searching for data

[0044] The server uses a search function to search the database for content data up to the specified position. For example, if a user inputs "Please tell me the synopsis up to page 5," the server retrieves the relevant data corresponding to this request.

[0045] 4. Apply a spoiler prevention filter

[0046] The server applies a spoiler prevention filter to the obtained data using a filtering means, which removes or masks information about important elements of the story or the ending.

[0047] 5. Formatting and sending response data

[0048] The server uses the formatting means to format the filtered data into a format that is easy for the user to understand, and transmits the formatted response data to the terminal via the transmission means.

[0049] 6. Receiving and Displaying Responses

[0050] The terminal receives the response data sent from the server and displays the response content to the user using a display unit, allowing the user to obtain the necessary information while avoiding the risk of spoilers.

[0051] Specific examples

[0052] For example, if a user is reading a novel and wants to recall the contents of the first five pages, the following steps would be taken:

[0053] 1. The user enters "Please tell me the synopsis up to page 5" into the device interface and presses the send button.

[0054] 2. The terminal sends the entered question to the server as request data.

[0055] 3. The server receives the request and analyzes the question using the request analysis means.

[0056] 4. The server uses a search means to retrieve content up to the specified position from the database.

[0057] 5. The server applies a spoiler prevention filter using a filtering method to mask important spoiler information.

[0058] 6. The server formats the filtered data using the formatting means and generates response data.

[0059] 7. The terminal receives the response data from the server and displays it to the user on the display means.

[0060] This allows users to efficiently obtain the information they need while avoiding the risk of spoilers. The system is designed to be user-friendly in terms of both visual and operational aspects, increasing user satisfaction. Furthermore, the spoiler prevention filter algorithm can be continuously improved, further enhancing user convenience.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] The terminal displays an interface that allows the user to enter a question. Specifically, it generates a text input field and displays it on the screen. It also creates a submit button that the user can click. With this interface displayed, the user is ready to enter a question.

[0064] Step 2:

[0065] The user enters a question into the interface and presses the send button. Specifically, the user enters a question that includes page numbers and time codes (e.g., "Please tell me the synopsis up to page 5") and clicks the send button. This action initiates the transmission of the request.

[0066] Step 3:

[0067] The device formats the user's question as request data and sends it to the server. Specifically, it obtains the user's input and sends it to the server's endpoint as an HTTP request. Once the transmission is complete, the request data is passed to the server.

[0068] Step 4:

[0069] The server receives and analyzes the request sent from the terminal. Specifically, it analyzes the request data and extracts the user's question (for example, page number or time code). This allows the server to understand what the user is looking for.

[0070] Step 5:

[0071] The server uses a search function to search the database for content data up to the specified position. Specifically, based on the extracted question, the server queries the content database to obtain the relevant data. For example, it obtains information "up to page 5."

[0072] Step 6:

[0073] The server applies a spoiler prevention filter to the data obtained using the filtering means. Specifically, the search results are passed through a spoiler prevention algorithm to remove or mask important plot or ending information. The filtered data has a low risk of spoilers.

[0074] Step 7:

[0075] The server uses a formatting means to format the filtered data as response data. Specifically, the server formats the filtered content data into a format that is easy for the user to understand (e.g., text format). This process generates the response data.

[0076] Step 8:

[0077] The server uses a transmission means to send the formatted response data to the terminal. Specifically, it returns the data to the terminal as an HTTP response. This data is a response to the user's request, and filtering has been completed.

[0078] Step 9:

[0079] The terminal receives the response sent from the server and displays it on the user interface. Specifically, the terminal displays the received response data in a display area such as a text box so that the user can check the content. This allows the user to obtain the necessary information without risking spoilers.

[0080] Example 1

[0081] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0082] In the past, when users wanted to check the content or the relationships between characters while watching content, the method of presenting information carried the risk of spoilers, which posed a problem. Therefore, there is a demand for a system that can safely and efficiently obtain the necessary information.

[0083] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0084] In this invention, the server includes a request analysis means for analyzing the content of a question entered by a user, a search means for searching a database for content data up to a specified position, a filter means for applying a spoiler prevention filter to the search results, a formatting means for formatting the filtered data into a format that is easy for the user to understand, and a transmission means for transmitting the formatted response data. This makes it possible to provide a system that allows users to safely and efficiently obtain the information they need while reducing the risk of spoilers.

[0085] The "request analysis means" is a device or program for analyzing the content of a question entered by a user.

[0086] The "search means" is a device or program for searching the database for content data up to a specified position.

[0087] "Filtering Measures" means devices or programs that apply anti-spoiler filters to search results to remove or mask information about important elements or the ending.

[0088] The "shaping means" is a device or program for converting the filtered data into a format that is easy for the user to understand.

[0089] The "transmission means" refers to a device or program for transmitting the formatted response data to the user terminal.

[0090] The "interface means" refers to a device or program that allows a user to input a question and transmit the question data to the server.

[0091] The "display means" is a device or program for receiving response data sent from the server and displaying it to the user.

[0092] A "database" is a system or platform for storing and retrieving content data up to a specified location.

[0093] This invention relates to a system that allows users to check the ongoing content and character relationships while watching content such as novels or movies. In particular, it is possible to provide information while reducing the risk of spoilers. This system is composed of request analysis means, search means, filter means, formatting means, and transmission means. Interface means and display means that constitute the user interface are also part of this system.

[0094] System Operation Overview

[0095] The terminal provides an interface that allows the user to input a question and sends the question to the server. The server analyzes the user's question and searches the database for content data up to the specified position. It applies a spoiler prevention filter to the search results, formats the filtered data, and sends it to the user's terminal. Finally, the terminal displays the response data to the user.

[0096] Hardware and software used

[0097] 1. Terminal

[0098] Hardware: Smartphones, tablets, PCs

[0099] Software: Web browser, mobile application

[0100] 2. Server

[0101] Hardware: Cloud server, dedicated server

[0102] Software: Web servers, database management systems (e.g., MySQL, PostgreSQL), natural language processing (NLP) libraries (e.g., spaCy, NLTK), machine learning models (e.g., BERT model, GPT-3)

[0103] Specific examples

[0104] Example 1: Checking the contents of a novel

[0105] The user types in "Please tell me the synopsis up to page 5" and clicks the submit button.

[0106] The terminal transmits the input question to the server as request data.

[0107] The server receives the request and extracts the keywords "up to page 5" and "summary" using a request analysis means.

[0108] The server uses a search tool to retrieve up to five pages of content from the database.

[0109] The server applies a spoiler prevention filter using a filtering means to mask important spoiler information.

[0110] The server formats the filtered data using the formatting means and generates response data.

[0111] The terminal receives the response data from the server and displays it to the user on the display means.

[0112] Prompt Sentence Examples

[0113] "Please give me a summary of the first five pages of your novel, but please avoid spoilers."

[0114] "Please tell me the plot of the movie up to the 30th minute, but please mask any important spoilers."

[0115] This allows users to efficiently obtain the necessary information without spoilers.

[0116] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0117] Step 1:

[0118] The terminal provides an interface that allows the user to input a question. The user inputs the question through this interface and clicks the submit button. For example, input data can be text such as "Please tell me the plot up to page 5." The input text data is captured by front-end technology such as JavaScript and sent to the server as an HTTP request. As output, an HTTP request message is generated.

[0119] Step 2:

[0120] The server receives an HTTP request sent from a terminal. The input is an HTTP request message, which contains the user's question. The request analysis means on the server analyzes this request message and extracts text data. Specifically, an NLP library (such as spaCy or NLTK) is used to analyze the part used as a query. The analysis results of the question are output as the specified page range and keywords.

[0121] Step 3:

[0122] The server uses a search tool to search the database for content data up to a specified position. The input is analyzed text data, which is sent to the database as an SQL query. For example, if the query is "contents up to page 5," data corresponding to the page range in question is retrieved from the database. The original text data is output as the search result.

[0123] Step 4:

[0124] The server applies a spoiler prevention filter to the textual data of the search results using a filter method. The input is the textual data retrieved from the database, and the filter method uses a machine learning model (e.g., BERT model or GPT-3) to identify and remove or mask important elements or information about the ending. The output is the filtered, safe data.

[0125] Step 5:

[0126] The server uses a formatting method to format the filtered data into a format that is easy for the user to understand. The input is the filtered data, which is converted into a visually easy-to-understand format using Markdown or HTML. Specifically, the content is organized using bullet points or paragraphs. The formatted response data is generated as the output.

[0127] Step 6:

[0128] The server transmits the formatted response data to the terminal via the transmission means. The input is the formatted response data, which is transmitted to the terminal as an HTTP response. The output is an HTTP response message.

[0129] Step 7:

[0130] The terminal receives an HTTP response sent from the server. The input is an HTTP response message, and the display means analyzes this response data and displays it to the user. Specifically, the received data is displayed as text on the screen. The output is generated as text to be displayed on the terminal screen.

[0131] (Application example 1)

[0132] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0133] While watching content, it is difficult for users to obtain necessary information about the ongoing content or the relationships between characters while avoiding spoilers. This has led to a growing demand for a system that allows users to obtain information efficiently without losing their enjoyment of the content. A system that can solve this problem is needed.

[0134] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0135] In this invention, the server includes a request analysis means, a search means for searching for content data up to a specified position, a filter means for applying a spoiler prevention filter to the search results, a formatting means for formatting the filtered data as response data, a transmission means for transmitting the response data, an interface means for inputting a question in natural language and transmitting it to the server, and a display means for receiving and displaying the response data transmitted from the server, and an application executable on a smart device. This allows the user to efficiently obtain information such as checking the ongoing content and understanding the relationships between characters while avoiding spoilers.

[0136] The "request analysis means" is a function for analyzing the request data sent by the user and extracting the question content.

[0137] The "search means" is a function for searching the database for content data up to a specified position.

[0138] "Filtering means" is a function that applies a spoiler prevention filter to search results to remove or mask important spoiler information.

[0139] The "formatting means" is a function for formatting the filtered data into a format that is easy for the user to understand.

[0140] The "transmission means" is a function for transmitting the formatted response data to the user terminal.

[0141] The "interface means" is a function that allows the user to input questions in natural language and send them to the server.

[0142] The "display means" is a function for receiving response data sent from the server and displaying it to the user.

[0143] An "application that can be executed on a smart device" is software that runs on a device such as a smartphone or tablet, and is an application that processes input from a user and responses from a server.

[0144] To implement this invention, a user uses a "content helper" application that runs on a smart device such as a smartphone or tablet. This application allows the user to ask questions in natural language about the ongoing content and relationships between characters while watching content such as a movie or novel.

[0145] Specifically, when a user inputs a question into the application, the data is sent to the server via the interface means of the smart device. On the server side, the question is analyzed using a request analysis means, and content data up to the specified position is searched for in a database using a search means. A spoiler prevention filter is then applied to the search results using a filter means. The filtered data is then formatted by a formatting means into a format that is easy for the user to understand, and is finally sent to the smart device via a transmission means. The smart device receives this data and displays it to the user via a display means.

[0146] The hardware used is a smart device such as a smartphone or tablet, and the software is a server application using Flask, and Requests is used for data communication. Any web framework (e.g., Django, Flask) can be used on the server side.

[0147] Examples:

[0148] For example, if a user is reading a novel and wants to check the relationships between characters, the system works as follows:

[0149] 1. The user enters "Who is the protagonist's friend?" in the "Content Helper" application on their smart device and presses the submit button.

[0150] 2. The smart device sends the question to the server via the interface means.

[0151] 3. On the server side, the request analysis means analyzes the content of the question, and the search means retrieves related content data from the database.

[0152] 4. Apply a spoiler prevention filter to the acquired data using a filtering method to remove important spoiler information.

[0153] 5. The filtered data is formatted by the formatting means into a format that is easy for the user to understand.

[0154] 6. The formatted data is sent to the smart device via the transmission means and displayed to the user via the display means.

[0155] This allows the user to efficiently obtain the necessary information while avoiding spoilers.

[0156] Example prompt sentence:

[0157] "If I want to investigate character relationships, generate Python code for a system that parses the question, provides relevant information, and applies a spoiler prevention filter."

[0158] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0159] Step 1:

[0160] The user enters a question into the "Content Helper" application on their smart device and presses the send button.

[0161] Input: Question (e.g., "Who is the protagonist's friend?")

[0162] Output: Request data including the question

[0163] How it works: The user enters a question in natural language into the application's interface and presses the submit button to generate the request data and proceed to the next step.

[0164] Step 2:

[0165] The terminal transmits the generated request data to the server through the interface means.

[0166] Input: Request data

[0167] Output: The request data sent to the server

[0168] Operation: The terminal captures the click event of the send button and sends this request data to the server.

[0169] Step 3:

[0170] The server receives the request data and analyzes the content of the question using a request analysis means.

[0171] Input: Request data

[0172] Output: Parsed question

[0173] How it works: The server analyzes the request data and extracts the question. For example, it analyzes the prompt text to extract information about the protagonist's friends.

[0174] Step 4:

[0175] The server uses a search means to search the database for content data up to the specified position.

[0176] Input: Parsed question content

[0177] Output: Corresponding content data

[0178] Operation: The server queries the database to find and retrieve the relevant content data based on the parsed query.

[0179] Step 5:

[0180] The server uses a filter means to apply a spoiler prevention filter to the acquired data.

[0181] Input: Acquired content data

[0182] Output: Filtered data

[0183] How it works: The server applies a filter algorithm to remove or mask important spoiler information, for example, removing information about the story's ending.

[0184] Step 6:

[0185] The server uses a formatting means to format the filtered data as response data.

[0186] Input: Filtered data

[0187] Output: Formatted response data

[0188] What it does: The server formats the filtered data in a user-friendly format, such as bullet points or concise sentences.

[0189] Step 7:

[0190] The server transmits the formatted response data to the terminal through the transmission means.

[0191] Input: Formatted response data

[0192] Output: Response data sent to the device

[0193] Operation: The server sends the formatted response data to the device.

[0194] Step 8:

[0195] The terminal displays the response data received from the server to the user using a display means.

[0196] Input: Received response data

[0197] Output: Information displayed to the user

[0198] Operation: The device receives the response data and displays it to the user in the application's display interface, allowing the user to efficiently obtain the necessary information while avoiding spoilers.

[0199] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0200] This invention relates to a system that allows users to check the content so far while avoiding spoilers while watching content such as novels or movies. In particular, this system provides information according to the user's emotional state by combining an emotion engine. This system is composed of request analysis means, search means, filter means, formatting means, transmission means, interface means, and display means.

[0201] System Overview

[0202] The basic flow of the system is that the device sends a question from the user to the server as request data, and the server analyzes the question while recognizing the user's emotions. Next, it searches the database for content data up to the specified position and applies a spoiler prevention filter to the search results. The filtered data is then formatted and sent to the device. The user's device receives this response data and displays it.

[0203] Basic processing explanation

[0204] 1. Enter your question and submit your request

[0205] The terminal provides an interface where the user can enter a question. The user enters the question and presses the send button to initiate a request.

[0206] 2. Emotional Recognition

[0207] The device uses an emotion engine to recognize the user's emotions. The recognition method is to identify emotions by analyzing the user's facial expressions, voice, or text input. For example, if the user is confused, the emotion engine will capture that emotion.

[0208] 3. Receiving and Parsing the Request

[0209] The server receives the request sent from the terminal and analyzes it together with the emotion data recognized by the emotion engine, and extracts the question content using the analysis means.

[0210] 4. Searching for data

[0211] The server uses a search means to search for content data up to a specified position. For example, based on a request such as "Please tell me the synopsis up to page 5," the server retrieves the relevant data from the database.

[0212] 5. Apply a spoiler prevention filter

[0213] The server uses a filter to apply a spoiler prevention filter to the acquired data. Based on the data from the emotion engine, the server adjusts the filter's strictness according to the user's emotional state (e.g., confusion, anxiety, excitement). For example, if the user feels anxious, the filter is strengthened.

[0214] 6. Formatting and sending response data

[0215] The server uses the formatting means to format the filtered data as response data, which is provided in an appropriate format taking into account the user's emotional state. The transmission means then transmits the response data to the terminal.

[0216] 7. Receiving and Displaying Responses

[0217] The terminal receives the response data sent from the server and uses the display means to display the data on a user interface so that the user can check the content. This allows the user to effectively obtain the necessary information while avoiding spoilers.

[0218] Specific examples

[0219] For example, if a user is reading a novel and wants to recall the contents of the first five pages, the following steps would be taken:

[0220] 1. The user enters "Please tell me the synopsis up to page 5" into the device interface and presses the send button.

[0221] 2. The device sends the input question to the server as request data. At the same time, the emotion engine recognizes the user's emotions (e.g., confusion, anxiety).

[0222] 3. The server receives the request and analyzes the question content and emotion data using the request analysis means.

[0223] 4. The server uses a search means to retrieve content up to the specified position from the database.

[0224] 5. The server applies a spoiler prevention filter using a filter means and adjusts the strength of the filter based on the emotion data.

[0225] 6. The server formats the filtered data using the formatting means and generates it as response data.

[0226] 7. The device receives the response data from the server and displays it along with an icon that indicates the emotion using facial expressions and voice. This allows the user to obtain the necessary information in a way that takes their emotions into consideration while avoiding spoilers.

[0227] This system effectively recognizes user emotions and provides optimal information based on those emotions, improving the user experience. Furthermore, the emotion engine algorithm can be continuously improved to achieve even more accurate emotion recognition and filtering, further enhancing user satisfaction and convenience.

[0228] The processing flow will be explained below.

[0229] Step 1:

[0230] The terminal displays an interface that allows the user to enter a question. Specifically, it generates a text input field and displays it on the screen. It also creates a submit button that the user can click. This allows the user to enter a question and prepare it for submission.

[0231] Step 2:

[0232] The user enters a question into the interface and presses the send button. Specifically, the user enters a question that includes page numbers and time codes (e.g., "Please tell me the synopsis up to page 5") and clicks the send button. This action initiates the transmission of the request.

[0233] Step 3:

[0234] The device formats the user's question as request data and sends it to the server. Specifically, it acquires the user's input and sends it to the server's endpoint as an HTTP request. The request data also includes the user's emotional data recognized by the emotion engine.

[0235] Step 4:

[0236] The device uses an emotion engine to recognize the user's emotions. Specifically, it identifies emotions by capturing the user's facial expressions with a camera, recording their voice with a microphone, or analyzing the phrasing of text input. For example, if the user is confused, the emotion engine will recognize the user's emotion as "confused" based on their facial expressions and tone of voice.

[0237] Step 5:

[0238] The server receives and analyzes requests sent from the terminal. Specifically, it analyzes the request data and extracts the user's question (e.g., page number and time code) and emotional data. This allows the server to understand what the user is asking and take into account the user's emotional state.

[0239] Step 6:

[0240] The server uses a search function to search the database for content data up to the specified position. Specifically, the server queries the content database based on the extracted question to obtain the relevant data. For example, it obtains information for "up to page 5."

[0241] Step 7:

[0242] The server applies a spoiler prevention filter to the data obtained using the filtering means. Specifically, the search results are passed through a spoiler prevention algorithm to remove or mask important plot or ending information. Furthermore, based on data from the emotion engine, the strength of the filter is adjusted according to the user's emotional state (e.g., confusion, anxiety, excitement). For example, if the user is feeling anxious, the filter is strengthened.

[0243] Step 8:

[0244] The server uses a formatting means to format the filtered data as response data. Specifically, the server formats the filtered content data into a format that is easy for the user to understand (e.g., text format). This process generates the response data.

[0245] Step 9:

[0246] The server uses a transmission means to send the formatted response data to the terminal. Specifically, the server returns the data to the terminal as an HTTP response. This data is a response to the user's request, and has been filtered.

[0247] Step 10:

[0248] The device receives the response data sent from the server. Specifically, it analyzes the received response data and displays it in a format that corresponds to the user's emotional state. The display also includes emotional icons and simple comments to help the user easily recognize changes in emotions.

[0249] Step 11:

[0250] The terminal displays the received response data on the user interface so that the user can check the content. Specifically, the data is displayed in a display area such as a text box or a pop-up window so that the user can easily understand the content. This allows the user to effectively obtain the necessary information without the risk of spoilers.

[0251] Example 2

[0252] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0253] In conventional content viewing systems, when users want to know specific information, it is difficult to obtain the necessary information while avoiding spoilers. Furthermore, the provision of information that takes into account the user's emotional state is lacking, resulting in a lack of improvement in the user experience. Furthermore, the lack of an appropriate filtering function based on emotions means that unnecessary or inappropriate information is sometimes provided, resulting in a decrease in user satisfaction.

[0254] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0255] In this invention, the server includes a request analysis means, a search means, and a filter means, which enable the server to recognize the user's emotions and provide appropriate information without giving away spoilers.

[0256] The "request analysis means" is a device or method that analyzes the content of the question entered by the user and identifies the information being sought.

[0257] A "search means" is a device or method for searching for relevant information from a database or storage based on a specified range or condition.

[0258] A "filtering means" is a device or method that removes unnecessary parts from acquired information and extracts only appropriate information based on specific conditions.

[0259] A "formation means" is a device or method that prepares the filtered information in a suitable format for presentation to a user.

[0260] The "transmitting means" is a device or method for transmitting the formatted response data to the user's terminal.

[0261] The "interface means" is a device or method for a user to input a question and perform operations or inputs to send a request to a server.

[0262] The "display means" is a device or method for visually displaying the response data received from the server to the user.

[0263] An "emotion engine" is a software or hardware configuration for analyzing a user's facial expressions, voice, or text input to recognize the user's emotional state.

[0264] This invention relates to a system that allows users to check the content so far while avoiding spoilers while watching content such as novels or movies. In particular, the system provides information according to the user's emotional state by combining it with an emotion engine.

[0265] The system consists of the following main components:

[0266] 1. Hardware and Software Description

[0267] Hardware: Devices used by users (smartphones, tablets, PCs, etc.), servers

[0268] Software: emotion engine, request analysis means, search means, filter means, formatting means, transmission means, display means

[0269] 2. Roles of each component

[0270] Emotion Engine

[0271] This software recognizes a user's emotional state. For example, it analyzes the user's facial expressions, voice, and text input to identify emotions such as confusion, anxiety, and excitement.

[0272] Request analysis method

[0273] This is a means for analyzing the content of a question entered by a user and sending it to the server as request data. This means operates when the user enters a question into the interface of the terminal and sends it.

[0274] Search methods

[0275] This is a method of searching a database for information up to a specified position. For example, based on a request such as "Please tell me the synopsis up to page 5," the corresponding information is retrieved from the database. This search method uses a database management system (e.g., MySQL).

[0276] Filtering Method

[0277] This is a method of applying a spoiler prevention filter to the acquired information. The strength of the filter is adjusted based on the user's emotional state, and information is provided that reduces the user's confusion and anxiety.

[0278] shaping means

[0279] This is a means of formatting filtered information as response data. It takes into account the user's emotional state and prepares the data to return information in an appropriate format.

[0280] Transmission method

[0281] This is a means of sending formatted response data to the user's device, allowing the user to check the necessary information on their device.

[0282] Interface Means

[0283] It is a means of providing an interface for users to input questions and send them to the server.

[0284] Display means

[0285] This is a way to display the response data sent from the server to the user, allowing the user to check the necessary information without spoiling the story.

[0286] 3. Examples of concrete examples and prompts

[0287] For example, if a user is reading a novel and wants to recall the contents of the first five pages, the following specific steps are taken:

[0288] 1. The user enters "Please tell me the synopsis up to page 5" into the device interface and presses the send button.

[0289] 2. The device uses an emotion engine to recognize the user's emotional state and sends it to the server as request data.

[0290] 3. The server analyzes the request and retrieves the content data up to the specified location from the database.

[0291] 4. The server applies a spoiler prevention filter to the search results, formats the filtered data, and generates response data.

[0292] 5. The formatted response data is sent to the user's terminal by the sending means and displayed to the user through the display means.

[0293] This allows users to obtain the information they need in a way that takes their emotions into consideration. This system provides appropriate information according to the user's emotional state, improving the user experience.

[0294] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0295] Step 1: Enter and submit your question

[0296] The terminal provides an interface where the user can enter a question. The user enters a question and presses the send button to generate request data. For example, the user might enter "Please tell me the synopsis up to page 5." The request data includes the question entered by the user. This becomes the input to the server.

[0297] Input: User question (e.g. "Please tell me the synopsis up to page 5")

[0298] Output: Request data (including the user question)

[0299] Step 2: Recognize emotions

[0300] The device activates an emotion engine and analyzes the user's facial expressions, voice, and text content to recognize emotions. For example, the device uses a camera and microphone to analyze the user's facial expressions and tone of voice to detect confusion. The recognized emotion data is also added to the request data.

[0301] Input: User facial expressions, voice, and text input

[0302] Output: Emotion data (e.g., confusion, anxiety)

[0303] Step 3: Receiving and Parsing the Request

[0304] The server receives the request data sent from the device. Using a request analysis method, it analyzes the user's question and emotional data and determines a specific response. For example, it distinguishes between information such as "I'm looking for a five-page synopsis" and "I'm confused."

[0305] Input: Request data (including user question and sentiment data)

[0306] Output: Analysis results (specific requests and emotional state)

[0307] Step 4: Search for data

[0308] The server uses a search means to search the database for content data up to the specified position. For example, it uses a database management system (e.g., MySQL) to obtain summary information for pages 1 to 5 of the novel.

[0309] Input: Analysis results (specific requirements)

[0310] Output: Search results (content data up to the specified position)

[0311] Step 5: Apply a spoiler-free filter

[0312] The server applies a spoiler prevention filter to the retrieved content data using a filtering means, for example, removing information about important plot points or climaxes, and strengthening the filter if the user is confused based on emotion data.

[0313] Input: Search results (content data up to the specified position), emotion data

[0314] Output: filtered data (spoiler prevention applied)

[0315] Step 6: Format and send response data

[0316] The server uses the formatting means to format the filtered data and generate response data. The server formats the response data in a format that takes into account the emotional state and transmits the formatted data to the terminal through the transmission means. For example, the server formats the data in a simple and easy-to-understand format for a confused user.

[0317] Input: Filtered data (spoiler prevention applied)

[0318] Output: Response data (formatted)

[0319] Step 7: Receive and display the response

[0320] The terminal receives the response data sent from the server. Using the display means, the terminal displays the response data on a user interface so that the user can confirm the contents. For example, up to five pages of summary information and additional messages to clear up confusion are displayed on the terminal screen.

[0321] Input: Response data (formatted)

[0322] Output: Displayed information (formatted response data)

[0323] (Application example 2)

[0324] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0325] In conventional content viewing systems, when a user wants to review the content or ask a specific question, there is no well-established means for obtaining appropriate information while avoiding spoilers. Furthermore, because information cannot be provided according to the user's emotional state, users often encounter unnecessary spoilers. This invention proposes a system that efficiently provides only the information necessary for the user while taking into account the user's emotions.

[0326] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0327] In this invention, the server includes request analysis means, search means for searching for content data up to a specified position, filter means for applying a spoiler prevention filter to the search results, formatting means for formatting the filtered data as response data, transmission means for transmitting the response data, emotion recognition means for recognizing the emotional state of the user, and adjustment means for adjusting the strictness of the filtering means based on the emotion recognition data. This allows the user to obtain the information they need in a form appropriate to their own emotional state while preventing spoilers.

[0328] The "request analysis means" refers to a device or program that analyzes the content of questions and request data sent by users.

[0329] "Search means" refers to a device or program that searches and retrieves content data up to a specified position from a database or storage.

[0330] "Filtering means" refers to a device or program that applies a filter to search results to prevent spoilers.

[0331] "Forming means" refers to a device or program that formats the filtered data into a format that is easy for the user to understand.

[0332] "Transmission means" refers to a device or program that transmits the formatted response data to the user's terminal.

[0333] "Emotion recognition means" refers to a device or program that uses a camera or microphone to recognize the user's emotional state.

[0334] The "adjustment means" refers to a device or program that adjusts the settings and strictness of the filtering means based on the emotion data obtained by the emotion recognition means.

[0335] "User interface means" refers to a device or program that provides an interface for a user to input a question and send it to the server.

[0336] "Display means" refers to a device or program that visually displays the response data sent from the server to the user.

[0337] "Database" refers to a data structure and management system for storing and searching content data up to a specified position.

[0338] This invention provides a system for content distribution services that allows users to avoid spoilers while checking the content of novels, movies, etc. In particular, by combining it with an emotion recognition function, the system provides information according to the user's emotional state.

[0339] System Configuration

[0340] The system is composed of the following modules: a request parser, a searcher, a filter, a formatter, a sender, an emotion recognizer, and a moderator. It also includes a user interface and a display.

[0341] Hardware and software used

[0342] The hardware used is a smartphone or smart glasses, such as an iPhone, Android device, Google Glass, or Microsoft HoloLens. On the server side, a cloud-based server (e.g., AWS or Google Cloud) is used.

[0343] The software used is Microsoft Azure Emotion API and Google Cloud Vision API for emotion recognition, ElasticSearch and Apache Solr for data search and analysis, and Python-based web frameworks such as Django and Flask for spoiler prevention filters.

[0344] Description of the Examples

[0345] First, the user inputs a question using a smartphone or smart glasses. For example, a user reading a novel might input a question such as, "Tell me the plot up to page 5." Examples of prompt sentences include, "Who appears at the end?" or "Tell me the relationship between these characters."

[0346] The device receives the questions entered by the user and simultaneously recognizes the user's emotions using a camera and microphone. For example, if the device recognizes that the user is confused, it sends that emotional state to the server.

[0347] The server analyzes the received request and searches for the necessary content data based on the emotion data and the question. For example, it retrieves the synopsis information up to the specified position from the database. This is done using a search method.

[0348] The acquired data is processed by a filtering means to prevent spoilers. Based on the emotion recognition data, the filtering strictness is set by an adjusting means, and the data is filtered in a manner suitable for the user.

[0349] The filtered data is shaped as response data by the shaping means and transmitted to the user terminal via the transmission means. The terminal visually displays the received response data to the user using the display means. This allows the user to obtain the information they need according to their emotions while avoiding spoilers.

[0350] Adding specific examples

[0351] For example, if a user is reading a novel and wants to check the plot up to page 5, they can type "Tell me the plot up to page 5" into their smartphone. At the same time, the emotion recognition means will determine the user's confusion state from the camera footage. The server analyzes this request, searches the database for the contents up to page 5, and applies a spoiler prevention filter appropriate for a confused user. The filtered results are then formatted and sent to the user's smartphone. They are then displayed on the screen for the user to review. In this way, the user can obtain the necessary information while avoiding spoilers.

[0352] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0353] Step 1:

[0354] The user inputs the question using a smartphone or smart glasses. For example, they might input text such as "Please tell me the plot up to page 5." The input text is temporarily saved on the device.

[0355] Step 2:

[0356] The device's camera and microphone are used to recognize the user's emotions. The emotion recognition method uses the Microsoft Azure Emotion API and Google Cloud Vision API to analyze the user's facial expressions and voice to identify their emotional state (e.g., confusion, anxiety, excitement). The identified emotional data is sent to the server along with the text input data.

[0357] Step 3:

[0358] The server uses its request analysis means to analyze the received user's question and emotional state. This analysis determines what data is needed and how much filtering is required. The analysis results are stored in internal memory.

[0359] Step 4:

[0360] Using the search means, the server searches the database for content data up to a specified position. For example, data corresponding to "a synopsis up to page 5" is extracted from the database. The search results are stored in temporary memory.

[0361] Step 5:

[0362] A filter means is used to apply a spoiler prevention filter to the search results. The strictness of the filter is set by an adjustment means based on emotion recognition data, and filtering is performed to an appropriate degree. For example, if the user is confused, the filter is strengthened. The filtered data is again stored in temporary memory.

[0363] Step 6:

[0364] The filtered data is formatted as response data using a formatting means. The format and representation of the data are optimized based on the user's emotional state. The formatted response data is stored in a transmission buffer of the server.

[0365] Step 7:

[0366] Using the transmission means, the server sends the formatted response data to the user's terminal. The transmission protocol is HTTP or HTTPS. The response data is stored in the terminal's receiving buffer.

[0367] Step 8:

[0368] The device visually displays the received response data to the user using a display means. For example, a "synopsis up to page 5" is displayed on the screen. Icons and explanations corresponding to the recognized emotions are also displayed. This allows the user to obtain the necessary information while avoiding spoilers.

[0369] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0370] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0371] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0372] [Second embodiment]

[0373] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0374] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0375] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0376] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0377] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0378] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0379] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0380] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0381] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0382] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0383] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0384] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0385] This invention relates to a system that allows users to check the ongoing content and character relationships while watching content such as novels or movies. In particular, this system, which can provide information while reducing the risk of spoilers, is composed of request analysis means, search means, filter means, formatting means, and transmission means. Interface means and display means that constitute the user interface are also part of this system.

[0386] System Overview

[0387] The basic flow of the system is that the device accepts a question from the user and sends it to the server. The server analyzes the user's question and searches the database for content data up to the specified position. It then applies a spoiler prevention filter to the search results, formats the filtered data, and sends it to the user's device. Finally, the device displays the response data to the user.

[0388] Basic processing explanation

[0389] 1. Enter your question and submit your request

[0390] The terminal provides an interface where the user can enter a question. The user enters a question about the content up to a specific position through the interface and clicks the submit button. The terminal receives the user's input and sends it to the server as a request.

[0391] 2. Receiving and parsing the request

[0392] The server receives the request sent from the terminal, analyzes the request data sent by the user using the request analysis means, and extracts the question content.

[0393] 3. Searching for data

[0394] The server uses a search function to search the database for content data up to the specified position. For example, if a user inputs "Please tell me the synopsis up to page 5," the server retrieves the relevant data corresponding to this request.

[0395] 4. Apply a spoiler prevention filter

[0396] The server applies a spoiler prevention filter to the obtained data using a filtering means, which removes or masks information about important elements of the story or the ending.

[0397] 5. Formatting and sending response data

[0398] The server uses the formatting means to format the filtered data into a format that is easy for the user to understand, and transmits the formatted response data to the terminal via the transmission means.

[0399] 6. Receiving and Displaying Responses

[0400] The terminal receives the response data sent from the server and displays the response content to the user using a display unit, allowing the user to obtain the necessary information while avoiding the risk of spoilers.

[0401] Specific examples

[0402] For example, if a user is reading a novel and wants to recall the contents of the first five pages, the following steps would be taken:

[0403] 1. The user enters "Please tell me the synopsis up to page 5" into the device interface and presses the send button.

[0404] 2. The terminal sends the entered question to the server as request data.

[0405] 3. The server receives the request and analyzes the question using the request analysis means.

[0406] 4. The server uses a search means to retrieve content up to the specified position from the database.

[0407] 5. The server applies a spoiler prevention filter using a filtering method to mask important spoiler information.

[0408] 6. The server formats the filtered data using the formatting means and generates response data.

[0409] 7. The terminal receives the response data from the server and displays it to the user on the display means.

[0410] This allows users to efficiently obtain the information they need while avoiding the risk of spoilers. The system is designed to be user-friendly in terms of both visual and operational aspects, increasing user satisfaction. Furthermore, the spoiler prevention filter algorithm can be continuously improved, further enhancing user convenience.

[0411] The processing flow will be explained below.

[0412] Step 1:

[0413] The terminal displays an interface that allows the user to enter a question. Specifically, it generates a text input field and displays it on the screen. It also creates a submit button that the user can click. With this interface displayed, the user is ready to enter a question.

[0414] Step 2:

[0415] The user enters a question into the interface and presses the send button. Specifically, the user enters a question that includes page numbers and time codes (e.g., "Please tell me the synopsis up to page 5") and clicks the send button. This action initiates the transmission of the request.

[0416] Step 3:

[0417] The device formats the user's question as request data and sends it to the server. Specifically, it obtains the user's input and sends it to the server's endpoint as an HTTP request. Once the transmission is complete, the request data is passed to the server.

[0418] Step 4:

[0419] The server receives and analyzes the request sent from the terminal. Specifically, it analyzes the request data and extracts the user's question (for example, page number or time code). This allows the server to understand what the user is looking for.

[0420] Step 5:

[0421] The server uses a search function to search the database for content data up to the specified position. Specifically, based on the extracted question, the server queries the content database to obtain the relevant data. For example, it obtains information "up to page 5."

[0422] Step 6:

[0423] The server applies a spoiler prevention filter to the data obtained using the filtering means. Specifically, the search results are passed through a spoiler prevention algorithm to remove or mask important plot or ending information. The filtered data has a low risk of spoilers.

[0424] Step 7:

[0425] The server uses a formatting means to format the filtered data as response data. Specifically, the server formats the filtered content data into a format that is easy for the user to understand (e.g., text format). This process generates the response data.

[0426] Step 8:

[0427] The server uses a transmission means to send the formatted response data to the terminal. Specifically, it returns the data to the terminal as an HTTP response. This data is a response to the user's request, and filtering has been completed.

[0428] Step 9:

[0429] The terminal receives the response sent from the server and displays it on the user interface. Specifically, the terminal displays the received response data in a display area such as a text box so that the user can check the content. This allows the user to obtain the necessary information without risking spoilers.

[0430] Example 1

[0431] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0432] In the past, when users wanted to check the content or the relationships between characters while watching content, the method of presenting information carried the risk of spoilers, which posed a problem. Therefore, there is a demand for a system that can safely and efficiently obtain the necessary information.

[0433] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0434] In this invention, the server includes a request analysis means for analyzing the content of a question entered by a user, a search means for searching a database for content data up to a specified position, a filter means for applying a spoiler prevention filter to the search results, a formatting means for formatting the filtered data into a format that is easy for the user to understand, and a transmission means for transmitting the formatted response data. This makes it possible to provide a system that allows users to safely and efficiently obtain the information they need while reducing the risk of spoilers.

[0435] The "request analysis means" is a device or program for analyzing the content of a question entered by a user.

[0436] The "search means" is a device or program for searching the database for content data up to a specified position.

[0437] "Filtering Measures" means devices or programs that apply anti-spoiler filters to search results to remove or mask information about important elements or the ending.

[0438] The "shaping means" is a device or program for converting the filtered data into a format that is easy for the user to understand.

[0439] The "transmission means" refers to a device or program for transmitting the formatted response data to the user terminal.

[0440] The "interface means" refers to a device or program that allows a user to input a question and transmit the question data to the server.

[0441] The "display means" is a device or program for receiving response data sent from the server and displaying it to the user.

[0442] A "database" is a system or platform for storing and retrieving content data up to a specified location.

[0443] This invention relates to a system that allows users to check the ongoing content and character relationships while watching content such as novels or movies. In particular, it is possible to provide information while reducing the risk of spoilers. This system is composed of request analysis means, search means, filter means, formatting means, and transmission means. Interface means and display means that constitute the user interface are also part of this system.

[0444] System Operation Overview

[0445] The terminal provides an interface that allows the user to input a question and sends the question to the server. The server analyzes the user's question and searches the database for content data up to the specified position. It applies a spoiler prevention filter to the search results, formats the filtered data, and sends it to the user's terminal. Finally, the terminal displays the response data to the user.

[0446] Hardware and software used

[0447] 1. Terminal

[0448] Hardware: Smartphones, tablets, PCs

[0449] Software: Web browser, mobile application

[0450] 2. Server

[0451] Hardware: Cloud server, dedicated server

[0452] Software: Web servers, database management systems (e.g., MySQL, PostgreSQL), natural language processing (NLP) libraries (e.g., spaCy, NLTK), machine learning models (e.g., BERT model, GPT-3)

[0453] Specific examples

[0454] Example 1: Checking the contents of a novel

[0455] The user types in "Please tell me the synopsis up to page 5" and clicks the submit button.

[0456] The terminal transmits the input question to the server as request data.

[0457] The server receives the request and extracts the keywords "up to page 5" and "summary" using a request analysis means.

[0458] The server uses a search tool to retrieve up to five pages of content from the database.

[0459] The server applies a spoiler prevention filter using a filtering means to mask important spoiler information.

[0460] The server formats the filtered data using the formatting means and generates response data.

[0461] The terminal receives the response data from the server and displays it to the user on the display means.

[0462] Prompt Sentence Examples

[0463] "Please give me a summary of the first five pages of your novel, but please avoid spoilers."

[0464] "Please tell me the plot of the movie up to the 30th minute, but please mask any important spoilers."

[0465] This allows users to efficiently obtain the necessary information without spoilers.

[0466] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0467] Step 1:

[0468] The terminal provides an interface that allows the user to input a question. The user inputs the question through this interface and clicks the submit button. For example, input data can be text such as "Please tell me the plot up to page 5." The input text data is captured by front-end technology such as JavaScript and sent to the server as an HTTP request. As output, an HTTP request message is generated.

[0469] Step 2:

[0470] The server receives an HTTP request sent from a terminal. The input is an HTTP request message, which contains the user's question. The request analysis means on the server analyzes this request message and extracts text data. Specifically, an NLP library (such as spaCy or NLTK) is used to analyze the part used as a query. The analysis results of the question are output as the specified page range and keywords.

[0471] Step 3:

[0472] The server uses a search tool to search the database for content data up to a specified position. The input is analyzed text data, which is sent to the database as an SQL query. For example, if the query is "contents up to page 5," data corresponding to the page range in question is retrieved from the database. The original text data is output as the search result.

[0473] Step 4:

[0474] The server applies a spoiler prevention filter to the textual data of the search results using a filter method. The input is the textual data retrieved from the database, and the filter method uses a machine learning model (e.g., BERT model or GPT-3) to identify and remove or mask important elements or information about the ending. The output is the filtered, safe data.

[0475] Step 5:

[0476] The server uses a formatting method to format the filtered data into a format that is easy for the user to understand. The input is the filtered data, which is converted into a visually easy-to-understand format using Markdown or HTML. Specifically, the content is organized using bullet points or paragraphs. The formatted response data is generated as the output.

[0477] Step 6:

[0478] The server transmits the formatted response data to the terminal via the transmission means. The input is the formatted response data, which is transmitted to the terminal as an HTTP response. The output is an HTTP response message.

[0479] Step 7:

[0480] The terminal receives an HTTP response sent from the server. The input is an HTTP response message, and the display means analyzes this response data and displays it to the user. Specifically, the received data is displayed as text on the screen. The output is generated as text to be displayed on the terminal screen.

[0481] (Application example 1)

[0482] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0483] While watching content, it is difficult for users to obtain necessary information about the ongoing content or the relationships between characters while avoiding spoilers. This has led to a growing demand for a system that allows users to obtain information efficiently without losing their enjoyment of the content. A system that can solve this problem is needed.

[0484] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0485] In this invention, the server includes a request analysis means, a search means for searching for content data up to a specified position, a filter means for applying a spoiler prevention filter to the search results, a formatting means for formatting the filtered data as response data, a transmission means for transmitting the response data, an interface means for inputting a question in natural language and transmitting it to the server, and a display means for receiving and displaying the response data transmitted from the server, and an application executable on a smart device. This allows the user to efficiently obtain information such as checking the ongoing content and understanding the relationships between characters while avoiding spoilers.

[0486] The "request analysis means" is a function for analyzing the request data sent by the user and extracting the question content.

[0487] The "search means" is a function for searching the database for content data up to a specified position.

[0488] "Filtering means" is a function that applies a spoiler prevention filter to search results to remove or mask important spoiler information.

[0489] The "formatting means" is a function for formatting the filtered data into a format that is easy for the user to understand.

[0490] The "transmission means" is a function for transmitting the formatted response data to the user terminal.

[0491] The "interface means" is a function that allows the user to input questions in natural language and send them to the server.

[0492] The "display means" is a function for receiving response data sent from the server and displaying it to the user.

[0493] An "application that can be executed on a smart device" is software that runs on a device such as a smartphone or tablet, and is an application that processes input from a user and responses from a server.

[0494] To implement this invention, a user uses a "content helper" application that runs on a smart device such as a smartphone or tablet. This application allows the user to ask questions in natural language about the ongoing content and relationships between characters while watching content such as a movie or novel.

[0495] Specifically, when a user inputs a question into the application, the data is sent to the server via the interface means of the smart device. On the server side, the question is analyzed using a request analysis means, and content data up to the specified position is searched for in a database using a search means. A spoiler prevention filter is then applied to the search results using a filter means. The filtered data is then formatted by a formatting means into a format that is easy for the user to understand, and is finally sent to the smart device via a transmission means. The smart device receives this data and displays it to the user via a display means.

[0496] The hardware used is a smart device such as a smartphone or tablet, and the software is a server application using Flask, and Requests is used for data communication. Any web framework (e.g., Django, Flask) can be used on the server side.

[0497] Examples:

[0498] For example, if a user is reading a novel and wants to check the relationships between characters, the system works as follows:

[0499] 1. The user enters "Who is the protagonist's friend?" in the "Content Helper" application on their smart device and presses the submit button.

[0500] 2. The smart device sends the question to the server via the interface means.

[0501] 3. On the server side, the request analysis means analyzes the content of the question, and the search means retrieves related content data from the database.

[0502] 4. Apply a spoiler prevention filter to the acquired data using a filtering method to remove important spoiler information.

[0503] 5. The filtered data is formatted by the formatting means into a format that is easy for the user to understand.

[0504] 6. The formatted data is sent to the smart device via the transmission means and displayed to the user via the display means.

[0505] This allows the user to efficiently obtain the necessary information while avoiding spoilers.

[0506] Example prompt sentence:

[0507] "If I want to investigate character relationships, generate Python code for a system that parses the question, provides relevant information, and applies a spoiler prevention filter."

[0508] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0509] Step 1:

[0510] The user enters a question into the "Content Helper" application on their smart device and presses the send button.

[0511] Input: Question (e.g., "Who is the protagonist's friend?")

[0512] Output: Request data including the question

[0513] How it works: The user enters a question in natural language into the application's interface and presses the submit button to generate the request data and proceed to the next step.

[0514] Step 2:

[0515] The terminal transmits the generated request data to the server through the interface means.

[0516] Input: Request data

[0517] Output: The request data sent to the server

[0518] Operation: The terminal captures the click event of the send button and sends this request data to the server.

[0519] Step 3:

[0520] The server receives the request data and analyzes the content of the question using a request analysis means.

[0521] Input: Request data

[0522] Output: Parsed question

[0523] How it works: The server analyzes the request data and extracts the question. For example, it analyzes the prompt text to extract information about the protagonist's friends.

[0524] Step 4:

[0525] The server uses a search means to search the database for content data up to the specified position.

[0526] Input: Parsed question content

[0527] Output: Corresponding content data

[0528] Operation: The server queries the database to find and retrieve the relevant content data based on the parsed query.

[0529] Step 5:

[0530] The server uses a filter means to apply a spoiler prevention filter to the acquired data.

[0531] Input: Acquired content data

[0532] Output: Filtered data

[0533] How it works: The server applies a filter algorithm to remove or mask important spoiler information, for example, removing information about the story's ending.

[0534] Step 6:

[0535] The server uses a formatting means to format the filtered data as response data.

[0536] Input: Filtered data

[0537] Output: Formatted response data

[0538] What it does: The server formats the filtered data in a user-friendly format, such as bullet points or concise sentences.

[0539] Step 7:

[0540] The server transmits the formatted response data to the terminal through the transmission means.

[0541] Input: Formatted response data

[0542] Output: Response data sent to the device

[0543] Operation: The server sends the formatted response data to the device.

[0544] Step 8:

[0545] The terminal displays the response data received from the server to the user using a display means.

[0546] Input: Received response data

[0547] Output: Information displayed to the user

[0548] Operation: The device receives the response data and displays it to the user in the application's display interface, allowing the user to efficiently obtain the necessary information while avoiding spoilers.

[0549] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0550] This invention relates to a system that allows users to check the content so far while avoiding spoilers while watching content such as novels or movies. In particular, this system provides information according to the user's emotional state by combining an emotion engine. This system is composed of request analysis means, search means, filter means, formatting means, transmission means, interface means, and display means.

[0551] System Overview

[0552] The basic flow of the system is that the device sends a question from the user to the server as request data, and the server analyzes the question while recognizing the user's emotions. Next, it searches the database for content data up to the specified position and applies a spoiler prevention filter to the search results. The filtered data is then formatted and sent to the device. The user's device receives this response data and displays it.

[0553] Basic processing explanation

[0554] 1. Enter your question and submit your request

[0555] The terminal provides an interface where the user can enter a question. The user enters the question and presses the send button to initiate a request.

[0556] 2. Emotional Recognition

[0557] The device uses an emotion engine to recognize the user's emotions. The recognition method is to identify emotions by analyzing the user's facial expressions, voice, or text input. For example, if the user is confused, the emotion engine will capture that emotion.

[0558] 3. Receiving and Parsing the Request

[0559] The server receives the request sent from the terminal and analyzes it together with the emotion data recognized by the emotion engine, and extracts the question content using the analysis means.

[0560] 4. Searching for data

[0561] The server uses a search means to search for content data up to a specified position. For example, based on a request such as "Please tell me the synopsis up to page 5," the server retrieves the relevant data from the database.

[0562] 5. Apply a spoiler prevention filter

[0563] The server uses a filter to apply a spoiler prevention filter to the acquired data. Based on the data from the emotion engine, the server adjusts the filter's strictness according to the user's emotional state (e.g., confusion, anxiety, excitement). For example, if the user feels anxious, the filter is strengthened.

[0564] 6. Formatting and sending response data

[0565] The server uses the formatting means to format the filtered data as response data, which is provided in an appropriate format taking into account the user's emotional state. The transmission means then transmits the response data to the terminal.

[0566] 7. Receiving and Displaying Responses

[0567] The terminal receives the response data sent from the server and uses the display means to display the data on a user interface so that the user can check the content. This allows the user to effectively obtain the necessary information while avoiding spoilers.

[0568] Specific examples

[0569] For example, if a user is reading a novel and wants to recall the contents of the first five pages, the following steps would be taken:

[0570] 1. The user enters "Please tell me the synopsis up to page 5" into the device interface and presses the send button.

[0571] 2. The device sends the input question to the server as request data. At the same time, the emotion engine recognizes the user's emotions (e.g., confusion, anxiety).

[0572] 3. The server receives the request and analyzes the question content and emotion data using the request analysis means.

[0573] 4. The server uses a search means to retrieve content up to the specified position from the database.

[0574] 5. The server applies a spoiler prevention filter using a filter means and adjusts the strength of the filter based on the emotion data.

[0575] 6. The server formats the filtered data using the formatting means and generates it as response data.

[0576] 7. The device receives the response data from the server and displays it along with an icon that indicates the emotion using facial expressions and voice. This allows the user to obtain the necessary information in a way that takes their emotions into consideration while avoiding spoilers.

[0577] This system effectively recognizes user emotions and provides optimal information based on those emotions, improving the user experience. Furthermore, the emotion engine algorithm can be continuously improved to achieve even more accurate emotion recognition and filtering, further enhancing user satisfaction and convenience.

[0578] The processing flow will be explained below.

[0579] Step 1:

[0580] The terminal displays an interface that allows the user to enter a question. Specifically, it generates a text input field and displays it on the screen. It also creates a submit button that the user can click. This allows the user to enter a question and prepare it for submission.

[0581] Step 2:

[0582] The user enters a question into the interface and presses the send button. Specifically, the user enters a question that includes page numbers and time codes (e.g., "Please tell me the synopsis up to page 5") and clicks the send button. This action initiates the transmission of the request.

[0583] Step 3:

[0584] The device formats the user's question as request data and sends it to the server. Specifically, it acquires the user's input and sends it to the server's endpoint as an HTTP request. The request data also includes the user's emotional data recognized by the emotion engine.

[0585] Step 4:

[0586] The device uses an emotion engine to recognize the user's emotions. Specifically, it identifies emotions by capturing the user's facial expressions with a camera, recording their voice with a microphone, or analyzing the phrasing of text input. For example, if the user is confused, the emotion engine will recognize the user's emotion as "confused" based on their facial expressions and tone of voice.

[0587] Step 5:

[0588] The server receives and analyzes requests sent from the terminal. Specifically, it analyzes the request data and extracts the user's question (e.g., page number and time code) and emotional data. This allows the server to understand what the user is asking and take into account the user's emotional state.

[0589] Step 6:

[0590] The server uses a search function to search the database for content data up to the specified position. Specifically, the server queries the content database based on the extracted question to obtain the relevant data. For example, it obtains information for "up to page 5."

[0591] Step 7:

[0592] The server applies a spoiler prevention filter to the data obtained using the filtering means. Specifically, the search results are passed through a spoiler prevention algorithm to remove or mask important plot or ending information. Furthermore, based on data from the emotion engine, the strength of the filter is adjusted according to the user's emotional state (e.g., confusion, anxiety, excitement). For example, if the user is feeling anxious, the filter is strengthened.

[0593] Step 8:

[0594] The server uses a formatting means to format the filtered data as response data. Specifically, the server formats the filtered content data into a format that is easy for the user to understand (e.g., text format). This process generates the response data.

[0595] Step 9:

[0596] The server uses a transmission means to send the formatted response data to the terminal. Specifically, the server returns the data to the terminal as an HTTP response. This data is a response to the user's request, and has been filtered.

[0597] Step 10:

[0598] The device receives the response data sent from the server. Specifically, it analyzes the received response data and displays it in a format that corresponds to the user's emotional state. The display also includes emotional icons and simple comments to help the user easily recognize changes in emotions.

[0599] Step 11:

[0600] The terminal displays the received response data on the user interface so that the user can check the content. Specifically, the data is displayed in a display area such as a text box or a pop-up window so that the user can easily understand the content. This allows the user to effectively obtain the necessary information without the risk of spoilers.

[0601] Example 2

[0602] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0603] In conventional content viewing systems, when users want to know specific information, it is difficult to obtain the necessary information while avoiding spoilers. Furthermore, the provision of information that takes into account the user's emotional state is lacking, resulting in a lack of improvement in the user experience. Furthermore, the lack of an appropriate filtering function based on emotions means that unnecessary or inappropriate information is sometimes provided, resulting in a decrease in user satisfaction.

[0604] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0605] In this invention, the server includes a request analysis means, a search means, and a filter means, which enable the server to recognize the user's emotions and provide appropriate information without giving away spoilers.

[0606] The "request analysis means" is a device or method that analyzes the content of the question entered by the user and identifies the information being sought.

[0607] A "search means" is a device or method for searching for relevant information from a database or storage based on a specified range or condition.

[0608] A "filtering means" is a device or method that removes unnecessary parts from acquired information and extracts only appropriate information based on specific conditions.

[0609] A "formation means" is a device or method that prepares the filtered information in a suitable format for presentation to a user.

[0610] The "transmitting means" is a device or method for transmitting the formatted response data to the user's terminal.

[0611] The "interface means" is a device or method for a user to input a question and perform operations or inputs to send a request to a server.

[0612] The "display means" is a device or method for visually displaying the response data received from the server to the user.

[0613] An "emotion engine" is a software or hardware configuration for analyzing a user's facial expressions, voice, or text input to recognize the user's emotional state.

[0614] This invention relates to a system that allows users to check the content so far while avoiding spoilers while watching content such as novels or movies. In particular, the system provides information according to the user's emotional state by combining it with an emotion engine.

[0615] The system consists of the following main components:

[0616] 1. Hardware and Software Description

[0617] Hardware: Devices used by users (smartphones, tablets, PCs, etc.), servers

[0618] Software: emotion engine, request analysis means, search means, filter means, formatting means, transmission means, display means

[0619] 2. Roles of each component

[0620] Emotion Engine

[0621] This software recognizes a user's emotional state by analyzing their facial expressions, voice, and text input to identify emotions such as confusion, anxiety, and excitement.

[0622] Request analysis method

[0623] This is a means for analyzing the content of a question entered by a user and sending it to the server as request data. This means operates when the user enters a question into the interface of the terminal and sends it.

[0624] Search methods

[0625] This is a method of searching a database for information up to a specified position. For example, based on a request such as "Please tell me the synopsis up to page 5," the corresponding information is retrieved from the database. This search method uses a database management system (e.g., MySQL).

[0626] Filtering Method

[0627] This is a method of applying a spoiler prevention filter to the acquired information. The strength of the filter is adjusted based on the user's emotional state, and information is provided that reduces the user's confusion and anxiety.

[0628] shaping means

[0629] This is a means of formatting filtered information as response data. It takes into account the user's emotional state and prepares the data to return information in an appropriate format.

[0630] Transmission method

[0631] This is a means of sending formatted response data to the user's device, allowing the user to check the necessary information on their device.

[0632] Interface Means

[0633] It is a means for providing an interface for users to input questions and send them to the server.

[0634] Display means

[0635] This is a way to display the response data sent from the server to the user, allowing the user to check the necessary information without spoiling the story.

[0636] 3. Examples of concrete examples and prompts

[0637] For example, if a user is reading a novel and wants to recall the contents of the first five pages, the following specific steps are taken:

[0638] 1. The user enters "Please tell me the synopsis up to page 5" into the device interface and presses the send button.

[0639] 2. The device uses an emotion engine to recognize the user's emotional state and sends it to the server as request data.

[0640] 3. The server analyzes the request and retrieves the content data from the database up to the specified location.

[0641] 4. The server applies a spoiler prevention filter to the search results, formats the filtered data, and generates response data.

[0642] 5. The formatted response data is sent to the user's terminal by the sending means and displayed to the user through the display means.

[0643] This allows users to obtain the information they need in a way that takes their emotions into consideration. This system provides appropriate information according to the user's emotional state, improving the user experience.

[0644] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0645] Step 1: Enter and submit your question

[0646] The terminal provides an interface where the user can enter a question. The user enters a question and presses the send button to generate request data. For example, the user might enter "Please tell me the synopsis up to page 5." The request data includes the question entered by the user. This becomes the input to the server.

[0647] Input: User question (e.g. "Please tell me the synopsis up to page 5")

[0648] Output: Request data (including the user question)

[0649] Step 2: Recognize emotions

[0650] The device activates an emotion engine and analyzes the user's facial expressions, voice, and text content to recognize emotions. For example, it uses a camera and microphone to analyze the user's facial expressions and tone of voice to detect confusion. The recognized emotion data is also added to the request data.

[0651] Input: User facial expressions, voice, and text input

[0652] Output: Emotion data (e.g., confusion, anxiety)

[0653] Step 3: Receiving and Parsing the Request

[0654] The server receives the request data sent from the device. Using a request analysis method, it analyzes the user's question and emotional data and determines a specific response. For example, it distinguishes between information such as "I'm looking for a five-page synopsis" and "I'm confused."

[0655] Input: Request data (including user question and sentiment data)

[0656] Output: Analysis results (specific requests and emotional state)

[0657] Step 4: Search for data

[0658] The server uses a search means to search the database for content data up to the specified position. For example, it uses a database management system (e.g., MySQL) to obtain summary information for pages 1 to 5 of a novel.

[0659] Input: Analysis results (specific requirements)

[0660] Output: Search results (content data up to the specified position)

[0661] Step 5: Apply a spoiler-free filter

[0662] The server uses a filtering means to apply a spoiler prevention filter to the retrieved content data, for example, removing information about important plot points or climaxes, and strengthening the filter if the user is confused based on emotion data.

[0663] Input: Search results (content data up to the specified position), emotion data

[0664] Output: filtered data (spoiler prevention applied)

[0665] Step 6: Format and send response data

[0666] The server uses the formatting means to format the filtered data and generate response data. The server formats the response data in a format that takes into account the emotional state and transmits the formatted data to the terminal through the transmission means. For example, the server formats the data in a simple and easy-to-understand format for a confused user.

[0667] Input: Filtered data (spoiler prevention applied)

[0668] Output: Response data (formatted)

[0669] Step 7: Receive and display the response

[0670] The terminal receives the response data sent from the server. Using the display means, the terminal displays the response data on a user interface so that the user can confirm the contents. For example, up to five pages of summary information and additional messages to clear up confusion are displayed on the terminal screen.

[0671] Input: Response data (formatted)

[0672] Output: Displayed information (formatted response data)

[0673] (Application example 2)

[0674] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0675] In conventional content viewing systems, when a user wants to review the content or ask a specific question, there is no well-established means for obtaining appropriate information while avoiding spoilers. Furthermore, because information cannot be provided according to the user's emotional state, users often encounter unnecessary spoilers. This invention proposes a system that efficiently provides only the information necessary for the user while taking into account the user's emotions.

[0676] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0677] In this invention, the server includes request analysis means, search means for searching for content data up to a specified position, filter means for applying a spoiler prevention filter to the search results, formatting means for formatting the filtered data as response data, transmission means for transmitting the response data, emotion recognition means for recognizing the emotional state of the user, and adjustment means for adjusting the strictness of the filtering means based on the emotion recognition data. This allows the user to obtain the information they need in a form appropriate to their own emotional state while preventing spoilers.

[0678] The "request analysis means" refers to a device or program that analyzes the content of questions and request data sent by users.

[0679] "Search means" refers to a device or program that searches and retrieves content data up to a specified position from a database or storage.

[0680] "Filtering means" refers to a device or program that applies a filter to search results to prevent spoilers.

[0681] "Forming means" refers to a device or program that formats the filtered data into a format that is easy for the user to understand.

[0682] "Transmission means" refers to a device or program that transmits the formatted response data to the user's terminal.

[0683] "Emotion recognition means" refers to a device or program that uses a camera or microphone to recognize the user's emotional state.

[0684] The "adjustment means" refers to a device or program that adjusts the settings and strictness of the filtering means based on the emotion data obtained by the emotion recognition means.

[0685] "User interface means" refers to a device or program that provides an interface for a user to input a question and send it to the server.

[0686] "Display means" refers to a device or program that visually displays the response data sent from the server to the user.

[0687] "Database" refers to a data structure and management system for storing and searching content data up to a specified position.

[0688] This invention provides a system for content distribution services that allows users to avoid spoilers while checking the content of novels, movies, etc. In particular, by combining it with an emotion recognition function, the system provides information according to the user's emotional state.

[0689] System Configuration

[0690] The system is composed of the following modules: a request parser, a searcher, a filter, a formatter, a sender, an emotion recognizer, and a moderator. It also includes a user interface and a display.

[0691] Hardware and software used

[0692] The hardware used is a smartphone or smart glasses, such as an iPhone, Android device, Google Glass, or Microsoft HoloLens. On the server side, a cloud-based server (e.g., AWS or Google Cloud) is used.

[0693] The software used is Microsoft Azure Emotion API and Google Cloud Vision API for emotion recognition, ElasticSearch and Apache Solr for data search and analysis, and Python-based web frameworks such as Django and Flask for spoiler prevention filters.

[0694] Description of the Examples

[0695] First, the user inputs a question using a smartphone or smart glasses. For example, a user reading a novel might input a question such as, "Tell me the plot up to page 5." Examples of prompts include, "Who appears at the end?" or "Tell me the relationship between these characters."

[0696] The device receives the questions entered by the user and simultaneously recognizes the user's emotions using a camera and microphone. For example, if the device recognizes that the user is confused, it sends that emotional state to the server.

[0697] The server analyzes the received request and searches for the necessary content data based on the emotion data and the question. For example, it retrieves the synopsis information up to the specified position from the database. This is done using a search method.

[0698] The acquired data is processed by a filtering means to prevent spoilers. Based on the emotion recognition data, the strictness of the filter is set by an adjusting means, and the data is filtered in a manner suitable for the user.

[0699] The filtered data is shaped as response data by the shaping means and transmitted to the user terminal via the transmission means. The terminal visually displays the received response data to the user using the display means. This allows the user to obtain the information they need according to their emotions while avoiding spoilers.

[0700] Adding specific examples

[0701] For example, if a user is reading a novel and wants to check the plot up to page 5, they can type "Tell me the plot up to page 5" into their smartphone. At the same time, the emotion recognition means will determine the user's confusion state from the camera footage. The server analyzes this request, searches the database for the contents up to page 5, and applies a spoiler prevention filter appropriate for a confused user. The filtered results are then formatted and sent to the user's smartphone. They are then displayed on the screen for the user to review. In this way, the user can obtain the necessary information while avoiding spoilers.

[0702] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0703] Step 1:

[0704] The user inputs the question using a smartphone or smart glasses. For example, they might input text such as "Please tell me the plot up to page 5." The input text is temporarily saved on the device.

[0705] Step 2:

[0706] The device's camera and microphone are used to recognize the user's emotions. The emotion recognition method uses the Microsoft Azure Emotion API and Google Cloud Vision API to analyze the user's facial expressions and voice to identify their emotional state (e.g., confusion, anxiety, excitement). The identified emotional data is sent to the server along with the text input data.

[0707] Step 3:

[0708] The server uses its request analysis means to analyze the received user's question and emotional state. This analysis determines what data is needed and how much filtering is required. The analysis results are stored in internal memory.

[0709] Step 4:

[0710] Using the search means, the server searches the database for content data up to a specified position. For example, data corresponding to "a synopsis up to page 5" is extracted from the database. The search results are stored in temporary memory.

[0711] Step 5:

[0712] A filter means is used to apply a spoiler prevention filter to the search results. The strictness of the filter is set by an adjustment means based on emotion recognition data, and filtering is performed to an appropriate degree. For example, if the user is confused, the filter is strengthened. The filtered data is again stored in temporary memory.

[0713] Step 6:

[0714] The filtered data is formatted as response data using a formatting means. The format and representation of the data are optimized based on the user's emotional state. The formatted response data is stored in a transmission buffer of the server.

[0715] Step 7:

[0716] Using the transmission means, the server sends the formatted response data to the user's terminal. The transmission protocol is HTTP or HTTPS. The response data is stored in the terminal's receiving buffer.

[0717] Step 8:

[0718] The device visually displays the received response data to the user using a display means. For example, a "synopsis up to page 5" is displayed on the screen. Icons and explanations corresponding to the recognized emotions are also displayed. This allows the user to obtain the necessary information while avoiding spoilers.

[0719] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0720] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0721] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0722] [Third embodiment]

[0723] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0724] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0725] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0726] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0727] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0728] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0729] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0730] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0731] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0732] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0733] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0734] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0735] This invention relates to a system that allows users to check the ongoing content and character relationships while watching content such as novels or movies. In particular, this system, which can provide information while reducing the risk of spoilers, is composed of request analysis means, search means, filter means, formatting means, and transmission means. Interface means and display means that constitute the user interface are also part of this system.

[0736] System Overview

[0737] The basic flow of the system is that the device accepts a question from the user and sends it to the server. The server analyzes the user's question and searches the database for content data up to the specified position. It then applies a spoiler prevention filter to the search results, formats the filtered data, and sends it to the user's device. Finally, the device displays the response data to the user.

[0738] Basic processing explanation

[0739] 1. Enter your question and submit your request

[0740] The terminal provides an interface where the user can enter a question. The user enters a question about the content up to a specific position through the interface and clicks the submit button. The terminal receives the user's input and sends it to the server as a request.

[0741] 2. Receiving and parsing the request

[0742] The server receives the request sent from the terminal, and uses the request analysis means to analyze the request data sent by the user and extract the question content.

[0743] 3. Searching for data

[0744] The server uses a search function to search the database for content data up to the specified position. For example, if a user inputs "Please tell me the synopsis up to page 5," the server retrieves the relevant data corresponding to this request.

[0745] 4. Apply a spoiler prevention filter

[0746] The server applies a spoiler prevention filter to the obtained data using a filtering means, which removes or masks information about important elements of the story or the ending.

[0747] 5. Formatting and sending response data

[0748] The server uses the formatting means to format the filtered data into a format that is easy for the user to understand, and transmits the formatted response data to the terminal via the transmission means.

[0749] 6. Receiving and Displaying Responses

[0750] The terminal receives the response data sent from the server and displays the response content to the user using a display unit, allowing the user to obtain the necessary information while avoiding the risk of spoilers.

[0751] Specific examples

[0752] For example, if a user is reading a novel and wants to recall the contents of the first five pages, the following steps would be taken:

[0753] 1. The user enters "Please tell me the synopsis up to page 5" into the device interface and presses the send button.

[0754] 2. The terminal sends the entered question to the server as request data.

[0755] 3. The server receives the request and analyzes the question using the request analysis means.

[0756] 4. The server uses a search method to retrieve content up to the specified position from the database.

[0757] 5. The server applies a spoiler prevention filter using a filtering method to mask important spoiler information.

[0758] 6. The server formats the filtered data using the formatting means and generates response data.

[0759] 7. The terminal receives the response data from the server and displays it to the user on the display means.

[0760] This allows users to efficiently obtain the information they need while avoiding the risk of spoilers. The system is designed to be user-friendly in terms of both visual and operational aspects, increasing user satisfaction. Furthermore, the spoiler prevention filter algorithm can be continuously improved, further enhancing user convenience.

[0761] The processing flow will be explained below.

[0762] Step 1:

[0763] The terminal displays an interface that allows the user to enter a question. Specifically, it generates a text input field and displays it on the screen. It also creates a submit button that the user can click. With this interface displayed, the user is ready to enter a question.

[0764] Step 2:

[0765] The user enters a question into the interface and presses the send button. Specifically, the user enters a question that includes page numbers and time codes (e.g., "Please tell me the synopsis up to page 5") and clicks the send button. This action initiates the transmission of the request.

[0766] Step 3:

[0767] The device formats the user's question as request data and sends it to the server. Specifically, it obtains the user's input and sends it to the server's endpoint as an HTTP request. Once the transmission is complete, the request data is passed to the server.

[0768] Step 4:

[0769] The server receives and analyzes the request sent from the terminal. Specifically, it analyzes the request data and extracts the user's question (for example, page number or time code). This allows the server to understand what the user is looking for.

[0770] Step 5:

[0771] The server uses a search function to search the database for content data up to the specified position. Specifically, based on the extracted question, the server queries the content database to obtain the relevant data. For example, it obtains information for "up to page 5."

[0772] Step 6:

[0773] The server applies a spoiler prevention filter to the data obtained using the filtering means. Specifically, the search results are passed through a spoiler prevention algorithm to remove or mask important plot or ending information. The filtered data has a low risk of spoilers.

[0774] Step 7:

[0775] The server uses a formatting means to format the filtered data as response data. Specifically, the server formats the filtered content data into a format that is easy for the user to understand (e.g., text format). This process generates the response data.

[0776] Step 8:

[0777] The server uses a transmission means to send the formatted response data to the terminal. Specifically, it returns the data to the terminal as an HTTP response. This data is a response to the user's request, and filtering has been completed.

[0778] Step 9:

[0779] The terminal receives the response sent from the server and displays it on the user interface. Specifically, the terminal displays the received response data in a display area such as a text box so that the user can check the content. This allows the user to obtain the necessary information without risking spoilers.

[0780] Example 1

[0781] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0782] In the past, when users wanted to check the content or the relationships between characters while watching content, the method of presenting information carried the risk of spoilers, which posed a problem. Therefore, there is a demand for a system that can safely and efficiently obtain the necessary information.

[0783] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0784] In this invention, the server includes a request analysis means for analyzing the content of a question entered by a user, a search means for searching a database for content data up to a specified position, a filter means for applying a spoiler prevention filter to the search results, a formatting means for formatting the filtered data into a format that is easy for the user to understand, and a transmission means for transmitting the formatted response data. This makes it possible to provide a system that allows users to safely and efficiently obtain the information they need while reducing the risk of spoilers.

[0785] The "request analysis means" is a device or program for analyzing the content of a question entered by a user.

[0786] The "search means" is a device or program for searching the database for content data up to a specified position.

[0787] "Filtering Measures" means devices or programs that apply anti-spoiler filters to search results to remove or mask information about important elements or the ending.

[0788] The "shaping means" is a device or program for converting the filtered data into a format that is easy for the user to understand.

[0789] The "transmission means" refers to a device or program for transmitting the formatted response data to the user terminal.

[0790] The "interface means" refers to a device or program that allows a user to input a question and transmit the question data to the server.

[0791] The "display means" is a device or program for receiving response data sent from the server and displaying it to the user.

[0792] A "database" is a system or platform for storing and retrieving content data up to a specified location.

[0793] This invention relates to a system that allows users to check the ongoing content and character relationships while watching content such as novels or movies. In particular, it is possible to provide information while reducing the risk of spoilers. This system is composed of request analysis means, search means, filter means, formatting means, and transmission means. Interface means and display means that constitute the user interface are also part of this system.

[0794] System Operation Overview

[0795] The terminal provides an interface that allows the user to input a question and sends the question to the server. The server analyzes the user's question and searches the database for content data up to the specified position. It applies a spoiler prevention filter to the search results, formats the filtered data, and sends it to the user's terminal. Finally, the terminal displays the response data to the user.

[0796] Hardware and software used

[0797] 1. Terminal

[0798] Hardware: Smartphones, tablets, PCs

[0799] Software: Web browser, mobile application

[0800] 2. Server

[0801] Hardware: Cloud server, dedicated server

[0802] Software: Web servers, database management systems (e.g., MySQL, PostgreSQL), natural language processing (NLP) libraries (e.g., spaCy, NLTK), machine learning models (e.g., BERT model, GPT-3)

[0803] Specific examples

[0804] Example 1: Checking the contents of a novel

[0805] The user types in "Please tell me the synopsis up to page 5" and clicks the submit button.

[0806] The terminal transmits the input question to the server as request data.

[0807] The server receives the request and extracts the keywords "up to page 5" and "summary" using a request analysis means.

[0808] The server uses a search tool to retrieve up to five pages of content from the database.

[0809] The server applies a spoiler prevention filter using a filtering means to mask important spoiler information.

[0810] The server formats the filtered data using the formatting means and generates response data.

[0811] The terminal receives the response data from the server and displays it to the user on the display means.

[0812] Prompt Sentence Examples

[0813] "Please give me a summary of the first five pages of your novel, but please avoid spoilers."

[0814] "Please tell me the plot of the movie up to the 30th minute, but please mask any important spoilers."

[0815] This allows users to efficiently obtain the necessary information without spoilers.

[0816] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0817] Step 1:

[0818] The terminal provides an interface that allows the user to input a question. The user inputs the question through this interface and clicks the submit button. For example, input data can be text such as "Please tell me the plot up to page 5." The input text data is captured by front-end technology such as JavaScript and sent to the server as an HTTP request. As output, an HTTP request message is generated.

[0819] Step 2:

[0820] The server receives an HTTP request sent from a terminal. The input is an HTTP request message, which contains the user's question. The request analysis means on the server analyzes this request message and extracts text data. Specifically, an NLP library (such as spaCy or NLTK) is used to analyze the part used as a query. The analysis results of the question are output as the specified page range and keywords.

[0821] Step 3:

[0822] The server uses a search tool to search the database for content data up to a specified position. The input is analyzed text data, which is sent to the database as an SQL query. For example, if the query is "contents up to page 5," data corresponding to the page range in question is retrieved from the database. The original text data is output as the search result.

[0823] Step 4:

[0824] The server applies a spoiler prevention filter to the textual data of the search results using a filter method. The input is the textual data retrieved from the database, and the filter method uses a machine learning model (e.g., BERT model or GPT-3) to identify and remove or mask important elements or information about the ending. The output is the filtered, safe data.

[0825] Step 5:

[0826] The server uses a formatting method to format the filtered data into a format that is easy for the user to understand. The input is the filtered data, which is converted into a visually easy-to-understand format using Markdown or HTML. Specifically, the content is organized using bullet points or paragraphs. The formatted response data is generated as the output.

[0827] Step 6:

[0828] The server transmits the formatted response data to the terminal via the transmission means. The input is the formatted response data, which is transmitted to the terminal as an HTTP response. The output is an HTTP response message.

[0829] Step 7:

[0830] The terminal receives an HTTP response sent from the server. The input is an HTTP response message, and the display means analyzes this response data and displays it to the user. Specifically, the received data is displayed as text on the screen. The output is generated as text to be displayed on the terminal screen.

[0831] (Application example 1)

[0832] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0833] While watching content, it is difficult for users to obtain necessary information about the ongoing content or the relationships between characters while avoiding spoilers. This has led to a growing demand for a system that allows users to obtain information efficiently without losing their enjoyment of the content. A system that can solve this problem is needed.

[0834] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0835] In this invention, the server includes a request analysis means, a search means for searching for content data up to a specified position, a filter means for applying a spoiler prevention filter to the search results, a formatting means for formatting the filtered data as response data, a transmission means for transmitting the response data, an interface means for inputting a question in natural language and transmitting it to the server, and a display means for receiving and displaying the response data transmitted from the server, and an application executable on a smart device. This allows the user to efficiently obtain information such as checking the ongoing content and understanding the relationships between characters while avoiding spoilers.

[0836] The "request analysis means" is a function for analyzing the request data sent by the user and extracting the question content.

[0837] The "search means" is a function for searching the database for content data up to a specified position.

[0838] "Filtering means" is a function that applies a spoiler prevention filter to search results to remove or mask important spoiler information.

[0839] The "formatting means" is a function for formatting the filtered data into a format that is easy for the user to understand.

[0840] The "transmission means" is a function for transmitting the formatted response data to the user terminal.

[0841] The "interface means" is a function that allows the user to input questions in natural language and send them to the server.

[0842] The "display means" is a function for receiving response data sent from the server and displaying it to the user.

[0843] An "application that can be executed on a smart device" is software that runs on a device such as a smartphone or tablet, and is an application that processes input from a user and responses from a server.

[0844] To implement this invention, a user uses a "content helper" application that runs on a smart device such as a smartphone or tablet. This application allows the user to ask questions in natural language about the ongoing content and relationships between characters while watching content such as a movie or novel.

[0845] Specifically, when a user inputs a question into the application, the data is sent to the server via the interface means of the smart device. On the server side, the question is analyzed using a request analysis means, and content data up to the specified position is searched for in a database using a search means. A spoiler prevention filter is then applied to the search results using a filter means. The filtered data is then formatted by a formatting means into a format that is easy for the user to understand, and is finally sent to the smart device via a transmission means. The smart device receives this data and displays it to the user via a display means.

[0846] The hardware used is a smart device such as a smartphone or tablet, and the software is a server application using Flask, and Requests is used for data communication. Any web framework (e.g., Django, Flask) can be used on the server side.

[0847] Examples:

[0848] For example, if a user is reading a novel and wants to check the relationships between characters, the system works as follows:

[0849] 1. The user enters "Who is the protagonist's friend?" in the "Content Helper" application on their smart device and presses the submit button.

[0850] 2. The smart device sends the question to the server via the interface means.

[0851] 3. On the server side, the request analysis means analyzes the content of the question, and the search means retrieves related content data from the database.

[0852] 4. Apply a spoiler prevention filter to the acquired data using a filtering method to remove important spoiler information.

[0853] 5. The filtered data is formatted by the formatting means into a format that is easy for the user to understand.

[0854] 6. The formatted data is sent to the smart device via the transmission means and displayed to the user via the display means.

[0855] This allows the user to efficiently obtain the necessary information while avoiding spoilers.

[0856] Example prompt sentence:

[0857] "If I want to investigate character relationships, generate Python code for a system that parses the question, provides relevant information, and applies a spoiler prevention filter."

[0858] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0859] Step 1:

[0860] The user enters a question into the "Content Helper" application on their smart device and presses the send button.

[0861] Input: Question (e.g., "Who is the protagonist's friend?")

[0862] Output: Request data including the question

[0863] How it works: The user enters a question in natural language into the application's interface and presses the submit button to generate the request data and proceed to the next step.

[0864] Step 2:

[0865] The terminal transmits the generated request data to the server through the interface means.

[0866] Input: Request data

[0867] Output: The request data sent to the server

[0868] Operation: The terminal captures the click event of the send button and sends this request data to the server.

[0869] Step 3:

[0870] The server receives the request data and analyzes the content of the question using a request analysis means.

[0871] Input: Request data

[0872] Output: Parsed question

[0873] How it works: The server analyzes the request data and extracts the question. For example, it analyzes the prompt text to extract information about the protagonist's friends.

[0874] Step 4:

[0875] The server uses a search means to search the database for content data up to the specified position.

[0876] Input: Parsed question content

[0877] Output: Corresponding content data

[0878] Operation: The server queries the database to find and retrieve the relevant content data based on the parsed query.

[0879] Step 5:

[0880] The server uses a filter means to apply a spoiler prevention filter to the acquired data.

[0881] Input: Acquired content data

[0882] Output: Filtered data

[0883] How it works: The server applies a filter algorithm to remove or mask important spoiler information, for example, removing information about the story's ending.

[0884] Step 6:

[0885] The server uses a formatting means to format the filtered data as response data.

[0886] Input: Filtered data

[0887] Output: Formatted response data

[0888] What it does: The server formats the filtered data in a user-friendly format, such as bullet points or concise sentences.

[0889] Step 7:

[0890] The server transmits the formatted response data to the terminal through the transmission means.

[0891] Input: Formatted response data

[0892] Output: Response data sent to the device

[0893] Operation: The server sends the formatted response data to the device.

[0894] Step 8:

[0895] The terminal displays the response data received from the server to the user using a display means.

[0896] Input: Received response data

[0897] Output: Information displayed to the user

[0898] Operation: The device receives the response data and displays it to the user in the application's display interface, allowing the user to efficiently obtain the necessary information while avoiding spoilers.

[0899] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0900] This invention relates to a system that allows users to check the content so far while avoiding spoilers while watching content such as novels or movies. In particular, this system provides information according to the user's emotional state by combining an emotion engine. This system is composed of request analysis means, search means, filter means, formatting means, transmission means, interface means, and display means.

[0901] System Overview

[0902] The basic flow of the system is that the device sends a question from the user to the server as request data, and the server analyzes the question while recognizing the user's emotions. Next, it searches the database for content data up to the specified position and applies a spoiler prevention filter to the search results. The filtered data is then formatted and sent to the device. The user's device receives this response data and displays it.

[0903] Basic processing explanation

[0904] 1. Enter your question and submit your request

[0905] The terminal provides an interface where the user can enter a question. The user enters the question and presses the send button to initiate a request.

[0906] 2. Emotional Recognition

[0907] The device uses an emotion engine to recognize the user's emotions. The recognition method is to identify emotions by analyzing the user's facial expressions, voice, or text input. For example, if the user is confused, the emotion engine will capture that emotion.

[0908] 3. Receiving and parsing the request

[0909] The server receives the request sent from the terminal and analyzes it together with the emotion data recognized by the emotion engine, and extracts the question content using the analysis means.

[0910] 4. Searching for data

[0911] The server uses a search means to search for content data up to a specified position. For example, based on a request such as "Please tell me the synopsis up to page 5," the server retrieves the relevant data from the database.

[0912] 5. Apply a spoiler prevention filter

[0913] The server uses a filter to apply a spoiler prevention filter to the acquired data. Based on the data from the emotion engine, the server adjusts the filter's strictness according to the user's emotional state (e.g., confusion, anxiety, excitement). For example, if the user feels anxious, the filter is strengthened.

[0914] 6. Formatting and sending response data

[0915] The server uses the formatting means to format the filtered data as response data, which is provided in an appropriate format taking into account the user's emotional state. The transmission means then transmits the response data to the terminal.

[0916] 7. Receiving and Displaying Responses

[0917] The terminal receives the response data sent from the server and uses the display means to display the data on a user interface so that the user can check the content. This allows the user to effectively obtain the necessary information while avoiding spoilers.

[0918] Specific examples

[0919] For example, if a user is reading a novel and wants to recall the contents of the first five pages, the following steps would be taken:

[0920] 1. The user enters "Please tell me the synopsis up to page 5" into the device interface and presses the send button.

[0921] 2. The device sends the input question to the server as request data. At the same time, the emotion engine recognizes the user's emotions (e.g., confusion, anxiety).

[0922] 3. The server receives the request and analyzes the question content and emotion data using the request analysis means.

[0923] 4. The server uses a search method to retrieve content up to the specified position from the database.

[0924] 5. The server applies a spoiler prevention filter using a filter means and adjusts the strength of the filter based on the emotion data.

[0925] 6. The server formats the filtered data using the formatting means and generates it as response data.

[0926] 7. The device receives the response data from the server and displays it along with an icon that indicates the emotion using facial expressions and voice. This allows the user to obtain the necessary information in a way that takes their emotions into consideration while avoiding spoilers.

[0927] This system effectively recognizes user emotions and provides optimal information based on those emotions, improving the user experience. Furthermore, the emotion engine algorithm can be continuously improved to achieve even more accurate emotion recognition and filtering, further enhancing user satisfaction and convenience.

[0928] The processing flow will be explained below.

[0929] Step 1:

[0930] The terminal displays an interface that allows the user to enter a question. Specifically, it generates a text input field and displays it on the screen. It also creates a submit button that the user can click. This allows the user to enter a question and prepare it for submission.

[0931] Step 2:

[0932] The user enters a question into the interface and presses the send button. Specifically, the user enters a question that includes page numbers and time codes (e.g., "Please tell me the synopsis up to page 5") and clicks the send button. This action initiates the transmission of the request.

[0933] Step 3:

[0934] The device formats the user's question as request data and sends it to the server. Specifically, it acquires the user's input and sends it to the server's endpoint as an HTTP request. The request data also includes the user's emotional data recognized by the emotion engine.

[0935] Step 4:

[0936] The device uses an emotion engine to recognize the user's emotions. Specifically, it identifies emotions by capturing the user's facial expressions with a camera, recording their voice with a microphone, or analyzing the phrasing of text input. For example, if the user is confused, the emotion engine will recognize the user's emotion as "confused" based on their facial expressions and tone of voice.

[0937] Step 5:

[0938] The server receives and analyzes requests sent from the terminal. Specifically, it analyzes the request data and extracts the user's question (e.g., page number and time code) and emotional data. This allows the server to understand what the user is asking and take into account the user's emotional state.

[0939] Step 6:

[0940] The server uses a search function to search the database for content data up to the specified position. Specifically, the server queries the content database based on the extracted question to obtain the relevant data. For example, it obtains information for "up to page 5."

[0941] Step 7:

[0942] The server applies a spoiler prevention filter to the data obtained using the filtering means. Specifically, the search results are passed through a spoiler prevention algorithm to remove or mask important plot or ending information. Furthermore, based on data from the emotion engine, the strength of the filter is adjusted according to the user's emotional state (e.g., confusion, anxiety, excitement). For example, if the user is feeling anxious, the filter is strengthened.

[0943] Step 8:

[0944] The server uses a formatting means to format the filtered data as response data. Specifically, the server formats the filtered content data into a format that is easy for the user to understand (e.g., text format). This process generates the response data.

[0945] Step 9:

[0946] The server uses a transmission means to send the formatted response data to the terminal. Specifically, the server returns the data to the terminal as an HTTP response. This data is a response to the user's request, and has been filtered.

[0947] Step 10:

[0948] The device receives the response data sent from the server. Specifically, it analyzes the received response data and displays it in a format that corresponds to the user's emotional state. The display also includes emotional icons and simple comments to help the user easily recognize changes in emotions.

[0949] Step 11:

[0950] The terminal displays the received response data on the user interface so that the user can check the content. Specifically, the data is displayed in a display area such as a text box or a pop-up window so that the user can easily understand the content. This allows the user to effectively obtain the necessary information without the risk of spoilers.

[0951] Example 2

[0952] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0953] In conventional content viewing systems, when users want to know specific information, it is difficult to obtain the necessary information while avoiding spoilers. Furthermore, the provision of information that takes into account the user's emotional state is lacking, resulting in a lack of improvement in the user experience. Furthermore, the lack of an appropriate filtering function based on emotions means that unnecessary or inappropriate information is sometimes provided, resulting in a decrease in user satisfaction.

[0954] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0955] In this invention, the server includes a request analysis means, a search means, and a filter means, which enable the server to recognize the user's emotions and provide appropriate information without giving away spoilers.

[0956] The "request analysis means" is a device or method that analyzes the content of the question entered by the user and identifies the information being sought.

[0957] A "search means" is a device or method for searching for relevant information from a database or storage based on a specified range or condition.

[0958] A "filtering means" is a device or method that removes unnecessary parts from acquired information and extracts only appropriate information based on specific conditions.

[0959] A "formation means" is a device or method that prepares the filtered information in a suitable format for presentation to a user.

[0960] The "transmitting means" is a device or method for transmitting the formatted response data to the user's terminal.

[0961] The "interface means" is a device or method for a user to input a question and perform operations or inputs to send a request to a server.

[0962] The "display means" is a device or method for visually displaying the response data received from the server to the user.

[0963] An "emotion engine" is a software or hardware configuration for analyzing a user's facial expressions, voice, or text input to recognize the user's emotional state.

[0964] This invention relates to a system that allows users to check the content so far while avoiding spoilers while watching content such as novels or movies. In particular, the system provides information according to the user's emotional state by combining it with an emotion engine.

[0965] The system consists of the following main components:

[0966] 1. Hardware and Software Description

[0967] Hardware: Devices used by users (smartphones, tablets, PCs, etc.), servers

[0968] Software: emotion engine, request analysis means, search means, filter means, formatting means, transmission means, display means

[0969] 2. Roles of each component

[0970] Emotion Engine

[0971] This software recognizes a user's emotional state. For example, it analyzes the user's facial expressions, voice, and text input to identify emotions such as confusion, anxiety, and excitement.

[0972] Request analysis method

[0973] This is a means for analyzing the content of a question entered by a user and sending it to the server as request data. This means operates when the user enters a question into the interface of the terminal and sends it.

[0974] Search methods

[0975] This is a method of searching a database for information up to a specified position. For example, based on a request such as "Please tell me the synopsis up to page 5," the corresponding information is retrieved from the database. This search method uses a database management system (e.g., MySQL).

[0976] Filtering Method

[0977] This is a method of applying a spoiler prevention filter to the acquired information. The strength of the filter is adjusted based on the user's emotional state, and information is provided that reduces the user's confusion and anxiety.

[0978] shaping means

[0979] This is a means of formatting filtered information as response data. It takes into account the user's emotional state and prepares the data to return information in an appropriate format.

[0980] Transmission method

[0981] This is a means of sending formatted response data to the user's device, allowing the user to check the necessary information on their device.

[0982] Interface Means

[0983] It is a means for providing an interface for users to input questions and send them to the server.

[0984] Display means

[0985] This is a way to display the response data sent from the server to the user, allowing the user to check the necessary information without spoiling the story.

[0986] 3. Examples of concrete examples and prompts

[0987] For example, if a user is reading a novel and wants to recall the contents of the first five pages, the following specific steps are taken:

[0988] 1. The user enters "Please tell me the synopsis up to page 5" into the device interface and presses the send button.

[0989] 2. The device uses an emotion engine to recognize the user's emotional state and sends it to the server as request data.

[0990] 3. The server analyzes the request and retrieves the content data from the database up to the specified location.

[0991] 4. The server applies a spoiler prevention filter to the search results, formats the filtered data, and generates response data.

[0992] 5. The formatted response data is sent to the user's terminal by the sending means and displayed to the user through the display means.

[0993] This allows users to obtain the information they need in a way that takes their emotions into consideration. This system provides appropriate information according to the user's emotional state, improving the user experience.

[0994] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0995] Step 1: Enter and submit your question

[0996] The terminal provides an interface where the user can enter a question. The user enters a question and presses the send button to generate request data. For example, the user might enter "Please tell me the synopsis up to page 5." The request data includes the question entered by the user. This becomes the input to the server.

[0997] Input: User question (e.g. "Please tell me the synopsis up to page 5")

[0998] Output: Request data (including the user question)

[0999] Step 2: Recognize emotions

[1000] The device activates an emotion engine and analyzes the user's facial expressions, voice, and text content to recognize emotions. For example, it uses a camera and microphone to analyze the user's facial expressions and tone of voice to detect confusion. The recognized emotion data is also added to the request data.

[1001] Input: User facial expressions, voice, and text input

[1002] Output: Emotion data (e.g., confusion, anxiety)

[1003] Step 3: Receiving and Parsing the Request

[1004] The server receives the request data sent from the device. Using a request analysis method, it analyzes the user's question and emotional data and determines a specific response. For example, it distinguishes between information such as "I'm looking for a five-page synopsis" and "I'm confused."

[1005] Input: Request data (including user question and sentiment data)

[1006] Output: Analysis results (specific requests and emotional state)

[1007] Step 4: Search for data

[1008] The server uses a search means to search the database for content data up to the specified position. For example, it uses a database management system (e.g., MySQL) to obtain summary information for pages 1 to 5 of a novel.

[1009] Input: Analysis results (specific requirements)

[1010] Output: Search results (content data up to the specified position)

[1011] Step 5: Apply a spoiler-free filter

[1012] The server uses a filtering means to apply a spoiler prevention filter to the retrieved content data, for example, removing information about important plot points or climaxes, and strengthening the filter if the user is confused based on emotion data.

[1013] Input: Search results (content data up to the specified position), emotion data

[1014] Output: filtered data (spoiler prevention applied)

[1015] Step 6: Format and send response data

[1016] The server uses the formatting means to format the filtered data and generate response data. The server formats the response data in a format that takes into account the emotional state and transmits the formatted data to the terminal through the transmission means. For example, the server formats the data in a simple and easy-to-understand format for a confused user.

[1017] Input: Filtered data (spoiler prevention applied)

[1018] Output: Response data (formatted)

[1019] Step 7: Receive and display the response

[1020] The terminal receives the response data sent from the server. Using the display means, the terminal displays the response data on a user interface so that the user can confirm the contents. For example, up to five pages of summary information and additional messages to clear up confusion are displayed on the terminal screen.

[1021] Input: Response data (formatted)

[1022] Output: Displayed information (formatted response data)

[1023] (Application example 2)

[1024] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1025] In conventional content viewing systems, when a user wants to review the content or ask a specific question, there is no well-established means for obtaining appropriate information while avoiding spoilers. Furthermore, because information cannot be provided according to the user's emotional state, users often encounter unnecessary spoilers. This invention proposes a system that efficiently provides only the information necessary for the user while taking into account the user's emotions.

[1026] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1027] In this invention, the server includes request analysis means, search means for searching for content data up to a specified position, filter means for applying a spoiler prevention filter to the search results, formatting means for formatting the filtered data as response data, transmission means for transmitting the response data, emotion recognition means for recognizing the emotional state of the user, and adjustment means for adjusting the strictness of the filtering means based on the emotion recognition data. This allows the user to obtain the information they need in a form appropriate to their own emotional state while preventing spoilers.

[1028] The "request analysis means" refers to a device or program that analyzes the content of questions and request data sent by users.

[1029] "Search means" refers to a device or program that searches and retrieves content data up to a specified position from a database or storage.

[1030] "Filtering means" refers to a device or program that applies a filter to search results to prevent spoilers.

[1031] "Forming means" refers to a device or program that formats the filtered data into a format that is easy for the user to understand.

[1032] "Transmission means" refers to a device or program that transmits the formatted response data to the user's terminal.

[1033] "Emotion recognition means" refers to a device or program that uses a camera or microphone to recognize the user's emotional state.

[1034] The "adjustment means" refers to a device or program that adjusts the settings and strictness of the filtering means based on the emotion data obtained by the emotion recognition means.

[1035] "User interface means" refers to a device or program that provides an interface for a user to input a question and send it to the server.

[1036] "Display means" refers to a device or program that visually displays the response data sent from the server to the user.

[1037] "Database" refers to a data structure and management system for storing and searching content data up to a specified position.

[1038] This invention provides a system for content distribution services that allows users to avoid spoilers while checking the content of novels, movies, etc. In particular, by combining it with an emotion recognition function, the system provides information according to the user's emotional state.

[1039] System Configuration

[1040] The system is composed of the following modules: a request parser, a searcher, a filter, a formatter, a sender, an emotion recognizer, and a moderator. It also includes a user interface and a display.

[1041] Hardware and software used

[1042] The hardware used is a smartphone or smart glasses, such as an iPhone, Android device, Google Glass, or Microsoft HoloLens. On the server side, a cloud-based server (e.g., AWS or Google Cloud) is used.

[1043] The software used is Microsoft Azure Emotion API and Google Cloud Vision API for emotion recognition, ElasticSearch and Apache Solr for data search and analysis, and Python-based web frameworks such as Django and Flask for spoiler prevention filters.

[1044] Description of the Examples

[1045] First, the user inputs a question using a smartphone or smart glasses. For example, a user reading a novel might input a question such as, "Tell me the plot up to page 5." Examples of prompts include, "Who appears at the end?" or "Tell me the relationship between these characters."

[1046] The device receives the questions entered by the user and simultaneously recognizes the user's emotions using a camera and microphone. For example, if the device recognizes that the user is confused, it sends that emotional state to the server.

[1047] The server analyzes the received request and searches for the necessary content data based on the emotion data and the question. For example, it retrieves the synopsis information up to the specified position from the database. This is done using a search method.

[1048] The acquired data is processed by a filtering means to prevent spoilers. Based on the emotion recognition data, the strictness of the filter is set by an adjusting means, and the data is filtered in a manner suitable for the user.

[1049] The filtered data is shaped as response data by the shaping means and transmitted to the user terminal via the transmission means. The terminal visually displays the received response data to the user using the display means. This allows the user to obtain the information they need according to their emotions while avoiding spoilers.

[1050] Adding specific examples

[1051] For example, if a user is reading a novel and wants to check the plot up to page 5, they can type "Tell me the plot up to page 5" into their smartphone. At the same time, the emotion recognition means will determine the user's confusion state from the camera footage. The server analyzes this request, searches the database for the contents up to page 5, and applies a spoiler prevention filter appropriate for a confused user. The filtered results are then formatted and sent to the user's smartphone. They are then displayed on the screen for the user to review. In this way, the user can obtain the necessary information while avoiding spoilers.

[1052] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1053] Step 1:

[1054] The user inputs the question using a smartphone or smart glasses. For example, they might input text such as "Please tell me the plot up to page 5." The input text is temporarily saved on the device.

[1055] Step 2:

[1056] The device's camera and microphone are used to recognize the user's emotions. The emotion recognition method uses the Microsoft Azure Emotion API and Google Cloud Vision API to analyze the user's facial expressions and voice to identify their emotional state (e.g., confusion, anxiety, excitement). The identified emotional data is sent to the server along with the text input data.

[1057] Step 3:

[1058] The server uses its request analysis means to analyze the received user's question and emotional state. This analysis determines what data is needed and how much filtering is required. The analysis results are stored in internal memory.

[1059] Step 4:

[1060] Using the search means, the server searches the database for content data up to a specified position. For example, data corresponding to "a synopsis up to page 5" is extracted from the database. The search results are stored in temporary memory.

[1061] Step 5:

[1062] A filter means is used to apply a spoiler prevention filter to the search results. The strictness of the filter is set by an adjustment means based on emotion recognition data, and filtering is performed to an appropriate degree. For example, if the user is confused, the filter is strengthened. The filtered data is again stored in temporary memory.

[1063] Step 6:

[1064] The filtered data is formatted as response data using a formatting means. The format and representation of the data are optimized based on the user's emotional state. The formatted response data is stored in a transmission buffer of the server.

[1065] Step 7:

[1066] Using the transmission means, the server sends the formatted response data to the user's terminal. The transmission protocol is HTTP or HTTPS. The response data is stored in the terminal's receiving buffer.

[1067] Step 8:

[1068] The device visually displays the received response data to the user using a display means. For example, a "synopsis up to page 5" is displayed on the screen. Icons and explanations corresponding to the recognized emotions are also displayed. This allows the user to obtain the necessary information while avoiding spoilers.

[1069] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1070] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1071] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1072] [Fourth embodiment]

[1073] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1074] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1075] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1076] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1077] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1078] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1079] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1080] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1081] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1082] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1083] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1084] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1085] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1086] This invention relates to a system that allows users to check the ongoing content and character relationships while watching content such as novels or movies. In particular, this system, which can provide information while reducing the risk of spoilers, is composed of request analysis means, search means, filter means, formatting means, and transmission means. Interface means and display means that constitute the user interface are also part of this system.

[1087] System Overview

[1088] The basic flow of the system is that the device accepts a question from the user and sends it to the server. The server analyzes the user's question and searches the database for content data up to the specified position. It then applies a spoiler prevention filter to the search results, formats the filtered data, and sends it to the user's device. Finally, the device displays the response data to the user.

[1089] Basic processing explanation

[1090] 1. Enter your question and submit your request

[1091] The terminal provides an interface where the user can enter a question. The user enters a question about the content up to a specific position through the interface and clicks the submit button. The terminal receives the user's input and sends it to the server as a request.

[1092] 2. Receiving and parsing the request

[1093] The server receives the request sent from the terminal, and uses the request analysis means to analyze the request data sent by the user and extract the question content.

[1094] 3. Searching for data

[1095] The server uses a search function to search the database for content data up to the specified position. For example, if a user inputs "Please tell me the synopsis up to page 5," the server retrieves the relevant data corresponding to this request.

[1096] 4. Apply a spoiler prevention filter

[1097] The server applies a spoiler prevention filter to the obtained data using a filtering means, which removes or masks information about important elements of the story or the ending.

[1098] 5. Formatting and sending response data

[1099] The server uses the formatting means to format the filtered data into a format that is easy for the user to understand, and transmits the formatted response data to the terminal via the transmission means.

[1100] 6. Receiving and Displaying Responses

[1101] The terminal receives the response data sent from the server and displays the response content to the user using a display unit, allowing the user to obtain the necessary information while avoiding the risk of spoilers.

[1102] Specific examples

[1103] For example, if a user is reading a novel and wants to recall the contents of the first five pages, the following steps would be taken:

[1104] 1. The user enters "Please tell me the synopsis up to page 5" into the device interface and presses the send button.

[1105] 2. The terminal sends the entered question to the server as request data.

[1106] 3. The server receives the request and analyzes the question using the request analysis means.

[1107] 4. The server uses a search method to retrieve content up to the specified position from the database.

[1108] 5. The server applies a spoiler prevention filter using a filtering method to mask important spoiler information.

[1109] 6. The server formats the filtered data using the formatting means and generates response data.

[1110] 7. The terminal receives the response data from the server and displays it to the user on the display means.

[1111] This allows users to efficiently obtain the information they need while avoiding the risk of spoilers. The system is designed to be user-friendly in terms of both visual and operational aspects, increasing user satisfaction. Furthermore, the spoiler prevention filter algorithm can be continuously improved, further enhancing user convenience.

[1112] The processing flow will be explained below.

[1113] Step 1:

[1114] The terminal displays an interface that allows the user to enter a question. Specifically, it generates a text input field and displays it on the screen. It also creates a submit button that the user can click. With this interface displayed, the user is ready to enter a question.

[1115] Step 2:

[1116] The user enters a question into the interface and presses the send button. Specifically, the user enters a question that includes page numbers and time codes (e.g., "Please tell me the synopsis up to page 5") and clicks the send button. This action initiates the transmission of the request.

[1117] Step 3:

[1118] The device formats the user's question as request data and sends it to the server. Specifically, it obtains the user's input and sends it to the server's endpoint as an HTTP request. Once the transmission is complete, the request data is passed to the server.

[1119] Step 4:

[1120] The server receives and analyzes the request sent from the terminal. Specifically, it analyzes the request data and extracts the user's question (for example, page number or time code). This allows the server to understand what the user is looking for.

[1121] Step 5:

[1122] The server uses a search function to search the database for content data up to the specified position. Specifically, based on the extracted question, the server queries the content database to obtain the relevant data. For example, it obtains information for "up to page 5."

[1123] Step 6:

[1124] The server applies a spoiler prevention filter to the data obtained using the filtering means. Specifically, the search results are passed through a spoiler prevention algorithm to remove or mask important plot or ending information. The filtered data has a low risk of spoilers.

[1125] Step 7:

[1126] The server uses a formatting means to format the filtered data as response data. Specifically, the server formats the filtered content data into a format that is easy for the user to understand (e.g., text format). This process generates the response data.

[1127] Step 8:

[1128] The server uses a transmission means to send the formatted response data to the terminal. Specifically, it returns the data to the terminal as an HTTP response. This data is a response to the user's request, and filtering has been completed.

[1129] Step 9:

[1130] The terminal receives the response sent from the server and displays it on the user interface. Specifically, the terminal displays the received response data in a display area such as a text box so that the user can check the content. This allows the user to obtain the necessary information without risking spoilers.

[1131] Example 1

[1132] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1133] In the past, when users wanted to check the content or the relationships between characters while watching content, the method of presenting information carried the risk of spoilers, which posed a problem. Therefore, there is a demand for a system that can safely and efficiently obtain the necessary information.

[1134] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1135] In this invention, the server includes a request analysis means for analyzing the content of a question entered by a user, a search means for searching a database for content data up to a specified position, a filter means for applying a spoiler prevention filter to the search results, a formatting means for formatting the filtered data into a format that is easy for the user to understand, and a transmission means for transmitting the formatted response data. This makes it possible to provide a system that allows users to safely and efficiently obtain the information they need while reducing the risk of spoilers.

[1136] The "request analysis means" is a device or program for analyzing the content of a question entered by a user.

[1137] The "search means" is a device or program for searching the database for content data up to a specified position.

[1138] "Filtering Measures" means devices or programs that apply anti-spoiler filters to search results to remove or mask information about important elements or the ending.

[1139] The "shaping means" is a device or program for converting the filtered data into a format that is easy for the user to understand.

[1140] The "transmission means" refers to a device or program for transmitting the formatted response data to the user terminal.

[1141] The "interface means" refers to a device or program that allows a user to input a question and transmit the question data to the server.

[1142] The "display means" is a device or program for receiving response data sent from the server and displaying it to the user.

[1143] A "database" is a system or platform for storing and retrieving content data up to a specified location.

[1144] This invention relates to a system that allows users to check the ongoing content and character relationships while watching content such as novels or movies. In particular, it is possible to provide information while reducing the risk of spoilers. This system is composed of request analysis means, search means, filter means, formatting means, and transmission means. Interface means and display means that constitute the user interface are also part of this system.

[1145] System Operation Overview

[1146] The terminal provides an interface that allows the user to input a question and sends the question to the server. The server analyzes the user's question and searches the database for content data up to the specified position. It applies a spoiler prevention filter to the search results, formats the filtered data, and sends it to the user's terminal. Finally, the terminal displays the response data to the user.

[1147] Hardware and software used

[1148] 1. Terminal

[1149] Hardware: Smartphones, tablets, PCs

[1150] Software: Web browser, mobile application

[1151] 2. Server

[1152] Hardware: Cloud server, dedicated server

[1153] Software: Web servers, database management systems (e.g., MySQL, PostgreSQL), natural language processing (NLP) libraries (e.g., spaCy, NLTK), machine learning models (e.g., BERT model, GPT-3)

[1154] Specific examples

[1155] Example 1: Checking the contents of a novel

[1156] The user types in "Please tell me the synopsis up to page 5" and clicks the submit button.

[1157] The terminal transmits the input question to the server as request data.

[1158] The server receives the request and extracts the keywords "up to page 5" and "summary" using a request analysis means.

[1159] The server uses a search tool to retrieve up to five pages of content from the database.

[1160] The server applies a spoiler prevention filter using a filtering means to mask important spoiler information.

[1161] The server formats the filtered data using the formatting means and generates response data.

[1162] The terminal receives the response data from the server and displays it to the user on the display means.

[1163] Prompt Sentence Examples

[1164] "Please give me a summary of the first five pages of your novel, but please avoid spoilers."

[1165] "Please tell me the plot of the movie up to the 30th minute, but please mask any important spoilers."

[1166] This allows users to efficiently obtain the necessary information without spoilers.

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

[1168] Step 1:

[1169] The terminal provides an interface that allows the user to input a question. The user inputs the question through this interface and clicks the submit button. For example, input data can be text such as "Please tell me the plot up to page 5." The input text data is captured by front-end technology such as JavaScript and sent to the server as an HTTP request. As output, an HTTP request message is generated.

[1170] Step 2:

[1171] The server receives an HTTP request sent from a terminal. The input is an HTTP request message, which contains the user's question. The request analysis means on the server analyzes this request message and extracts text data. Specifically, an NLP library (such as spaCy or NLTK) is used to analyze the part used as a query. The analysis results of the question are output as the specified page range and keywords.

[1172] Step 3:

[1173] The server uses a search tool to search the database for content data up to a specified position. The input is analyzed text data, which is sent to the database as an SQL query. For example, if the query is "contents up to page 5," data corresponding to the page range in question is retrieved from the database. The original text data is output as the search result.

[1174] Step 4:

[1175] The server applies a spoiler prevention filter to the textual data of the search results using a filter method. The input is the textual data retrieved from the database, and the filter method uses a machine learning model (e.g., BERT model or GPT-3) to identify and remove or mask important elements or information about the ending. The output is the filtered, safe data.

[1176] Step 5:

[1177] The server uses a formatting method to format the filtered data into a format that is easy for the user to understand. The input is the filtered data, which is converted into a visually easy-to-understand format using Markdown or HTML. Specifically, the content is organized using bullet points or paragraphs. The formatted response data is generated as the output.

[1178] Step 6:

[1179] The server transmits the formatted response data to the terminal via the transmission means. The input is the formatted response data, which is transmitted to the terminal as an HTTP response. The output is an HTTP response message.

[1180] Step 7:

[1181] The terminal receives an HTTP response sent from the server. The input is an HTTP response message, and the display means analyzes this response data and displays it to the user. Specifically, the received data is displayed as text on the screen. The output is generated as text to be displayed on the terminal screen.

[1182] (Application example 1)

[1183] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1184] While watching content, it is difficult for users to obtain necessary information about the ongoing content or the relationships between characters while avoiding spoilers. This has led to a growing demand for a system that allows users to obtain information efficiently without losing their enjoyment of the content. A system that can solve this problem is needed.

[1185] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1186] In this invention, the server includes a request analysis means, a search means for searching for content data up to a specified position, a filter means for applying a spoiler prevention filter to the search results, a formatting means for formatting the filtered data as response data, a transmission means for transmitting the response data, an interface means for inputting a question in natural language and transmitting it to the server, and a display means for receiving and displaying the response data transmitted from the server, and an application executable on a smart device. This allows the user to efficiently obtain information such as checking the ongoing content and understanding the relationships between characters while avoiding spoilers.

[1187] The "request analysis means" is a function for analyzing the request data sent by the user and extracting the question content.

[1188] The "search means" is a function for searching the database for content data up to a specified position.

[1189] "Filtering means" is a function that applies a spoiler prevention filter to search results to remove or mask important spoiler information.

[1190] The "formatting means" is a function for formatting the filtered data into a format that is easy for the user to understand.

[1191] The "transmission means" is a function for transmitting the formatted response data to the user terminal.

[1192] The "interface means" is a function that allows the user to input questions in natural language and send them to the server.

[1193] The "display means" is a function for receiving response data sent from the server and displaying it to the user.

[1194] An "application that can be executed on a smart device" is software that runs on a device such as a smartphone or tablet, and is an application that processes input from a user and responses from a server.

[1195] To implement this invention, a user uses a "content helper" application that runs on a smart device such as a smartphone or tablet. This application allows the user to ask questions in natural language about the ongoing content and relationships between characters while watching content such as a movie or novel.

[1196] Specifically, when a user inputs a question into the application, the data is sent to the server via the interface means of the smart device. On the server side, the question is analyzed using a request analysis means, and content data up to the specified position is searched for in a database using a search means. A spoiler prevention filter is then applied to the search results using a filter means. The filtered data is then formatted by a formatting means into a format that is easy for the user to understand, and is finally sent to the smart device via a transmission means. The smart device receives this data and displays it to the user via a display means.

[1197] The hardware used is a smart device such as a smartphone or tablet, and the software is a server application using Flask, and Requests is used for data communication. Any web framework (e.g., Django, Flask) can be used on the server side.

[1198] Examples:

[1199] For example, if a user is reading a novel and wants to check the relationships between characters, the system works as follows:

[1200] 1. The user enters "Who is the protagonist's friend?" in the "Content Helper" application on their smart device and presses the submit button.

[1201] 2. The smart device sends the question to the server via the interface means.

[1202] 3. On the server side, the request analysis means analyzes the content of the question, and the search means retrieves related content data from the database.

[1203] 4. Apply a spoiler prevention filter to the acquired data using a filtering method to remove important spoiler information.

[1204] 5. The filtered data is formatted by the formatting means into a format that is easy for the user to understand.

[1205] 6. The formatted data is sent to the smart device via the transmission means and displayed to the user via the display means.

[1206] This allows the user to efficiently obtain the necessary information while avoiding spoilers.

[1207] Example prompt sentence:

[1208] "If I want to investigate character relationships, generate Python code for a system that parses the question, provides relevant information, and applies a spoiler prevention filter."

[1209] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1210] Step 1:

[1211] The user enters a question into the "Content Helper" application on their smart device and presses the send button.

[1212] Input: Question (e.g., "Who is the protagonist's friend?")

[1213] Output: Request data including the question

[1214] How it works: The user enters a question in natural language into the application's interface and presses the submit button to generate the request data and proceed to the next step.

[1215] Step 2:

[1216] The terminal transmits the generated request data to the server through the interface means.

[1217] Input: Request data

[1218] Output: The request data sent to the server

[1219] Operation: The terminal captures the click event of the send button and sends this request data to the server.

[1220] Step 3:

[1221] The server receives the request data and analyzes the content of the question using a request analysis means.

[1222] Input: Request data

[1223] Output: Parsed question

[1224] How it works: The server analyzes the request data and extracts the question. For example, it analyzes the prompt text to extract information about the protagonist's friends.

[1225] Step 4:

[1226] The server uses a search means to search the database for content data up to the specified position.

[1227] Input: Parsed question content

[1228] Output: Corresponding content data

[1229] Operation: The server queries the database to find and retrieve the relevant content data based on the parsed query.

[1230] Step 5:

[1231] The server uses a filter means to apply a spoiler prevention filter to the acquired data.

[1232] Input: Acquired content data

[1233] Output: Filtered data

[1234] How it works: The server applies a filter algorithm to remove or mask important spoiler information, for example, removing information about the story's ending.

[1235] Step 6:

[1236] The server uses a formatting means to format the filtered data as response data.

[1237] Input: Filtered data

[1238] Output: Formatted response data

[1239] What it does: The server formats the filtered data in a user-friendly format, such as bullet points or concise sentences.

[1240] Step 7:

[1241] The server transmits the formatted response data to the terminal through the transmission means.

[1242] Input: Formatted response data

[1243] Output: Response data sent to the device

[1244] Operation: The server sends the formatted response data to the device.

[1245] Step 8:

[1246] The terminal displays the response data received from the server to the user using a display means.

[1247] Input: Received response data

[1248] Output: Information displayed to the user

[1249] Operation: The device receives the response data and displays it to the user in the application's display interface, allowing the user to efficiently obtain the necessary information while avoiding spoilers.

[1250] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1251] This invention relates to a system that allows users to check the content so far while avoiding spoilers while watching content such as novels or movies. In particular, this system provides information according to the user's emotional state by combining an emotion engine. This system is composed of request analysis means, search means, filter means, formatting means, transmission means, interface means, and display means.

[1252] System Overview

[1253] The basic flow of the system is that the device sends a question from the user to the server as request data, and the server analyzes the question while recognizing the user's emotions. Next, it searches the database for content data up to the specified position and applies a spoiler prevention filter to the search results. The filtered data is then formatted and sent to the device. The user's device receives this response data and displays it.

[1254] Basic processing explanation

[1255] 1. Enter your question and submit your request

[1256] The terminal provides an interface where the user can enter a question. The user enters the question and presses the send button to initiate a request.

[1257] 2. Emotional Recognition

[1258] The device uses an emotion engine to recognize the user's emotions. The recognition method is to identify emotions by analyzing the user's facial expressions, voice, or text input. For example, if the user is confused, the emotion engine will capture that emotion.

[1259] 3. Receiving and parsing the request

[1260] The server receives the request sent from the terminal and analyzes it together with the emotion data recognized by the emotion engine, and extracts the question content using the analysis means.

[1261] 4. Searching for data

[1262] The server uses a search means to search for content data up to a specified position. For example, based on a request such as "Please tell me the synopsis up to page 5," the server retrieves the relevant data from the database.

[1263] 5. Apply a spoiler prevention filter

[1264] The server uses a filter to apply a spoiler prevention filter to the acquired data. Based on the data from the emotion engine, the server adjusts the filter's strictness according to the user's emotional state (e.g., confusion, anxiety, excitement). For example, if the user feels anxious, the filter is strengthened.

[1265] 6. Formatting and sending response data

[1266] The server uses the formatting means to format the filtered data as response data, which is provided in an appropriate format taking into account the user's emotional state. The transmission means then transmits the response data to the terminal.

[1267] 7. Receiving and Displaying Responses

[1268] The terminal receives the response data sent from the server and uses the display means to display the data on a user interface so that the user can check the content. This allows the user to effectively obtain the necessary information while avoiding spoilers.

[1269] Specific examples

[1270] For example, if a user is reading a novel and wants to recall the contents of the first five pages, the following steps would be taken:

[1271] 1. The user enters "Please tell me the synopsis up to page 5" into the device interface and presses the send button.

[1272] 2. The device sends the input question to the server as request data. At the same time, the emotion engine recognizes the user's emotions (e.g., confusion, anxiety).

[1273] 3. The server receives the request and analyzes the question content and emotion data using the request analysis means.

[1274] 4. The server uses a search method to retrieve content up to the specified position from the database.

[1275] 5. The server applies a spoiler prevention filter using a filter means and adjusts the strength of the filter based on the emotion data.

[1276] 6. The server formats the filtered data using the formatting means and generates it as response data.

[1277] 7. The device receives the response data from the server and displays it along with an icon that indicates the emotion using facial expressions and voice. This allows the user to obtain the necessary information in a way that takes their emotions into consideration while avoiding spoilers.

[1278] This system effectively recognizes user emotions and provides optimal information based on those emotions, improving the user experience. Furthermore, the emotion engine algorithm can be continuously improved to achieve even more accurate emotion recognition and filtering, further enhancing user satisfaction and convenience.

[1279] The processing flow will be explained below.

[1280] Step 1:

[1281] The terminal displays an interface that allows the user to enter a question. Specifically, it generates a text input field and displays it on the screen. It also creates a submit button that the user can click. This allows the user to enter a question and prepare it for submission.

[1282] Step 2:

[1283] The user enters a question into the interface and presses the send button. Specifically, the user enters a question that includes page numbers and time codes (e.g., "Please tell me the synopsis up to page 5") and clicks the send button. This action initiates the transmission of the request.

[1284] Step 3:

[1285] The device formats the user's question as request data and sends it to the server. Specifically, it acquires the user's input and sends it to the server's endpoint as an HTTP request. The request data also includes the user's emotional data recognized by the emotion engine.

[1286] Step 4:

[1287] The device uses an emotion engine to recognize the user's emotions. Specifically, it identifies emotions by capturing the user's facial expressions with a camera, recording their voice with a microphone, or analyzing the phrasing of text input. For example, if the user is confused, the emotion engine will recognize the user's emotion as "confused" based on their facial expressions and tone of voice.

[1288] Step 5:

[1289] The server receives and analyzes requests sent from the terminal. Specifically, it analyzes the request data and extracts the user's question (e.g., page number and time code) and emotional data. This allows the server to understand what the user is asking and take into account the user's emotional state.

[1290] Step 6:

[1291] The server uses a search function to search the database for content data up to the specified position. Specifically, the server queries the content database based on the extracted question to obtain the relevant data. For example, it obtains information for "up to page 5."

[1292] Step 7:

[1293] The server applies a spoiler prevention filter to the data obtained using the filtering means. Specifically, the search results are passed through a spoiler prevention algorithm to remove or mask important plot or ending information. Furthermore, based on data from the emotion engine, the strength of the filter is adjusted according to the user's emotional state (e.g., confusion, anxiety, excitement). For example, if the user is feeling anxious, the filter is strengthened.

[1294] Step 8:

[1295] The server uses a formatting means to format the filtered data as response data. Specifically, the server formats the filtered content data into a format that is easy for the user to understand (e.g., text format). This process generates the response data.

[1296] Step 9:

[1297] The server uses a transmission means to send the formatted response data to the terminal. Specifically, the server returns the data to the terminal as an HTTP response. This data is a response to the user's request, and has been filtered.

[1298] Step 10:

[1299] The device receives the response data sent from the server. Specifically, it analyzes the received response data and displays it in a format that corresponds to the user's emotional state. The display also includes emotional icons and simple comments to help the user easily recognize changes in emotions.

[1300] Step 11:

[1301] The terminal displays the received response data on the user interface so that the user can check the content. Specifically, the data is displayed in a display area such as a text box or a pop-up window so that the user can easily understand the content. This allows the user to effectively obtain the necessary information without the risk of spoilers.

[1302] Example 2

[1303] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1304] In conventional content viewing systems, when users want to know specific information, it is difficult to obtain the necessary information while avoiding spoilers. Furthermore, the provision of information that takes into account the user's emotional state is lacking, resulting in a lack of improvement in the user experience. Furthermore, the lack of an appropriate filtering function based on emotions means that unnecessary or inappropriate information is sometimes provided, resulting in a decrease in user satisfaction.

[1305] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1306] In this invention, the server includes a request analysis means, a search means, and a filter means, which enable the server to recognize the user's emotions and provide appropriate information without giving away spoilers.

[1307] The "request analysis means" is a device or method that analyzes the content of the question entered by the user and identifies the information being sought.

[1308] A "search means" is a device or method for searching for relevant information from a database or storage based on a specified range or condition.

[1309] A "filtering means" is a device or method that removes unnecessary parts from acquired information and extracts only appropriate information based on specific conditions.

[1310] A "formation means" is a device or method that prepares the filtered information in a suitable format for presentation to a user.

[1311] The "transmitting means" is a device or method for transmitting the formatted response data to the user's terminal.

[1312] The "interface means" is a device or method for a user to input a question and perform operations or inputs to send a request to a server.

[1313] The "display means" is a device or method for visually displaying the response data received from the server to the user.

[1314] An "emotion engine" is a software or hardware configuration for analyzing a user's facial expressions, voice, or text input to recognize the user's emotional state.

[1315] This invention relates to a system that allows users to check the content so far while avoiding spoilers while watching content such as novels or movies. In particular, the system provides information according to the user's emotional state by combining it with an emotion engine.

[1316] The system consists of the following main components:

[1317] 1. Hardware and Software Description

[1318] Hardware: Devices used by users (smartphones, tablets, PCs, etc.), servers

[1319] Software: emotion engine, request analysis means, search means, filter means, formatting means, transmission means, display means

[1320] 2. Roles of each component

[1321] Emotion Engine

[1322] This software recognizes a user's emotional state. For example, it analyzes the user's facial expressions, voice, and text input to identify emotions such as confusion, anxiety, and excitement.

[1323] Request analysis method

[1324] This is a means for analyzing the content of a question entered by a user and sending it to the server as request data. This means operates when the user enters a question into the interface of the terminal and sends it.

[1325] Search methods

[1326] This is a method of searching a database for information up to a specified position. For example, based on a request such as "Please tell me the synopsis up to page 5," the corresponding information is retrieved from the database. This search method uses a database management system (e.g., MySQL).

[1327] Filtering Method

[1328] This is a method of applying a spoiler prevention filter to the acquired information. The strength of the filter is adjusted based on the user's emotional state, and information is provided that reduces the user's confusion and anxiety.

[1329] shaping means

[1330] This is a means of formatting filtered information as response data. It takes into account the user's emotional state and prepares the data to return information in an appropriate format.

[1331] Transmission method

[1332] This is a means of sending formatted response data to the user's device, allowing the user to check the necessary information on their device.

[1333] Interface Means

[1334] It is a means for providing an interface for users to input questions and send them to the server.

[1335] Display means

[1336] This is a way to display the response data sent from the server to the user, allowing the user to check the necessary information without spoiling the story.

[1337] 3. Examples of concrete examples and prompts

[1338] For example, if a user is reading a novel and wants to recall the contents of the first five pages, the following specific steps are taken:

[1339] 1. The user enters "Please tell me the synopsis up to page 5" into the device interface and presses the send button.

[1340] 2. The device uses an emotion engine to recognize the user's emotional state and sends it to the server as request data.

[1341] 3. The server analyzes the request and retrieves the content data from the database up to the specified location.

[1342] 4. The server applies a spoiler prevention filter to the search results, formats the filtered data, and generates response data.

[1343] 5. The formatted response data is sent to the user's terminal by the sending means and displayed to the user through the display means.

[1344] This allows users to obtain the information they need in a way that takes their emotions into consideration. This system provides appropriate information according to the user's emotional state, improving the user experience.

[1345] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1346] Step 1: Enter and submit your question

[1347] The terminal provides an interface where the user can enter a question. The user enters a question and presses the send button to generate request data. For example, the user might enter "Please tell me the synopsis up to page 5." The request data includes the question entered by the user. This becomes the input to the server.

[1348] Input: User question (e.g. "Please tell me the synopsis up to page 5")

[1349] Output: Request data (including the user question)

[1350] Step 2: Recognize emotions

[1351] The device activates an emotion engine and analyzes the user's facial expressions, voice, and text content to recognize emotions. For example, the device uses a camera and microphone to analyze the user's facial expressions and tone of voice to detect confusion. The recognized emotion data is also added to the request data.

[1352] Input: User facial expressions, voice, and text input

[1353] Output: Emotion data (e.g., confusion, anxiety)

[1354] Step 3: Receiving and Parsing the Request

[1355] The server receives the request data sent from the device. Using a request analysis method, it analyzes the user's question and emotional data and determines a specific response. For example, it distinguishes between information such as "I'm looking for a five-page synopsis" and "I'm confused."

[1356] Input: Request data (including user question and sentiment data)

[1357] Output: Analysis results (specific requests and emotional state)

[1358] Step 4: Search for data

[1359] The server uses a search means to search the database for content data up to the specified position. For example, it uses a database management system (e.g., MySQL) to obtain summary information for pages 1 to 5 of the novel.

[1360] Input: Analysis results (specific requirements)

[1361] Output: Search results (content data up to the specified position)

[1362] Step 5: Apply a spoiler-free filter

[1363] The server applies a spoiler prevention filter to the retrieved content data using a filtering means, for example, removing information about important plot points or climaxes, and strengthening the filter if the user is confused based on emotion data.

[1364] Input: Search results (content data up to the specified position), emotion data

[1365] Output: filtered data (spoiler prevention applied)

[1366] Step 6: Format and send response data

[1367] The server uses the formatting means to format the filtered data and generate response data. The server formats the response data in a format that takes into account the emotional state and transmits the formatted data to the terminal through the transmission means. For example, the server formats the data in a simple and easy-to-understand format for a confused user.

[1368] Input: Filtered data (spoiler prevention applied)

[1369] Output: Response data (formatted)

[1370] Step 7: Receive and display the response

[1371] The terminal receives the response data sent from the server. Using the display means, the terminal displays the response data on a user interface so that the user can confirm the contents. For example, up to five pages of summary information and additional messages to clear up confusion are displayed on the terminal screen.

[1372] Input: Response data (formatted)

[1373] Output: Displayed information (formatted response data)

[1374] (Application example 2)

[1375] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1376] In conventional content viewing systems, when a user wants to review the content or ask a specific question, there is no well-established means for obtaining appropriate information while avoiding spoilers. Furthermore, because information cannot be provided according to the user's emotional state, users often encounter unnecessary spoilers. This invention proposes a system that efficiently provides only the information necessary for the user while taking into account the user's emotions.

[1377] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1378] In this invention, the server includes request analysis means, search means for searching for content data up to a specified position, filter means for applying a spoiler prevention filter to the search results, formatting means for formatting the filtered data as response data, transmission means for transmitting the response data, emotion recognition means for recognizing the emotional state of the user, and adjustment means for adjusting the strictness of the filtering means based on the emotion recognition data. This allows the user to obtain the information they need in a form appropriate to their own emotional state while preventing spoilers.

[1379] The "request analysis means" refers to a device or program that analyzes the content of questions and request data sent by users.

[1380] "Search means" refers to a device or program that searches and retrieves content data up to a specified position from a database or storage.

[1381] "Filtering means" refers to a device or program that applies a filter to search results to prevent spoilers.

[1382] "Forming means" refers to a device or program that formats the filtered data into a format that is easy for the user to understand.

[1383] "Transmission means" refers to a device or program that transmits the formatted response data to the user's terminal.

[1384] "Emotion recognition means" refers to a device or program that uses a camera or microphone to recognize the user's emotional state.

[1385] The "adjustment means" refers to a device or program that adjusts the settings and strictness of the filtering means based on the emotion data obtained by the emotion recognition means.

[1386] "User interface means" refers to a device or program that provides an interface for a user to input a question and send it to the server.

[1387] "Display means" refers to a device or program that visually displays the response data sent from the server to the user.

[1388] "Database" refers to a data structure and management system for storing and searching content data up to a specified position.

[1389] This invention provides a system for content distribution services that allows users to avoid spoilers while checking the content of novels, movies, etc. In particular, by combining it with an emotion recognition function, the system provides information according to the user's emotional state.

[1390] System Configuration

[1391] The system is composed of the following modules: a request parser, a searcher, a filter, a formatter, a sender, an emotion recognizer, and a moderator. It also includes a user interface and a display.

[1392] Hardware and software used

[1393] The hardware used is a smartphone or smart glasses, such as an iPhone, Android device, Google Glass, or Microsoft HoloLens. On the server side, a cloud-based server (e.g., AWS or Google Cloud) is used.

[1394] The software used is Microsoft Azure Emotion API and Google Cloud Vision API for emotion recognition, ElasticSearch and Apache Solr for data search and analysis, and Python-based web frameworks such as Django and Flask for spoiler prevention filters.

[1395] Description of the Examples

[1396] First, the user inputs a question using a smartphone or smart glasses. For example, a user reading a novel might input a question such as, "Tell me the plot up to page 5." Examples of prompts include, "Who appears at the end?" or "Tell me the relationship between these characters."

[1397] The device receives the questions entered by the user and simultaneously recognizes the user's emotions using a camera and microphone. For example, if the device recognizes that the user is confused, it sends that emotional state to the server.

[1398] The server analyzes the received request and searches for the necessary content data based on the emotion data and the question. For example, it retrieves the synopsis information up to the specified position from the database. This is done using a search method.

[1399] The acquired data is processed by a filtering means to prevent spoilers. Based on the emotion recognition data, the strictness of the filter is set by an adjusting means, and the data is filtered in a manner suitable for the user.

[1400] The filtered data is shaped as response data by the shaping means and transmitted to the user terminal via the transmission means. The terminal visually displays the received response data to the user using the display means. This allows the user to obtain the information they need according to their emotions while avoiding spoilers.

[1401] Adding specific examples

[1402] For example, if a user is reading a novel and wants to check the plot up to page 5, they can type "Tell me the plot up to page 5" into their smartphone. At the same time, the emotion recognition means will determine the user's confusion state from the camera footage. The server analyzes this request, searches the database for the contents up to page 5, and applies a spoiler prevention filter appropriate for a confused user. The filtered results are then formatted and sent to the user's smartphone. They are then displayed on the screen for the user to review. In this way, the user can obtain the necessary information while avoiding spoilers.

[1403] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1404] Step 1:

[1405] The user inputs the question using a smartphone or smart glasses. For example, they might input text such as "Please tell me the plot up to page 5." The input text is temporarily saved on the device.

[1406] Step 2:

[1407] The device's camera and microphone are used to recognize the user's emotions. The emotion recognition method uses the Microsoft Azure Emotion API and Google Cloud Vision API to analyze the user's facial expressions and voice to identify their emotional state (e.g., confusion, anxiety, excitement). The identified emotional data is sent to the server along with the text input data.

[1408] Step 3:

[1409] The server uses its request analysis means to analyze the received user's question and emotional state. This analysis determines what data is needed and how much filtering is required. The analysis results are stored in internal memory.

[1410] Step 4:

[1411] Using the search means, the server searches the database for content data up to a specified position. For example, data corresponding to "a synopsis up to page 5" is extracted from the database. The search results are stored in temporary memory.

[1412] Step 5:

[1413] A filter means is used to apply a spoiler prevention filter to the search results. The strictness of the filter is set by an adjustment means based on emotion recognition data, and filtering is performed to an appropriate degree. For example, if the user is confused, the filter is strengthened. The filtered data is again stored in temporary memory.

[1414] Step 6:

[1415] The filtered data is formatted as response data using a formatting means. The format and representation of the data are optimized based on the user's emotional state. The formatted response data is stored in a transmission buffer of the server.

[1416] Step 7:

[1417] Using the transmission means, the server sends the formatted response data to the user's terminal. The transmission protocol is HTTP or HTTPS. The response data is stored in the terminal's receiving buffer.

[1418] Step 8:

[1419] The device visually displays the received response data to the user using a display means. For example, a "synopsis up to page 5" is displayed on the screen. Icons and explanations corresponding to the recognized emotions are also displayed. This allows the user to obtain the necessary information while avoiding spoilers.

[1420] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1421] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1422] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1423] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1424] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1425] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1426] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1427] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1428] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1429] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1430] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1431] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1432] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1433] 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.

[1434] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1435] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1436] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1437] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1438] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1439] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1440] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1441] The following is further disclosed regarding the above embodiment.

[1442] (Claim 1)

[1443] A request analysis means;

[1444] a search means for searching content data up to a specified position;

[1445] a filtering means for applying an anti-spoiler filter to the search results;

[1446] a formatting means for formatting the filtered data as response data;

[1447] a transmitting means for transmitting response data;

[1448] A system including:

[1449] (Claim 2)

[1450] an interface means for acquiring the content of a question input by a user and transmitting it to a server;

[1451] 2. The system according to claim 1, further comprising a display unit for receiving and displaying a response from the server.

[1452] (Claim 3)

[1453] 2. The system according to claim 1, wherein a database is used to acquire content data up to a specified position.

[1454] "Example 1"

[1455] (Claim 1)

[1456] a request analysis means for analyzing the content of a question input by a user;

[1457] a search means for searching a database for content data up to a specified position;

[1458] a filtering means for applying an anti-spoiler filter to the search results;

[1459] a formatting means for formatting the filtered data into a format that is easy for a user to understand;

[1460] a transmitting means for transmitting the formatted response data;

[1461] A system including:

[1462] (Claim 2)

[1463] an interface means for acquiring the content of a question input by a user and transmitting it to a server;

[1464] 2. The system according to claim 1, further comprising a display unit for receiving and displaying a response from the server.

[1465] (Claim 3)

[1466] 2. The system according to claim 1, wherein a database is used to acquire content data up to a specified position.

[1467] "Application Example 1"

[1468] (Claim 1)

[1469] A request analysis means;

[1470] a search means for searching content data up to a specified position;

[1471] a filtering means for applying an anti-spoiler filter to the search results;

[1472] a formatting means for formatting the filtered data as response data;

[1473] a transmitting means for transmitting response data;

[1474] an interface means for inputting a question in natural language and transmitting it to a server;

[1475] an application executable on a smart device using a display means for receiving and displaying response data transmitted from the server;

[1476] A system including:

[1477] (Claim 2)

[1478] 2. The system according to claim 1, further comprising: an interface means for acquiring the content of a question input by a user and transmitting it to the server; and a display means for receiving and displaying a response from the server.

[1479] (Claim 3)

[1480] 2. The system according to claim 1, wherein a database is used to acquire content data up to a specified position.

[1481] "Example 2: Combining Emotion Engines"

[1482] (Claim 1)

[1483] A request analysis means;

[1484] A search means for searching information up to a specified position;

[1485] a filtering means for applying an anti-spoiler filter to the search results;

[1486] a formatting means for formatting the filtered information as response data;

[1487] a transmitting means for transmitting response data;

[1488] means including an emotion engine for recognizing an emotion of a user;

[1489] A system including:

[1490] (Claim 2)

[1491] an interface means for acquiring the content of a question input by a user and transmitting it to a server;

[1492] 2. The system according to claim 1, further comprising a display unit for receiving and displaying a response from the server.

[1493] (Claim 3)

[1494] 2. The system according to claim 1, wherein a database is used to acquire information up to a specified position.

[1495] "Application example 2 when combining emotion engines"

[1496] (Claim 1)

[1497] A request analysis means;

[1498] a search means for searching content data up to a specified position;

[1499] a filtering means for applying an anti-spoiler filter to the search results;

[1500] a formatting means for formatting the filtered data as response data;

[1501] a transmitting means for transmitting response data;

[1502] emotion recognition means for recognizing an emotional state of a user;

[1503] an adjustment means for adjusting the stringency of the filtering means based on the emotion recognition data;

[1504] A system including:

[1505] (Claim 2)

[1506] an interface means for acquiring the content of a question input by a user and transmitting it to a server;

[1507] 2. The system according to claim 1, further comprising a display unit for receiving and displaying a response from the server.

[1508] (Claim 3)

[1509] 2. The system according to claim 1, wherein a database is used to acquire content data up to a specified position. [Explanation of symbols]

[1510] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A request analysis means; a search means for searching content data up to a specified position; a filtering means for applying an anti-spoiler filter to the search results; a formatting means for formatting the filtered data as response data; a transmitting means for transmitting response data; A system including:

2. an interface means for acquiring the content of a question input by a user and transmitting it to a server; 2. The system according to claim 1, further comprising a display means for receiving and displaying a response from the server.

3. 2. The system according to claim 1, wherein a database is used to acquire content data up to a specified position.

Images