System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving input from a user of a news genre and a desired update time period; means for automatically collecting relevant news articles from a plurality of news sources on a network based on the received news genre; means for filtering and ranking the collected news articles; and means for generating and delivering a customized news feed for the desired update time period.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] In modern society, the speed at which information is acquired is fast, and users are increasingly exposed to a large amount of news every day. However, it takes a lot of time to search for the news they need, making it difficult to gather information efficiently. Furthermore, users who are interested in a particular genre lack a means to obtain the latest news and related information in that genre in a timely manner. The present invention aims to solve this problem by enabling users to efficiently obtain the information they need at the appropriate time. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that includes a means for receiving input of news genres and desired update times from a user, a means for automatically collecting related news articles from multiple news sources on a network based on the received news genres, a means for filtering and ranking the collected news articles, and a means for generating and distributing a customized news feed tailored to the desired update time. By using this system, users can efficiently collect the news they need and check it in a timely manner at their desired time.

[0006] "User" refers to the end user who uses this system to set the news genre and update time period.

[0007] "News genre" refers to a specific category of news that a user is interested in. Examples include IT, economics, sports, etc.

[0008] The "update time period" refers to the time period during which the user specifies the desired time for news update and distribution.

[0009] "Means for receiving input" refers to a function for receiving information on news genres and desired update time periods from users.

[0010] A "news source" refers to the information source from which news articles are collected, such as multiple news providers, APIs, and databases publicly available on the network.

[0011] "News Article" refers to an individual piece of news content collected from a news source.

[0012] "Automatic collection means" refers to a function that automatically retrieves relevant news articles from the network based on user settings.

[0013] "Filtering" refers to the process of sorting collected news articles based on specific criteria.

[0014] "Ranking" refers to the process of prioritizing the collected news articles so that the most relevant articles to the user are displayed first.

[0015] "Customized News Feed" refers to a personalized list of news articles generated based on a user's selected news genres and update timeframes.

[0016] The "means for delivering" refers to a function for transmitting the generated news feed to the user's terminal and making the news available for viewing at a specified time. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The present invention provides a system that allows users to set the news genres they are interested in and the update time periods they desire, and provides a news feed that is customized based on that information. Below, an embodiment of this system will be described.

[0039] User Settings

[0040] Users access the system and set their desired news genre and update time. For example, a user can select "IT news" and "economic news" through the application interface and set their preference to receive news at 7:00 a.m. every morning. This setting information is sent to the server.

[0041] Receiving and storing configuration information

[0042] The server receives the news genre and desired update time period sent by the user and stores it in a database, which assigns a unique ID to each user and manages their individual settings.

[0043] News gathering

[0044] When the specified update time arrives, the server collects relevant news from news sources on the network based on the user's settings, for example, by sending an API request to retrieve the latest news articles related to "IT" and "Economy," and stores the news articles in the database.

[0045] News filtering and ranking

[0046] The server filters and ranks the most important articles from the collected news articles based on relevance and recency, a process that results in the most relevant articles being selected for the user.

[0047] Customize and deliver news

[0048] Based on the filtered and ranked news articles, the server generates a customized news feed, which is delivered to the device at the update time specified by the user.

[0049] Viewing news

[0050] The device receives the news feed sent from the server and notifies the user at the set time. When the user opens the app, the customized news feed is displayed. For example, a user can open the app on their way to work and check the latest "IT news" and "economic news."

[0051] Specific examples

[0052] As a concrete example, suppose User A is interested in "sports news" and "entertainment news" and has set up a daily news feed at 6:00 PM. The server saves this setting information and starts collecting relevant news from 5:55 PM. After filtering and ranking, the customized news feed is delivered to User A's device at 6:00 PM. User A can easily check the latest sports and entertainment news on his / her way home.

[0053] The above is an embodiment of the system of the present invention, which enables users to efficiently collect news that matches their interests and check it in a timely manner at an appropriate time.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] When the user installs the application and starts it for the first time, they set the news genre and desired update time. Specifically, they select "IT news" and "Economic news" and want news updates every morning at 7:00. The setting information is entered through the application's user interface and sent to the server.

[0057] Step 2:

[0058] The server receives the setting information sent by the user. The received information includes the user's ID, selected news genre, and desired update time period. The server stores this information in a database. This allows the setting information to be managed uniquely for each user, and the data required for subsequent processing is retained.

[0059] Step 3:

[0060] A few minutes before the specified update time (in this case, 7:00 every morning), the server starts collecting news based on the configuration information. Specifically, it sends API requests to multiple reliable news sources for the selected news genres ("IT" and "Economy"), and retrieves the latest news articles.

[0061] Step 4:

[0062] The server filters the retrieved news articles, taking into account criteria such as the relevance, recency, and reliability of the news articles. For example, inappropriate content and duplicate articles are filtered out, and the most relevant news is selected.

[0063] Step 5:

[0064] The server ranks the filtered news articles. The ranking criteria take into account the importance and timeliness of the article. The more important and latest news are ranked higher and displayed preferentially.

[0065] Step 6:

[0066] The server generates a customized news feed from the filtered and ranked news articles, which is configured to include only news genres selected by the user.

[0067] Step 7:

[0068] At the specified update time (in this case, every morning at 7:00), the server delivers the generated customized news feed to the user's device via push notification, email, in-app notification, or other methods depending on the user's settings.

[0069] Step 8:

[0070] The device receives the news feed sent from the server and arranges for the news feed to be displayed at a time set by the user. For example, an application can automatically display a notification to inform the user that a new news feed has arrived.

[0071] Step 9:

[0072] Users open the application at the specified time and check the delivered news feed. Users can efficiently browse the latest news articles in the genres they are interested in. They can select articles that interest them and read detailed information.

[0073] This series of steps allows users to efficiently collect news that interests them and check it at an appropriate time, significantly reducing the time it takes for users to gather news and providing timely access to important information.

[0074] Example 1

[0075] 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."

[0076] In modern society, people have access to a vast amount of information. However, it is difficult to efficiently collect only the information of interest and review it in a timely manner. Conventional information collection systems lack the technology to provide customized information feeds based on specified information categories and update times. They also have limited functionality for filtering and ranking information items based on relevance and recency. Therefore, there is a need to develop a system that provides users with the most appropriate information at the right time.

[0077] 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.

[0078] In this invention, the server includes means for receiving input of an information category and a desired delivery time period from a user, means for automatically collecting related information items from multiple information sources on a network based on the received information category, means for filtering and ranking the collected information items, and means for generating and delivering a customized information feed tailored to the desired delivery time period, thereby enabling users to efficiently collect information that matches their interests and view it in a timely manner at an appropriate time.

[0079] "User" means a user of the system who intends to receive information based on his or her interests.

[0080] An "information category" is a division of a particular type of information that interests a user, such as a news genre or topic area.

[0081] The "desired delivery time period" is the range of time within which the user can receive information, and a specific time or time period can be specified.

[0082] "Multiple information sources on the network" refers to various sources accessible via the Internet, including news sites, blogs, APIs, etc.

[0083] "Relevant information items" refer to specific news articles or data entries collected based on the information categories received.

[0084] "Automatic collection methods" are mechanisms by which programs automatically obtain information based on user settings, such as using web crawlers or API requests.

[0085] "Filtering" is the process of selecting useful information items from collected information based on specific criteria.

[0086] "Ranking" is the process of prioritizing filtered information items based on relevance and recency.

[0087] A "customized information feed" is a collection of news and data delivered as a personalized stream of information generated according to a user's preferences.

[0088] The "means of delivery" refers to a method for sending the generated information feed to the user's terminal, and includes email, push notification, a dedicated application, and the like.

[0089] The present invention provides a system that allows users to set information categories of interest and desired delivery time periods, and provides a customized information feed based on that information. The following describes an embodiment of this system.

[0090] User Settings

[0091] Users access the system and set the information category and desired delivery time. For example, a user can select "IT news" and "economic news" through the application interface and set the information to be delivered at 7:00 every morning. This setting information is sent to the server.

[0092] Receiving and storing configuration information

[0093] The server receives the information category and desired delivery time slot sent by the user and stores it in a database. Specifically, it uses a database such as MySQL or PostgreSQL to manage user IDs, information categories, and delivery time slots.

[0094] Collection of information

[0095] As the specified delivery time approaches, the server collects relevant information from information sources on the network based on the user's settings. Specifically, it sends API requests to obtain the latest information items related to "IT" and "Economy" and stores the information in a database. The APIs used for this purpose are, for example, NewsAPI and NY Times API.

[0096] Filtering and ranking information

[0097] The server then filters and ranks the collected information items based on their relevance and recency. This process uses a machine learning algorithm based on Python's scikit-learn library. Specifically, it performs text analysis on the information items, calculates a relevance score, and assigns a ranking.

[0098] Personalized information delivery

[0099] Based on the filtered and ranked information items, the server generates a customized information feed in HTML or JSON format, customizing the content for each user, and then sends the generated information feed to the user's device.

[0100] Displaying Information

[0101] The device receives the information feed sent from the server and notifies the user at the set time. For example, the push notification function can be used to display a message saying, "The latest IT and economic news has been updated" at a specified time. When the user clicks on this notification, the app opens and the customized information feed is displayed.

[0102] Specific examples

[0103] As a concrete example, suppose User A is interested in "Sports News" and "Entertainment News" and has set up a schedule to receive information at 6:00 PM. The server saves this setting and starts collecting relevant information from 5:55 PM. After filtering and ranking, a customized information feed is delivered to User A's device at 6:00 PM. User A receives a notification on his / her way home and can open the app to check the latest sports and entertainment news.

[0104] Examples of prompt statements

[0105] An example of a prompt to be input to the generative AI model is as follows:

[0106] Explain how a system that provides a customized information feed works, allowing users to set the information categories they are interested in and the time slots they want delivered. For example, explain in detail how a system works if a user selects "IT news" and "Economic news" and sets the time slots to receive them every morning at 7:00.

[0107] The above is an embodiment of the system of the present invention. This system enables users to efficiently collect information that matches their interests and check it in a timely manner at an appropriate time.

[0108] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0109] Step 1:

[0110] The user opens the application and enters the information category and desired delivery time slot. Specifically, the user selects "IT News" or "Economic News" in the application interface and sets "7:00" as the delivery time slot. Once this setting information has been entered, the user presses the "Set" button to send it to the server. The input here is the information category and delivery time slot data, and the output is data sent to the server.

[0111] Step 2:

[0112] The server receives the information category and desired delivery time setting information sent by the user. It then stores the information in a database such as MySQL or PostgreSQL. Specifically, data including the user ID, information category, and delivery time is stored and managed in the database. The input is the user setting data, and the output is the operation of saving it to the database.

[0113] Step 3:

[0114] As the specified delivery time approaches, the server starts the information collection process. For example, if a user has set their preference to receive news at 7:00 in the morning, the server will send a request to a news API (such as NewsAPI or NY Times API) at 6:55 to collect the latest information on "IT" and "Economy." The collected data is then stored in a database as is. The input is the API request, and the output is the data of the retrieved information items.

[0115] Step 4:

[0116] The server filters and ranks the collected information items. Specifically, it uses the scikit-learn library to perform text analysis, selects articles that are highly relevant to the user's preferences, and calculates an importance score to rank them. This process uses relevance and recency as criteria. The input is the collected information items, and the output is the filtered and ranked information items.

[0117] Step 5:

[0118] Based on the filtered and ranked information items, the server generates a customized information feed. The generated information feed is created in HTML or JSON format and is customized to have different content for each user. Once generated, the information feed is sent to the user's device. The input is the filtered and ranked information items, and the output is the customized information feed.

[0119] Step 6:

[0120] The device receives the information feed sent from the server and notifies the user at the set time. The push notification function is used to notify the user of information updates. When the user clicks on the notification, the app opens and a customized information feed is displayed. The input is the information feed from the server, and the output is the customized information feed displayed to the user.

[0121] The above is the processing flow and specific operation of this system's program. By clarifying the detailed input and output at each step, as well as the specific content of data processing and data calculation, users can efficiently collect information that matches their interests and check it at a specified time.

[0122] (Application example 1)

[0123] 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."

[0124] In today's information society, users are required to access a vast amount of information, but it is extremely difficult to select the information that is important to them from that. They are also unable to receive information in a timely manner, and lack the means to efficiently collect and review information at an appropriate time. Furthermore, despite the increasing diversity of information formats, conventional systems tend to be limited to text-based information. There is a need to solve these issues and provide users with useful information at the appropriate time.

[0125] 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.

[0126] In this invention, the server includes means for receiving input of an information category and a desired update time period from a user, means for automatically collecting related information from multiple information sources on a communication network based on the received information category, means for filtering and ranking the collected information, means for generating and distributing a customized information feed according to the desired update time period, means for scheduling to notify the smart device of the customized information, and means for processing information in both video and text format when generating the customized information feed. This allows users to efficiently collect information that matches their interests and check it in a timely manner at an appropriate time.

[0127] An "information category" represents a particular subject or genre that interests a user.

[0128] "Update time period" refers to a specific time period during which a user wishes to receive updates and notifications about the information they desire.

[0129] "Communications network" refers collectively to the network system used to collect and transmit information.

[0130] "Source" refers to the source or service that provides information, such as an internet news site or data provider.

[0131] "Filtering" refers to the process of selecting necessary information from collected information based on specific criteria.

[0132] "Ranking" refers to the process of prioritizing filtered information based on specific criteria.

[0133] "Information Feed" refers to a stream of customized information provided to a user.

[0134] "Scheduling" refers to the process of planning the execution of a particular task or process at a predetermined time.

[0135] "Smart devices" refer to mobile terminals and wearable devices that have Internet connectivity and can manage and display information.

[0136] "Video format" refers to a media format that contains moving images.

[0137] "Text format" refers to a media format that contains text or textual information.

[0138] This invention is a system that provides a customized information feed based on information that a user sets by setting the information categories of interest and the desired update time period.

[0139] User Settings

[0140] The user accesses the system and sets the information category and desired update time. For example, the user selects "News" and "Entertainment" through the application interface and sets that they want to receive information every morning at 7:00. This setting information is sent to the server.

[0141] Receiving and storing configuration information

[0142] The server receives the information category and desired update time period sent by the user and stores it in a database. This assigns a unique ID to each user and manages individual settings information.

[0143] Collection of information

[0144] At the specified update time, the server collects relevant information from sources on the network based on the user's settings, for example by sending an API request to get the latest news and entertainment information, and stores that information in the database.

[0145] Filtering and ranking information

[0146] The server then filters and ranks the most important information from the collected data based on relevance and recency, resulting in the selection of the most relevant information for the user.

[0147] Personalized information delivery

[0148] Based on the filtered and ranked information, the server generates a customized information feed, which is then delivered to the device at the update time specified by the user.

[0149] Displaying Information

[0150] The device receives the information feed sent from the server and notifies the user at the set time. When the user opens the app, the customized information feed is displayed. For example, a user can open the app on their way to work to check the latest "News" and "Entertainment."

[0151] Specific actions

[0152] The system operates using multiple software components. It uses API requests to collect information, a Python scheduling library (schedule), and a library for sending HTTP requests (requests). This allows it to filter the collected information and deliver it at a time specified by the user.

[0153] For example, suppose User A is interested in "sports" and "technology" and has set up a preference to receive information every day at 6:00 PM. The server saves this preference information and starts collecting related information from 5:55 PM. After filtering and ranking, the customized information feed is delivered to User A's device at 6:00 PM. User A can easily check the latest sports news and technology-related information in the evening.

[0154] Prompt Sentence Examples

[0155] You want to create an application that generates a customized news feed based on the user's interest categories and delivers it at a specified time. Provide a Python program that includes the following elements:

[0156] 1. User interface for setting news categories and update times.

[0157] 2. Collect news of a specified category from sources.

[0158] 3. Filter the collected news and rank them based on recency.

[0159] 4. The filtered news feed is sent to the user's device at the specified time.

[0160] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0161] Step 1:

[0162] The user sets the information categories they are interested in and the desired update time slots through the application interface. The information categories (e.g., "News" or "Entertainment") and update time slots (e.g., every morning at 7:00) entered by the user are sent to the server from the settings screen.

[0163] Input: User-defined information category and desired update time period

[0164] Output: User preference data sent to the server

[0165] Step 2:

[0166] The server receives the setting information sent by the user and stores it in a database, which assigns a unique ID to each user and manages individual setting information.

[0167] Input: User-defined data (information category and update time period)

[0168] Output: User preferences stored in the database

[0169] Step 3:

[0170] When the specified update time arrives, the server collects relevant information from multiple sources on the network based on the user's settings. The server sends an API request to collect information and obtains the latest content related to "News" and "Entertainment."

[0171] Input: User setting information (information category and update time period), API request

[0172] Output: Collected information

[0173] Step 4:

[0174] The server filters the collected information and ranks it based on relevance and recency. The server automatically analyzes the information and selects the most relevant information for the user.

[0175] Input: Collected information

[0176] Output: Filtered and ranked information

[0177] Step 5:

[0178] The server generates a customized information feed based on the filtered and ranked information, and the generated information feed is delivered to the terminal at the update time specified by the user.

[0179] Input: Filtered and ranked information

[0180] Output: Customized information feed

[0181] Step 6:

[0182] The device receives the customized information feed sent from the server and notifies the user at the specified update time. When the user opens the app on the device, the customized information feed is displayed.

[0183] Input: Customized information feed

[0184] Output: A customized information feed displayed on your device

[0185] Step 7:

[0186] Users can open their devices on their way to work or in their spare time to check their customized information feed, allowing them to efficiently gather the latest information that matches their interests and view it at the appropriate time.

[0187] Input: A customized information feed displayed on your device

[0188] Output: Customized information for the user to review

[0189] 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.

[0190] The present invention is a system that receives input from a user regarding news genres and desired update times, automatically collects relevant news articles from multiple news sources on a network based on the input, filters and ranks them, and then generates a customized news feed. Furthermore, it incorporates an emotion engine that recognizes the user's emotions, providing a means for filtering and ranking news articles based on the user's emotional state. Specific implementation methods of the present invention are described below.

[0191] User Settings

[0192] Users access the system and set the news genre and desired update time. For example, they may select "IT news" and "Economic news" and want news updates every morning at 7:00. This setting information is entered through the application's user interface and sent to the server.

[0193] Receiving and storing configuration information

[0194] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database, allowing each user's settings information to be managed uniquely.

[0195] News gathering

[0196] At the specified update time, the server collects relevant news from news sources on the network based on the configuration information, for example, sending an API request to get the latest news articles on "IT" and "Economy" and stores them in the database.

[0197] Filtering and Ranking

[0198] The server filters the collected news articles and ranks them based on relevance and recency, a process that selects the most relevant articles for the user.

[0199] Customize and deliver news

[0200] Based on the filtered and ranked news articles, the server generates a customized news feed that is delivered to the user's device at the time of their choice.

[0201] Emotional engine regulation

[0202] The server uses an emotion engine that recognizes the user's emotions. The emotion engine analyzes voice, facial expressions, input data, etc. to identify the user's emotions. For example, if the user is showing positive emotions, it will prioritize displaying more optimistic news, and if the user is showing negative emotions, it will prioritize displaying comforting and encouraging news.

[0203] Viewing news

[0204] The device receives the customized news feed sent from the server and notifies the user at the specified time. When the user opens the app, the customized news feed is displayed.

[0205] Specific examples

[0206] As a specific example, suppose User A is interested in "sports news" and "entertainment news" and has set up a daily news feed at 6:00 PM. The server saves this setting information and starts collecting relevant news from 5:55 PM. After filtering and ranking, a customized news feed is delivered to User A's device at 6:00 PM. If the emotion engine recognizes that User A has been feeling stressed recently, news that helps with relaxation and distraction will be presented preferentially.

[0207] This invention allows users to efficiently collect news that interest them and check it at an appropriate time. Furthermore, the introduction of an emotion engine provides news articles that match the user's current emotional state, further improving the user experience.

[0208] The processing flow will be explained below.

[0209] Step 1:

[0210] When a user installs the application and starts it for the first time, they select the news genre and desired update time. For example, they may select "IT news" and "Economic news" and want news updates every morning at 7:00. This setting information is entered through the application's user interface and sent to the server.

[0211] Step 2:

[0212] The server receives the setting information sent by the user. The received information includes the user's ID, selected news genre, and desired update time period. This information is stored in a database and managed uniquely for each user.

[0213] Step 3:

[0214] A few minutes before the specified update time (e.g., 6:55), the server starts collecting relevant news based on the configuration information. Specifically, it sends API requests to retrieve the latest news articles related to "IT" and "Economy" from multiple reliable news sources. The retrieved news articles are then stored in a database.

[0215] Step 4:

[0216] The server filters the collected news articles based on criteria such as the article's relevance, recency, and credibility, for example, to exclude articles that the user has already seen or that are duplicates.

[0217] Step 5:

[0218] The server then ranks the filtered news articles, taking into account the importance and timeliness of the articles. The more important and up-to-date news is ranked higher and displayed preferentially.

[0219] Step 6:

[0220] The server uses an emotion engine to recognize the user's emotions. The emotion engine identifies the user's emotions through voice analysis, facial expression analysis, text analysis, etc. For example, if the user's recent typing history or voice tone indicates a positive emotion, the corresponding news article will be selected.

[0221] Step 7:

[0222] Based on the results of the emotion engine, the server reprioritizes news articles: for example, if a user expresses negative emotions, news articles that bring encouragement and hope will be prioritized.

[0223] Step 8:

[0224] Based on the filtered and ranked news articles, the server generates a customized news feed that is tailored to the user's preferred update timeframe.

[0225] Step 9:

[0226] At the specified update time (e.g., 7:00), the server delivers the generated customized news feed to the user's device via push notification, in-app notification, or email.

[0227] Step 10:

[0228] The device receives the news feed sent from the server, arranges for the news feed to be displayed at the time set by the user, and displays a notification to inform the user that a new news feed has arrived.

[0229] Step 11:

[0230] Users open the app and check the delivered news feed. They can browse the latest news articles in the genres they are interested in. The articles displayed are tailored to the user's emotional state, improving the user experience.

[0231] This step allows users to efficiently collect news that interests them and check news articles that correspond to their emotions at an appropriate time.

[0232] Example 2

[0233] 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."

[0234] In modern society, users need to efficiently obtain relevant information from a vast amount of news articles. However, conventional news gathering systems provide information without fully considering the user's interests or emotional state, making it difficult for users to find the information they need. Furthermore, a large amount of news information can have a negative impact on the user's emotions and mental state.

[0235] 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.

[0236] In this invention, the server includes means for receiving input of a news genre and a desired update time period from a user, means for automatically collecting related news articles from multiple news sources on a network based on the received news genre, means for filtering the collected news articles and ranking them based on relevance and recency, means for generating and delivering a customized news feed according to the desired update time period, and means for analyzing the user's emotions and adjusting the news feed based on the user's emotional state, thereby enabling the user to efficiently obtain news of interest and providing a news feed optimized according to the user's emotional state.

[0237] "News genre" refers to a particular category of news that interests a user.

[0238] A "desired update time slot" refers to a time at which a user desires to receive a news feed.

[0239] "News Source" means an online source that is consulted to provide relevant news articles.

[0240] "Filtering" refers to the process of sorting collected news articles based on specific criteria.

[0241] "Ranking" refers to the process of ranking the filtered news articles based on relevance and recency.

[0242] "Customized News Feed" means a list of news items that are individually optimized based on a user's preferences and criteria.

[0243] "Delivery" refers to the process of sending a customized news feed to a user's device.

[0244] An "emotion engine" refers to technology that recognizes a user's emotional state by analyzing voice, facial expressions, input data, etc.

[0245] "Emotional state" refers to a state that indicates a user's current feelings or mood.

[0246] MODE FOR CARRYING OUT THE INVENTION

[0247] The present invention is a system that receives input from users regarding news genres and desired update times, automatically collects relevant news articles from multiple news sources on the network based on the input, filters and ranks them, and then generates and distributes a customized news feed. Furthermore, the system aims to combine an emotion engine that recognizes the user's emotions and adjusts the news articles based on the user's emotional state.

[0248] User Settings

[0249] A user accesses the system and sets the news genre and desired update time. For example, if a user selects "sports news" and "entertainment news" and wants news updates every day at 6:00 PM, this setting information is entered through the application's user interface and sent to the server.

[0250] Receiving and storing configuration information

[0251] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database, allowing each user's settings information to be managed uniquely.

[0252] News gathering

[0253] At the specified update time, the server collects relevant news from news sources on the network based on the configuration information. For example, it sends an API request to retrieve the latest news articles on "sports" and "entertainment" and stores them in a database. Examples of news APIs that can be used include NewsAPI and Google News API.

[0254] Filtering and Ranking

[0255] The server filters the collected news articles and ranks them based on relevance and recency, for example by using a machine learning model (such as Scikit-learn) to rank the news articles, thereby selecting the most relevant articles for the user.

[0256] Customize and deliver news

[0257] Based on the filtered and ranked news articles, the server generates a customized news feed that is delivered to the user's device at the time of their choice.

[0258] Emotional engine regulation

[0259] The server uses an emotion engine that recognizes the user's emotions. The emotion engine analyzes voice, facial expressions, input data, etc. to identify the user's emotions. For example, if the user is showing positive emotions, it will prioritize displaying more optimistic news, and if the user is showing negative emotions, it will prioritize displaying comforting and encouraging news. Specific examples include using the Microsoft Emotion API and Amazon Comprehend.

[0260] Viewing news

[0261] The device receives the customized news feed sent from the server and notifies the user at the specified time. When the user opens the app, the customized news feed is displayed.

[0262] Specific examples

[0263] As a specific example, if User A is interested in "sports news" and "entertainment news" and has set his / her preference to receive news every day at 6:00 PM, the server will save this preference information and start collecting related news from 5:55 PM. After filtering and ranking, a customized news feed will be delivered to User A's device at 6:00 PM. Also, if the emotion engine recognizes that User A has been feeling stressed recently, news that will help him / her relax or unwind will be presented preferentially.

[0264] Example prompts for generative AI models

[0265] The following can be input to the generative AI model:

[0266] Example prompt 1:

[0267] "Write a program that automatically gathers and filters relevant news articles to provide a customized feed to users based on their preferred news genre and update time frame."

[0268] Example prompt 2:

[0269] "Write a program to create a system that recognizes a user's emotions and filters and ranks news based on those emotions."

[0270] This helps the generative AI model generate the program for the entire system.

[0271] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0272] Step 1:

[0273] A user accesses the system and sets the news genre and desired update time period.

[0274] Specific behavior:

[0275] The user enters information into the fields for "news genre" and "update time" through the application's user interface. For example, the user might enter "IT news" and "economic news" at 7:00 every morning. The entered data is sent to the server by pressing the send button.

[0276] Input: User-selected news genre and desired update time

[0277] Output: Configuration information sent to the server

[0278] Step 2:

[0279] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database.

[0280] Specific behavior:

[0281] The server receives user setting information via the REST API. It analyzes the received information and saves it as per-user settings in a database (e.g., MySQL or PostgreSQL). After saving is complete, it generates a save confirmation message for the user and sends it to the device.

[0282] Input: Received setting information

[0283] Output: Setting information saved in the database, save confirmation message

[0284] Step 3:

[0285] When the specified update time arrives, the server collects relevant news from news sources on the network based on the setting information.

[0286] Specific behavior:

[0287] Use Chron jobs or CRON scheduling to start the news gathering process at a specified time (e.g., 6:55 every morning). Send an API request to a news API (e.g., News API, Google News API) to retrieve the latest news in a specified genre. Store the retrieved news data in a database.

[0288] Input: User settings, latest news from news API

[0289] Output: A database containing news data

[0290] Step 4:

[0291] The server filters the collected news articles and ranks them based on relevance and recency.

[0292] Specific behavior:

[0293] Applying filtering algorithms based on news article categories, dates, keywords, etc. Ranking news articles using a machine learning model (e.g., a ranking algorithm built with Scikit-learn). Keeping the ranked results in temporary storage or memory.

[0294] Input: Collected news articles

[0295] Output: Filtered and ranked news articles

[0296] Step 5:

[0297] Based on the filtered and ranked news articles, the server generates a customized news feed and delivers it to the device at the specified time.

[0298] Specific behavior:

[0299] Generate a customized news feed at a specified time (e.g., every morning at 7:00). Deliver the news feed to the user's device using email or push notification APIs (e.g., Firebase Cloud Messaging). Log whether the feed was delivered successfully.

[0300] Input: Customized news article

[0301] Output: News feed delivered to the user's device

[0302] Step 6:

[0303] The server uses an emotion engine that recognizes the user's emotions and readjusts the news article.

[0304] Specific behavior:

[0305] Analyze user emotions using sentiment analysis APIs (e.g., Microsoft Emotion API, Amazon Comprehend). Input voice data and text feedback into the emotion engine to get results. Readjust the content of the news feed based on the emotional state. For example, prioritize positive articles.

[0306] Input: User emotion data

[0307] Output: Rebalanced news feed

[0308] Step 7:

[0309] The terminal receives the customized news feed sent from the server and notifies the user at a specified time.

[0310] Specific behavior:

[0311] The device receives push notifications and emails and notifies the user in the configured way. When the user launches the app, a customized news feed is displayed. User feedback is obtained and sent to the server.

[0312] Input: News feed from the server

[0313] Output: Notified news feed and user feedback

[0314] (Application example 2)

[0315] 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."

[0316] Conventional news feed generation systems allow users to set the news genres they are interested in and the update time slots they desire, but they are unable to customize news articles based on the user's emotional state. As a result, inappropriate news articles may be displayed when the user is feeling stressed or in a particular mood. Therefore, there is a need to provide a more user-friendly news feed by filtering and ranking news articles based on the user's emotional state.

[0317] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving input of a news genre and a desired update time period from a user; means for automatically collecting related news articles from multiple news sources on the network based on the received news genre; means for filtering and ranking the collected news articles; means for generating and delivering a customized news feed according to the desired update time period; and means for using an emotion engine that recognizes the user's emotional state to filter and rank the news articles based on the emotional state. This makes it possible to provide an optimal news feed tailored to the user's emotional state.

[0318] A "news genre" refers to news articles in a particular field or category that interests a user.

[0319] A "desired update time" is a specific time period during which a user would like to receive the latest news feed.

[0320] "News sources" are the websites and databases that provide news articles.

[0321] "Related news articles" refer to news articles collected based on the news genre set by the user.

[0322] "Filtering" refers to the process of filtering out collected news articles that are less relevant to the user.

[0323] "Ranking" is the process of prioritizing a collection of news articles based on their relevance and recency.

[0324] A "customized news feed" is a list of news articles generated and optimized based on a user's news genre and preferred update time frame.

[0325] An "emotion engine" refers to algorithms and techniques for recognizing a user's emotional state and filtering and ranking news articles based on that.

[0326] The present invention is a system that receives input from users regarding news genres and desired update times, automatically collects relevant news articles from multiple news sources on the network based on the input, filters and ranks them, and then generates a customized news feed. Furthermore, it combines an emotion engine that recognizes the user's emotions, providing a means for filtering and ranking news articles based on the user's emotional state.

[0327] A system for implementing the present invention includes the following components:

[0328] User Settings

[0329] Users can set their preferred news genre and update time through the application. For example, they can select "IT news" or "Economic news" and request news updates every morning at 7:00. This setting information is entered through the smartphone application's user interface and sent to the server.

[0330] Receiving and storing configuration information

[0331] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database. This database is managed using a database management system (DBMS) such as SQLite.

[0332] News gathering

[0333] When the specified update time arrives, the server collects relevant news articles from news sources based on the configuration information. For example, it uses a news API to obtain the latest news articles related to "IT" or "Economy" and stores this data in a database.

[0334] Filtering and Ranking

[0335] The server then filters the collected news articles and ranks them based on relevance and recency, a process that involves processing the data using, for example, the Python programming language and scripting libraries.

[0336] Customize and deliver news

[0337] Based on the filtered and ranked news articles, the server generates a customized news feed and delivers it to the user's device, such as a smartphone or tablet, according to the user's desired update time.

[0338] Emotional engine regulation

[0339] The server is equipped with an emotion engine that recognizes the user's emotions. This engine analyzes the user's facial images and voice data using machine learning models such as TensorFlow to identify the user's emotional state. For example, if the user is showing positive emotions, it will prioritize displaying more optimistic news, and if the user is showing negative emotions, it will prioritize displaying comforting and encouraging news.

[0340] Viewing news

[0341] The device receives the customized news feed sent from the server, and when the user opens the app, the system displays the news feed.

[0342] Specific examples

[0343] As a specific example, suppose User A is interested in "Entertainment" and "Sports" and has set his preferences to receive news every day at 6:00 PM. The server saves this preference information and starts collecting relevant news articles from 5:55 PM. After filtering and ranking, a customized news feed is delivered to User A's device at 6:00 PM. If the emotion engine recognizes that User A has been feeling stressed recently, news that will help him relax and unwind will be presented preferentially.

[0344] Prompt Sentence Examples

[0345] "Generate a smartphone app program using Python that collects the latest news based on the news genre and desired update time specified by the user, and uses an emotion engine to prioritize and display news that matches the user's emotional state."

[0346] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0347] Step 1:

[0348] The user inputs the news genre and desired update time into the application. For example, the user selects "IT news" and "Economic news" and requests news updates every morning at 7:00. This input information is sent to the server via the user interface. The news genre and desired update time are provided as input data, and the server receives this setting information as output.

[0349] Step 2:

[0350] The server stores the information received from the user about the news genre and desired update time period in a database. This process uses a database management system (e.g., SQLite). The server receives user setting information as input data and stores it accurately in the database.

[0351] Step 3:

[0352] At the set update time, the server collects relevant news articles from news sources and sends an API request to get the latest news articles based on the news genre set by the user. For example, the news API can be used to get the latest articles related to "IT" or "Economy" and store the data in a database. The news genre and API endpoint are used as input data, and the list of latest news articles is obtained as output.

[0353] Step 4:

[0354] The server filters the collected news articles and ranks them based on relevance and recency. This process is performed using the Python programming language and data processing libraries (e.g., pandas). It receives a list of collected news articles as input, evaluates the articles based on relevance and recency, and outputs a ranked list.

[0355] Step 5:

[0356] The server generates a customized news feed based on the filtered and ranked news articles and delivers it to the device according to the user's desired update time. The server retrieves the ranked news articles from the database, generates a news feed formatted for the user's interface, and sends it to the smartphone. The ranked articles are used as input data, and the customized news feed is delivered as output.

[0357] Step 6:

[0358] The server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's facial and voice data using TensorFlow's machine learning model to identify the user's emotions. It receives the user's facial expression image or voice data as input data, analyzes the data, and outputs the user's emotional state.

[0359] Step 7:

[0360] The server further filters and ranks the news articles based on the user's emotional state as determined by the emotion engine. For example, if the user is expressing positive emotions, it prioritizes optimistic news, and if the user is expressing negative emotions, it prioritizes comforting and encouraging news. The server takes the emotional state information as input data and re-evaluates and outputs the news articles based on it.

[0361] Step 8:

[0362] The device receives the customized news feed sent from the server and notifies the user at the specified time. When the user opens the app, the customized news feed is displayed. The app receives the news feed from the server as input data and displays it in the user interface as output.

[0363] 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.

[0364] 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.

[0365] 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.

[0366] [Second embodiment]

[0367] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0368] 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.

[0369] 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).

[0370] 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.

[0371] 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.

[0372] 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).

[0373] 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.

[0374] 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.

[0375] 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.

[0376] 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.

[0377] 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.

[0378] 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."

[0379] The present invention provides a system that allows users to set the news genres they are interested in and the update time periods they desire, and provides a news feed that is customized based on that information. Below, an embodiment of this system will be described.

[0380] User Settings

[0381] Users access the system and set their desired news genre and update time. For example, a user can select "IT news" and "economic news" through the application interface and set their preference to receive news at 7:00 a.m. every morning. This setting information is sent to the server.

[0382] Receiving and storing configuration information

[0383] The server receives the news genre and desired update time period sent by the user and stores it in a database, which assigns a unique ID to each user and manages their individual settings.

[0384] News gathering

[0385] When the specified update time arrives, the server collects relevant news from news sources on the network based on the user's settings, for example, by sending an API request to retrieve the latest news articles related to "IT" and "Economy," and stores the news articles in the database.

[0386] News filtering and ranking

[0387] The server filters and ranks the most important articles from the collected news articles based on relevance and recency, a process that results in the most relevant articles being selected for the user.

[0388] Customize and deliver news

[0389] Based on the filtered and ranked news articles, the server generates a customized news feed, which is delivered to the device at the update time specified by the user.

[0390] Viewing news

[0391] The device receives the news feed sent from the server and notifies the user at the set time. When the user opens the app, the customized news feed is displayed. For example, a user can open the app on their way to work and check the latest "IT news" and "economic news."

[0392] Specific examples

[0393] As a concrete example, suppose User A is interested in "sports news" and "entertainment news" and has set up a daily news feed at 6:00 PM. The server saves this setting information and starts collecting relevant news from 5:55 PM. After filtering and ranking, the customized news feed is delivered to User A's device at 6:00 PM. User A can easily check the latest sports and entertainment news on his / her way home.

[0394] The above is an embodiment of the system of the present invention, which enables users to efficiently collect news that matches their interests and check it in a timely manner at an appropriate time.

[0395] The processing flow will be explained below.

[0396] Step 1:

[0397] When the user installs the application and starts it for the first time, they set the news genre and desired update time. Specifically, they select "IT news" and "Economic news" and want news updates every morning at 7:00. The setting information is entered through the application's user interface and sent to the server.

[0398] Step 2:

[0399] The server receives the setting information sent by the user. The received information includes the user's ID, selected news genre, and desired update time period. The server stores this information in a database. This allows the setting information to be managed uniquely for each user, and the data required for subsequent processing is retained.

[0400] Step 3:

[0401] A few minutes before the specified update time (in this case, 7:00 every morning), the server starts collecting news based on the configuration information. Specifically, it sends API requests to multiple reliable news sources for the selected news genres ("IT" and "Economy"), and retrieves the latest news articles.

[0402] Step 4:

[0403] The server filters the retrieved news articles, taking into account criteria such as the relevance, recency, and reliability of the news articles. For example, inappropriate content and duplicate articles are filtered out, and the most relevant news is selected.

[0404] Step 5:

[0405] The server ranks the filtered news articles. The ranking criteria take into account the importance and timeliness of the article. The more important and latest news are ranked higher and displayed preferentially.

[0406] Step 6:

[0407] The server generates a customized news feed from the filtered and ranked news articles, which is configured to include only news genres selected by the user.

[0408] Step 7:

[0409] At the specified update time (in this case, every morning at 7:00), the server delivers the generated customized news feed to the user's device via push notification, email, in-app notification, or other methods depending on the user's settings.

[0410] Step 8:

[0411] The device receives the news feed sent from the server and arranges for the news feed to be displayed at a time set by the user. For example, an application can automatically display a notification to inform the user that a new news feed has arrived.

[0412] Step 9:

[0413] Users open the application at the specified time and check the delivered news feed. Users can efficiently browse the latest news articles in the genres they are interested in. They can select articles that interest them and read detailed information.

[0414] This series of steps allows users to efficiently collect news that interests them and check it at an appropriate time, significantly reducing the time it takes for users to gather news and providing timely access to important information.

[0415] Example 1

[0416] 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."

[0417] In modern society, people have access to a vast amount of information. However, it is difficult to efficiently collect only the information of interest and review it in a timely manner. Conventional information collection systems lack the technology to provide customized information feeds based on specified information categories and update times. They also have limited functionality for filtering and ranking information items based on relevance and recency. Therefore, there is a need to develop a system that provides users with the most appropriate information at the right time.

[0418] 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.

[0419] In this invention, the server includes means for receiving input of an information category and a desired delivery time period from a user, means for automatically collecting related information items from multiple information sources on a network based on the received information category, means for filtering and ranking the collected information items, and means for generating and delivering a customized information feed tailored to the desired delivery time period, thereby enabling users to efficiently collect information that matches their interests and view it in a timely manner at an appropriate time.

[0420] "User" means a user of the system who intends to receive information based on his or her interests.

[0421] An "information category" is a division of a particular type of information that interests a user, such as a news genre or topic area.

[0422] The "desired delivery time period" is the range of time within which the user can receive information, and a specific time or time period can be specified.

[0423] "Multiple information sources on the network" refers to various sources accessible via the Internet, including news sites, blogs, APIs, etc.

[0424] "Relevant information items" refer to specific news articles or data entries collected based on the information categories received.

[0425] "Automatic collection methods" are mechanisms by which programs automatically obtain information based on user settings, such as using web crawlers or API requests.

[0426] "Filtering" is the process of selecting useful information items from collected information based on specific criteria.

[0427] "Ranking" is the process of prioritizing filtered information items based on relevance and recency.

[0428] A "customized information feed" is a collection of news and data delivered as a personalized stream of information generated according to a user's preferences.

[0429] The "means of delivery" refers to a method for sending the generated information feed to the user's terminal, and includes email, push notification, a dedicated application, and the like.

[0430] The present invention provides a system that allows users to set information categories of interest and desired delivery time periods, and provides a customized information feed based on that information. The following describes an embodiment of this system.

[0431] User Settings

[0432] Users access the system and set the information category and desired delivery time. For example, a user can select "IT news" and "economic news" through the application interface and set the information to be delivered at 7:00 every morning. This setting information is sent to the server.

[0433] Receiving and storing configuration information

[0434] The server receives the information category and desired delivery time slot sent by the user and stores it in a database. Specifically, it uses a database such as MySQL or PostgreSQL to manage user IDs, information categories, and delivery time slots.

[0435] Collection of information

[0436] As the specified delivery time approaches, the server collects relevant information from information sources on the network based on the user's settings. Specifically, it sends API requests to obtain the latest information items related to "IT" and "Economy" and stores the information in a database. The APIs used for this purpose are, for example, NewsAPI and NY Times API.

[0437] Filtering and ranking information

[0438] The server then filters and ranks the collected information items based on their relevance and recency. This process uses a machine learning algorithm based on Python's scikit-learn library. Specifically, it performs text analysis on the information items, calculates a relevance score, and assigns a ranking.

[0439] Personalized information delivery

[0440] Based on the filtered and ranked information items, the server generates a customized information feed in HTML or JSON format, customizing the content for each user, and then sends the generated information feed to the user's device.

[0441] Displaying Information

[0442] The device receives the information feed sent from the server and notifies the user at the set time. For example, the push notification function can be used to display a message saying, "The latest IT and economic news has been updated" at a specified time. When the user clicks on this notification, the app opens and the customized information feed is displayed.

[0443] Specific examples

[0444] As a concrete example, suppose User A is interested in "Sports News" and "Entertainment News" and has set up a schedule to receive information at 6:00 PM. The server saves this setting and starts collecting relevant information from 5:55 PM. After filtering and ranking, a customized information feed is delivered to User A's device at 6:00 PM. User A receives a notification on his / her way home and can open the app to check the latest sports and entertainment news.

[0445] Examples of prompt statements

[0446] An example of a prompt to be input to the generative AI model is as follows:

[0447] Explain how a system that provides a customized information feed works, allowing users to set the information categories they are interested in and the time slots they want delivered. For example, explain in detail how a system works if a user selects "IT news" and "Economic news" and sets the time slots to receive them every morning at 7:00.

[0448] The above is an embodiment of the system of the present invention. This system enables users to efficiently collect information that matches their interests and check it in a timely manner at an appropriate time.

[0449] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0450] Step 1:

[0451] The user opens the application and enters the information category and desired delivery time slot. Specifically, the user selects "IT News" or "Economic News" in the application interface and sets "7:00" as the delivery time slot. Once this setting information has been entered, the user presses the "Set" button to send it to the server. The input here is the information category and delivery time slot data, and the output is data sent to the server.

[0452] Step 2:

[0453] The server receives the information category and desired delivery time setting information sent by the user. It then stores the information in a database such as MySQL or PostgreSQL. Specifically, data including the user ID, information category, and delivery time is stored and managed in the database. The input is the user setting data, and the output is the operation of saving it to the database.

[0454] Step 3:

[0455] As the specified delivery time approaches, the server starts the information collection process. For example, if a user has set their preference to receive news at 7:00 in the morning, the server will send a request to a news API (such as NewsAPI or NY Times API) at 6:55 to collect the latest information on "IT" and "Economy." The collected data is then stored in a database as is. The input is the API request, and the output is the data of the retrieved information items.

[0456] Step 4:

[0457] The server filters and ranks the collected information items. Specifically, it uses the scikit-learn library to perform text analysis, selects articles that are highly relevant to the user's preferences, and calculates an importance score to rank them. This process uses relevance and recency as criteria. The input is the collected information items, and the output is the filtered and ranked information items.

[0458] Step 5:

[0459] Based on the filtered and ranked information items, the server generates a customized information feed. The generated information feed is created in HTML or JSON format and is customized to have different content for each user. Once generated, the information feed is sent to the user's device. The input is the filtered and ranked information items, and the output is the customized information feed.

[0460] Step 6:

[0461] The device receives the information feed sent from the server and notifies the user at the set time. The push notification function is used to notify the user of information updates. When the user clicks on the notification, the app opens and a customized information feed is displayed. The input is the information feed from the server, and the output is the customized information feed displayed to the user.

[0462] The above is the processing flow and specific operation of this system's program. By clarifying the detailed input and output at each step, as well as the specific content of data processing and data calculation, users can efficiently collect information that matches their interests and check it at a specified time.

[0463] (Application example 1)

[0464] 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."

[0465] In today's information society, users are required to access a vast amount of information, but it is extremely difficult to select the information that is important to them from that. They are also unable to receive information in a timely manner, and lack the means to efficiently collect and review information at an appropriate time. Furthermore, despite the increasing diversity of information formats, conventional systems tend to be limited to text-based information. There is a need to solve these issues and provide users with useful information at the appropriate time.

[0466] 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.

[0467] In this invention, the server includes means for receiving input of an information category and a desired update time period from a user, means for automatically collecting related information from multiple information sources on a communication network based on the received information category, means for filtering and ranking the collected information, means for generating and distributing a customized information feed according to the desired update time period, means for scheduling to notify the smart device of the customized information, and means for processing information in both video and text format when generating the customized information feed. This allows users to efficiently collect information that matches their interests and check it in a timely manner at an appropriate time.

[0468] An "information category" represents a particular subject or genre that interests a user.

[0469] "Update time period" refers to a specific time period during which a user wishes to receive updates and notifications about the information they desire.

[0470] "Communications network" refers collectively to the network system used to collect and transmit information.

[0471] "Source" refers to the source or service that provides information, such as an internet news site or data provider.

[0472] "Filtering" refers to the process of selecting necessary information from collected information based on specific criteria.

[0473] "Ranking" refers to the process of prioritizing filtered information based on specific criteria.

[0474] "Information Feed" refers to a stream of customized information provided to a user.

[0475] "Scheduling" refers to the process of planning the execution of a particular task or process at a predetermined time.

[0476] "Smart devices" refer to mobile terminals and wearable devices that have Internet connectivity and can manage and display information.

[0477] "Video format" refers to a media format that contains moving images.

[0478] "Text format" refers to a media format that contains text or textual information.

[0479] This invention is a system that provides a customized information feed based on information that a user sets by setting the information categories of interest and the desired update time period.

[0480] User Settings

[0481] The user accesses the system and sets the information category and desired update time. For example, the user selects "News" and "Entertainment" through the application interface and sets that they want to receive information every morning at 7:00. This setting information is sent to the server.

[0482] Receiving and storing configuration information

[0483] The server receives the information category and desired update time period sent by the user and stores it in a database. This assigns a unique ID to each user and manages individual settings information.

[0484] Collection of information

[0485] At the specified update time, the server collects relevant information from sources on the network based on the user's settings, for example by sending an API request to get the latest news and entertainment information, and stores that information in the database.

[0486] Filtering and ranking information

[0487] The server then filters and ranks the most important information from the collected data based on relevance and recency, resulting in the selection of the most relevant information for the user.

[0488] Personalized information delivery

[0489] Based on the filtered and ranked information, the server generates a customized information feed, which is then delivered to the device at the update time specified by the user.

[0490] Displaying Information

[0491] The device receives the information feed sent from the server and notifies the user at the set time. When the user opens the app, the customized information feed is displayed. For example, a user can open the app on their way to work to check the latest "News" and "Entertainment."

[0492] Specific actions

[0493] The system operates using multiple software components. It uses API requests to collect information, a Python scheduling library (schedule), and a library for sending HTTP requests (requests). This allows it to filter the collected information and deliver it at a time specified by the user.

[0494] For example, suppose User A is interested in "sports" and "technology" and has set up a preference to receive information every day at 6:00 PM. The server saves this preference information and starts collecting related information from 5:55 PM. After filtering and ranking, the customized information feed is delivered to User A's device at 6:00 PM. User A can easily check the latest sports news and technology-related information in the evening.

[0495] Prompt Sentence Examples

[0496] You want to create an application that generates a customized news feed based on the user's interest categories and delivers it at a specified time. Provide a Python program that includes the following elements:

[0497] 1. User interface for setting news categories and update times.

[0498] 2. Collect news of a specified category from sources.

[0499] 3. Filter the collected news and rank them based on recency.

[0500] 4. The filtered news feed is sent to the user's device at the specified time.

[0501] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0502] Step 1:

[0503] The user sets the information categories they are interested in and the desired update time slots through the application interface. The information categories (e.g., "News" or "Entertainment") and update time slots (e.g., every morning at 7:00) entered by the user are sent to the server from the settings screen.

[0504] Input: User-defined information category and desired update time period

[0505] Output: User preference data sent to the server

[0506] Step 2:

[0507] The server receives the setting information sent by the user and stores it in a database, which assigns a unique ID to each user and manages individual setting information.

[0508] Input: User-defined data (information category and update time period)

[0509] Output: User preferences stored in the database

[0510] Step 3:

[0511] When the specified update time arrives, the server collects relevant information from multiple sources on the network based on the user's settings. The server sends an API request to collect information and obtains the latest content related to "News" and "Entertainment."

[0512] Input: User setting information (information category and update time period), API request

[0513] Output: Collected information

[0514] Step 4:

[0515] The server filters the collected information and ranks it based on relevance and recency. The server automatically analyzes the information and selects the most relevant information for the user.

[0516] Input: Collected information

[0517] Output: Filtered and ranked information

[0518] Step 5:

[0519] The server generates a customized information feed based on the filtered and ranked information, and the generated information feed is delivered to the terminal at the update time specified by the user.

[0520] Input: Filtered and ranked information

[0521] Output: Customized information feed

[0522] Step 6:

[0523] The device receives the customized information feed sent from the server and notifies the user at the specified update time. When the user opens the app on the device, the customized information feed is displayed.

[0524] Input: Customized information feed

[0525] Output: A customized information feed displayed on your device

[0526] Step 7:

[0527] Users can open their devices on their way to work or in their spare time to check their customized information feed, allowing them to efficiently gather the latest information that matches their interests and view it at the appropriate time.

[0528] Input: A customized information feed displayed on your device

[0529] Output: Customized information for the user to review

[0530] 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.

[0531] The present invention is a system that receives input from a user regarding news genres and desired update times, automatically collects relevant news articles from multiple news sources on a network based on the input, filters and ranks them, and then generates a customized news feed. Furthermore, it incorporates an emotion engine that recognizes the user's emotions, providing a means for filtering and ranking news articles based on the user's emotional state. Specific implementation methods of the present invention are described below.

[0532] User Settings

[0533] Users access the system and set the news genre and desired update time. For example, they may select "IT news" and "Economic news" and want news updates every morning at 7:00. This setting information is entered through the application's user interface and sent to the server.

[0534] Receiving and storing configuration information

[0535] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database, allowing each user's settings information to be managed uniquely.

[0536] News gathering

[0537] At the specified update time, the server collects relevant news from news sources on the network based on the configuration information, for example, sending an API request to get the latest news articles on "IT" and "Economy" and stores them in the database.

[0538] Filtering and Ranking

[0539] The server filters the collected news articles and ranks them based on relevance and recency, a process that selects the most relevant articles for the user.

[0540] Customize and deliver news

[0541] Based on the filtered and ranked news articles, the server generates a customized news feed that is delivered to the user's device at the time of their choice.

[0542] Emotional engine regulation

[0543] The server uses an emotion engine that recognizes the user's emotions. The emotion engine analyzes voice, facial expressions, input data, etc. to identify the user's emotions. For example, if the user is showing positive emotions, it will prioritize displaying more optimistic news, and if the user is showing negative emotions, it will prioritize displaying comforting and encouraging news.

[0544] Viewing news

[0545] The device receives the customized news feed sent from the server and notifies the user at the specified time. When the user opens the app, the customized news feed is displayed.

[0546] Specific examples

[0547] As a specific example, suppose User A is interested in "sports news" and "entertainment news" and has set up a daily news feed at 6:00 PM. The server saves this setting information and starts collecting relevant news from 5:55 PM. After filtering and ranking, a customized news feed is delivered to User A's device at 6:00 PM. If the emotion engine recognizes that User A has been feeling stressed recently, news that helps with relaxation and distraction will be presented preferentially.

[0548] This invention allows users to efficiently collect news that interest them and check it at an appropriate time. Furthermore, the introduction of an emotion engine provides news articles that match the user's current emotional state, further improving the user experience.

[0549] The processing flow will be explained below.

[0550] Step 1:

[0551] When a user installs the application and starts it for the first time, they select the news genre and desired update time. For example, they may select "IT news" and "Economic news" and want news updates every morning at 7:00. This setting information is entered through the application's user interface and sent to the server.

[0552] Step 2:

[0553] The server receives the setting information sent by the user. The received information includes the user's ID, selected news genre, and desired update time period. This information is stored in a database and managed uniquely for each user.

[0554] Step 3:

[0555] A few minutes before the specified update time (e.g., 6:55), the server starts collecting relevant news based on the configuration information. Specifically, it sends API requests to retrieve the latest news articles related to "IT" and "Economy" from multiple reliable news sources. The retrieved news articles are then stored in a database.

[0556] Step 4:

[0557] The server filters the collected news articles based on criteria such as the article's relevance, recency, and credibility, for example, to exclude articles that the user has already seen or that are duplicates.

[0558] Step 5:

[0559] The server then ranks the filtered news articles, taking into account the importance and timeliness of the articles. The more important and up-to-date news is ranked higher and displayed preferentially.

[0560] Step 6:

[0561] The server uses an emotion engine to recognize the user's emotions. The emotion engine identifies the user's emotions through voice analysis, facial expression analysis, text analysis, etc. For example, if the user's recent typing history or voice tone indicates a positive emotion, the corresponding news article will be selected.

[0562] Step 7:

[0563] Based on the results of the emotion engine, the server reprioritizes news articles: for example, if a user expresses negative emotions, news articles that bring encouragement and hope will be prioritized.

[0564] Step 8:

[0565] Based on the filtered and ranked news articles, the server generates a customized news feed that is tailored to the user's preferred update timeframe.

[0566] Step 9:

[0567] At the specified update time (e.g., 7:00), the server delivers the generated customized news feed to the user's device via push notification, in-app notification, or email.

[0568] Step 10:

[0569] The device receives the news feed sent from the server, arranges for the news feed to be displayed at the time set by the user, and displays a notification to inform the user that a new news feed has arrived.

[0570] Step 11:

[0571] Users open the app and check the delivered news feed. They can browse the latest news articles in the genres they are interested in. The articles displayed are tailored to the user's emotional state, improving the user experience.

[0572] This step allows users to efficiently collect news that interests them and check news articles that correspond to their emotions at an appropriate time.

[0573] Example 2

[0574] 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."

[0575] In modern society, users need to efficiently obtain relevant information from a vast amount of news articles. However, conventional news gathering systems provide information without fully considering the user's interests or emotional state, making it difficult for users to find the information they need. Furthermore, a large amount of news information can have a negative impact on the user's emotions and mental state.

[0576] 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.

[0577] In this invention, the server includes means for receiving input of a news genre and a desired update time period from a user, means for automatically collecting related news articles from multiple news sources on a network based on the received news genre, means for filtering the collected news articles and ranking them based on relevance and recency, means for generating and delivering a customized news feed according to the desired update time period, and means for analyzing the user's emotions and adjusting the news feed based on the user's emotional state, thereby enabling the user to efficiently obtain news of interest and providing a news feed optimized according to the user's emotional state.

[0578] "News genre" refers to a particular category of news that interests a user.

[0579] A "desired update time slot" refers to a time at which a user desires to receive a news feed.

[0580] "News Source" means an online source that is consulted to provide relevant news articles.

[0581] "Filtering" refers to the process of sorting collected news articles based on specific criteria.

[0582] "Ranking" refers to the process of ranking the filtered news articles based on relevance and recency.

[0583] "Customized News Feed" means a list of news items that are individually optimized based on a user's preferences and criteria.

[0584] "Delivery" refers to the process of sending a customized news feed to a user's device.

[0585] An "emotion engine" refers to technology that recognizes a user's emotional state by analyzing voice, facial expressions, input data, etc.

[0586] "Emotional state" refers to a state that indicates a user's current feelings or mood.

[0587] MODE FOR CARRYING OUT THE INVENTION

[0588] The present invention is a system that receives input from users regarding news genres and desired update times, automatically collects relevant news articles from multiple news sources on the network based on the input, filters and ranks them, and then generates and distributes a customized news feed. Furthermore, the system aims to combine an emotion engine that recognizes the user's emotions and adjusts the news articles based on the user's emotional state.

[0589] User Settings

[0590] A user accesses the system and sets the news genre and desired update time. For example, if a user selects "sports news" and "entertainment news" and wants news updates every day at 6:00 PM, this setting information is entered through the application's user interface and sent to the server.

[0591] Receiving and storing configuration information

[0592] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database, allowing each user's settings information to be managed uniquely.

[0593] News gathering

[0594] At the specified update time, the server collects relevant news from news sources on the network based on the configuration information. For example, it sends an API request to retrieve the latest news articles on "sports" and "entertainment" and stores them in a database. Examples of news APIs that can be used include NewsAPI and Google News API.

[0595] Filtering and Ranking

[0596] The server filters the collected news articles and ranks them based on relevance and recency, for example by using a machine learning model (such as Scikit-learn) to rank the news articles, thereby selecting the most relevant articles for the user.

[0597] Customize and deliver news

[0598] Based on the filtered and ranked news articles, the server generates a customized news feed that is delivered to the user's device at the time of their choice.

[0599] Emotional engine regulation

[0600] The server uses an emotion engine that recognizes the user's emotions. The emotion engine analyzes voice, facial expressions, input data, etc. to identify the user's emotions. For example, if the user is showing positive emotions, it will prioritize displaying more optimistic news, and if the user is showing negative emotions, it will prioritize displaying comforting and encouraging news. Specific examples include using the Microsoft Emotion API and Amazon Comprehend.

[0601] Viewing news

[0602] The device receives the customized news feed sent from the server and notifies the user at the specified time. When the user opens the app, the customized news feed is displayed.

[0603] Specific examples

[0604] As a specific example, if User A is interested in "sports news" and "entertainment news" and has set his / her preference to receive news every day at 6:00 PM, the server will save this preference information and start collecting related news from 5:55 PM. After filtering and ranking, a customized news feed will be delivered to User A's device at 6:00 PM. Also, if the emotion engine recognizes that User A has been feeling stressed recently, news that will help him / her relax or unwind will be presented preferentially.

[0605] Example prompts for generative AI models

[0606] The following can be input to the generative AI model:

[0607] Example prompt 1:

[0608] "Write a program that automatically gathers and filters relevant news articles to provide a customized feed to users based on their preferred news genre and update time frame."

[0609] Example prompt 2:

[0610] "Write a program to create a system that recognizes a user's emotions and filters and ranks news based on those emotions."

[0611] This helps the generative AI model generate the program for the entire system.

[0612] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0613] Step 1:

[0614] A user accesses the system and sets the news genre and desired update time period.

[0615] Specific behavior:

[0616] The user enters information into the fields for "news genre" and "update time" through the application's user interface. For example, the user might enter "IT news" and "economic news" at 7:00 every morning. The entered data is sent to the server by pressing the send button.

[0617] Input: User-selected news genre and desired update time

[0618] Output: Configuration information sent to the server

[0619] Step 2:

[0620] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database.

[0621] Specific behavior:

[0622] The server receives user setting information via the REST API. It analyzes the received information and saves it as per-user settings in a database (e.g., MySQL or PostgreSQL). After saving is complete, it generates a save confirmation message for the user and sends it to the device.

[0623] Input: Received setting information

[0624] Output: Setting information saved in the database, save confirmation message

[0625] Step 3:

[0626] When the specified update time arrives, the server collects relevant news from news sources on the network based on the setting information.

[0627] Specific behavior:

[0628] Use Chron jobs or CRON scheduling to start the news gathering process at a specified time (e.g., 6:55 every morning). Send an API request to a news API (e.g., News API, Google News API) to retrieve the latest news in a specified genre. Store the retrieved news data in a database.

[0629] Input: User settings, latest news from news API

[0630] Output: A database containing news data

[0631] Step 4:

[0632] The server filters the collected news articles and ranks them based on relevance and recency.

[0633] Specific behavior:

[0634] Applying filtering algorithms based on news article categories, dates, keywords, etc. Ranking news articles using a machine learning model (e.g., a ranking algorithm built with Scikit-learn). Keeping the ranked results in temporary storage or memory.

[0635] Input: Collected news articles

[0636] Output: Filtered and ranked news articles

[0637] Step 5:

[0638] Based on the filtered and ranked news articles, the server generates a customized news feed and delivers it to the device at the specified time.

[0639] Specific behavior:

[0640] Generate a customized news feed at a specified time (e.g., every morning at 7:00). Deliver the news feed to the user's device using email or push notification APIs (e.g., Firebase Cloud Messaging). Log whether the feed was delivered successfully.

[0641] Input: Customized news article

[0642] Output: News feed delivered to the user's device

[0643] Step 6:

[0644] The server uses an emotion engine that recognizes the user's emotions and readjusts the news article.

[0645] Specific behavior:

[0646] Analyze user emotions using sentiment analysis APIs (e.g., Microsoft Emotion API, Amazon Comprehend). Input voice data and text feedback into the emotion engine to get results. Readjust the content of the news feed based on the emotional state. For example, prioritize positive articles.

[0647] Input: User emotion data

[0648] Output: Rebalanced news feed

[0649] Step 7:

[0650] The terminal receives the customized news feed sent from the server and notifies the user at a specified time.

[0651] Specific behavior:

[0652] The device receives push notifications and emails and notifies the user in the configured way. When the user launches the app, a customized news feed is displayed. User feedback is obtained and sent to the server.

[0653] Input: News feed from the server

[0654] Output: Notified news feed and user feedback

[0655] (Application example 2)

[0656] 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."

[0657] Conventional news feed generation systems allow users to set the news genres they are interested in and the update time slots they desire, but they are unable to customize news articles based on the user's emotional state. As a result, inappropriate news articles may be displayed when the user is feeling stressed or in a particular mood. Therefore, there is a need to provide a more user-friendly news feed by filtering and ranking news articles based on the user's emotional state.

[0658] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving input of a news genre and a desired update time period from a user; means for automatically collecting related news articles from multiple news sources on the network based on the received news genre; means for filtering and ranking the collected news articles; means for generating and delivering a customized news feed according to the desired update time period; and means for using an emotion engine that recognizes the user's emotional state to filter and rank the news articles based on the emotional state. This makes it possible to provide an optimal news feed tailored to the user's emotional state.

[0659] A "news genre" refers to news articles in a particular field or category that interests a user.

[0660] A "desired update time" is a specific time period during which a user would like to receive the latest news feed.

[0661] "News sources" are the websites and databases that provide news articles.

[0662] "Related news articles" refer to news articles collected based on the news genre set by the user.

[0663] "Filtering" refers to the process of filtering out collected news articles that are less relevant to the user.

[0664] "Ranking" is the process of prioritizing a collection of news articles based on their relevance and recency.

[0665] A "customized news feed" is a list of news articles generated and optimized based on a user's news genre and preferred update time frame.

[0666] An "emotion engine" refers to algorithms and techniques for recognizing a user's emotional state and filtering and ranking news articles accordingly.

[0667] The present invention is a system that receives input from users regarding news genres and desired update times, automatically collects relevant news articles from multiple news sources on the network based on the input, filters and ranks them, and then generates a customized news feed. Furthermore, it combines an emotion engine that recognizes the user's emotions, providing a means for filtering and ranking news articles based on the user's emotional state.

[0668] A system for implementing the present invention includes the following components:

[0669] User Settings

[0670] Users can set their preferred news genre and update time through the application. For example, they can select "IT news" or "Economic news" and request news updates every morning at 7:00. This setting information is entered through the smartphone application's user interface and sent to the server.

[0671] Receiving and storing configuration information

[0672] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database. This database is managed using a database management system (DBMS) such as SQLite.

[0673] News gathering

[0674] When the specified update time arrives, the server collects relevant news articles from news sources based on the configuration information. For example, it uses a news API to obtain the latest news articles related to "IT" or "Economy" and stores this data in a database.

[0675] Filtering and Ranking

[0676] The server then filters the collected news articles and ranks them based on relevance and recency, a process that involves processing the data using, for example, the Python programming language and scripting libraries.

[0677] Customize and deliver news

[0678] Based on the filtered and ranked news articles, the server generates a customized news feed and delivers it to the user's device, such as a smartphone or tablet, according to the user's desired update time.

[0679] Emotional engine regulation

[0680] The server is equipped with an emotion engine that recognizes the user's emotions. This engine analyzes the user's facial images and voice data using machine learning models such as TensorFlow to identify the user's emotional state. For example, if the user is showing positive emotions, it will prioritize displaying more optimistic news, and if the user is showing negative emotions, it will prioritize displaying comforting and encouraging news.

[0681] Viewing news

[0682] The device receives the customized news feed sent from the server, and when the user opens the app, the system displays the news feed.

[0683] Specific examples

[0684] As a specific example, suppose User A is interested in "Entertainment" and "Sports" and has set his preferences to receive news every day at 6:00 PM. The server saves this preference information and starts collecting relevant news articles from 5:55 PM. After filtering and ranking, a customized news feed is delivered to User A's device at 6:00 PM. If the emotion engine recognizes that User A has been feeling stressed recently, news that will help him relax and unwind will be presented preferentially.

[0685] Prompt Sentence Examples

[0686] "Generate a smartphone app program using Python that collects the latest news based on the news genre and desired update time specified by the user, and uses an emotion engine to prioritize and display news that matches the user's emotional state."

[0687] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0688] Step 1:

[0689] The user inputs the news genre and desired update time into the application. For example, the user selects "IT news" and "Economic news" and requests news updates every morning at 7:00. This input information is sent to the server via the user interface. The news genre and desired update time are provided as input data, and the server receives this setting information as output.

[0690] Step 2:

[0691] The server stores the information received from the user about the news genre and desired update time period in a database. This process uses a database management system (e.g., SQLite). The server receives user setting information as input data and stores it accurately in the database.

[0692] Step 3:

[0693] At the set update time, the server collects relevant news articles from news sources and sends an API request to get the latest news articles based on the news genre set by the user. For example, the news API can be used to get the latest articles related to "IT" or "Economy" and store the data in a database. The news genre and API endpoint are used as input data, and the list of latest news articles is obtained as output.

[0694] Step 4:

[0695] The server filters the collected news articles and ranks them based on relevance and recency. This process is performed using the Python programming language and data processing libraries (e.g., pandas). It receives a list of collected news articles as input, evaluates the articles based on relevance and recency, and outputs a ranked list.

[0696] Step 5:

[0697] The server generates a customized news feed based on the filtered and ranked news articles and delivers it to the device according to the user's desired update time. The server retrieves the ranked news articles from the database, generates a news feed formatted for the user's interface, and sends it to the smartphone. The ranked articles are used as input data, and the customized news feed is delivered as output.

[0698] Step 6:

[0699] The server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's facial and voice data using TensorFlow's machine learning model to identify the user's emotions. It receives the user's facial expression image or voice data as input data, analyzes the data, and outputs the user's emotional state.

[0700] Step 7:

[0701] The server further filters and ranks the news articles based on the user's emotional state as determined by the emotion engine. For example, if the user is expressing positive emotions, it prioritizes optimistic news, and if the user is expressing negative emotions, it prioritizes comforting and encouraging news. The server takes the emotional state information as input data and re-evaluates and outputs the news articles based on it.

[0702] Step 8:

[0703] The device receives the customized news feed sent from the server and notifies the user at the specified time. When the user opens the app, the customized news feed is displayed. The app receives the news feed from the server as input data and displays it in the user interface as output.

[0704] 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.

[0705] 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.

[0706] 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.

[0707] [Third embodiment]

[0708] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0709] 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.

[0710] 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).

[0711] 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.

[0712] 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.

[0713] 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).

[0714] 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.

[0715] 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.

[0716] 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.

[0717] 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.

[0718] 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.

[0719] 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."

[0720] The present invention provides a system that allows users to set the news genres they are interested in and the update time periods they desire, and provides a news feed that is customized based on that information. Below, an embodiment of this system will be described.

[0721] User Settings

[0722] Users access the system and set their desired news genre and update time. For example, a user can select "IT news" and "economic news" through the application interface and set their preference to receive news at 7:00 a.m. every morning. This setting information is sent to the server.

[0723] Receiving and storing configuration information

[0724] The server receives the news genre and desired update time period sent by the user and stores it in a database, which assigns a unique ID to each user and manages their individual settings.

[0725] News gathering

[0726] When the specified update time arrives, the server collects relevant news from news sources on the network based on the user's settings, for example, by sending an API request to retrieve the latest news articles related to "IT" and "Economy," and stores the news articles in the database.

[0727] News filtering and ranking

[0728] The server filters and ranks the most important articles from the collected news articles based on relevance and recency, a process that results in the most relevant articles being selected for the user.

[0729] Customize and deliver news

[0730] Based on the filtered and ranked news articles, the server generates a customized news feed, which is delivered to the device at the update time specified by the user.

[0731] Viewing news

[0732] The device receives the news feed sent from the server and notifies the user at the set time. When the user opens the app, the customized news feed is displayed. For example, a user can open the app on their way to work and check the latest "IT news" and "economic news."

[0733] Specific examples

[0734] As a concrete example, suppose User A is interested in "sports news" and "entertainment news" and has set up a daily news feed at 6:00 PM. The server saves this setting information and starts collecting relevant news from 5:55 PM. After filtering and ranking, the customized news feed is delivered to User A's device at 6:00 PM. User A can easily check the latest sports and entertainment news on his / her way home.

[0735] The above is an embodiment of the system of the present invention, which enables users to efficiently collect news that matches their interests and check it in a timely manner at an appropriate time.

[0736] The processing flow will be explained below.

[0737] Step 1:

[0738] When the user installs the application and starts it for the first time, they set the news genre and desired update time. Specifically, they select "IT news" and "Economic news" and want news updates every morning at 7:00. The setting information is entered through the application's user interface and sent to the server.

[0739] Step 2:

[0740] The server receives the setting information sent by the user. The received information includes the user's ID, selected news genre, and desired update time period. The server stores this information in a database. This allows the setting information to be managed uniquely for each user, and the data required for subsequent processing is retained.

[0741] Step 3:

[0742] A few minutes before the specified update time (in this case, 7:00 every morning), the server starts collecting news based on the configuration information. Specifically, it sends API requests to multiple reliable news sources for the selected news genres ("IT" and "Economy"), and retrieves the latest news articles.

[0743] Step 4:

[0744] The server filters the retrieved news articles, taking into account criteria such as the relevance, recency, and reliability of the news articles. For example, inappropriate content and duplicate articles are filtered out, and the most relevant news is selected.

[0745] Step 5:

[0746] The server ranks the filtered news articles. The ranking criteria take into account the importance and timeliness of the article. The more important and latest news are ranked higher and displayed preferentially.

[0747] Step 6:

[0748] The server generates a customized news feed from the filtered and ranked news articles, which is configured to include only news genres selected by the user.

[0749] Step 7:

[0750] At the specified update time (in this case, every morning at 7:00), the server delivers the generated customized news feed to the user's device via push notification, email, in-app notification, or other methods depending on the user's settings.

[0751] Step 8:

[0752] The device receives the news feed sent from the server and arranges for the news feed to be displayed at a time set by the user. For example, an application can automatically display a notification to inform the user that a new news feed has arrived.

[0753] Step 9:

[0754] Users open the application at the specified time and check the delivered news feed. Users can efficiently browse the latest news articles in the genres they are interested in. They can select articles that interest them and read detailed information.

[0755] This series of steps allows users to efficiently collect news that interests them and check it at an appropriate time, significantly reducing the time it takes for users to gather news and providing timely access to important information.

[0756] Example 1

[0757] 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."

[0758] In modern society, people have access to a vast amount of information. However, it is difficult to efficiently collect only the information of interest and review it in a timely manner. Conventional information collection systems lack the technology to provide customized information feeds based on specified information categories and update times. They also have limited functionality for filtering and ranking information items based on relevance and recency. Therefore, there is a need to develop a system that provides users with the most appropriate information at the right time.

[0759] 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.

[0760] In this invention, the server includes means for receiving input of an information category and a desired delivery time period from a user, means for automatically collecting related information items from multiple information sources on a network based on the received information category, means for filtering and ranking the collected information items, and means for generating and delivering a customized information feed tailored to the desired delivery time period, thereby enabling users to efficiently collect information that matches their interests and view it in a timely manner at an appropriate time.

[0761] "User" means a user of the system who intends to receive information based on his or her interests.

[0762] An "information category" is a division of a particular type of information that interests a user, such as a news genre or topic area.

[0763] The "desired delivery time period" is the range of time within which the user can receive information, and a specific time or time period can be specified.

[0764] "Multiple information sources on the network" refers to various sources accessible via the Internet, including news sites, blogs, APIs, etc.

[0765] "Relevant information items" refer to specific news articles or data entries collected based on the information categories received.

[0766] "Automatic collection methods" are mechanisms by which programs automatically obtain information based on user settings, such as using web crawlers or API requests.

[0767] "Filtering" is the process of selecting useful information items from collected information based on specific criteria.

[0768] "Ranking" is the process of prioritizing filtered information items based on relevance and recency.

[0769] A "customized information feed" is a collection of news and data delivered as a personalized stream of information generated according to a user's preferences.

[0770] The "means of delivery" refers to a method for sending the generated information feed to the user's terminal, and includes email, push notification, a dedicated application, and the like.

[0771] The present invention provides a system that allows users to set information categories of interest and desired delivery time periods, and provides a customized information feed based on that information. The following describes an embodiment of this system.

[0772] User Settings

[0773] Users access the system and set the information category and desired delivery time. For example, a user can select "IT news" and "economic news" through the application interface and set the information to be delivered at 7:00 every morning. This setting information is sent to the server.

[0774] Receiving and storing configuration information

[0775] The server receives the information category and desired delivery time slot sent by the user and stores it in a database. Specifically, it uses a database such as MySQL or PostgreSQL to manage user IDs, information categories, and delivery time slots.

[0776] Collection of information

[0777] As the specified delivery time approaches, the server collects relevant information from information sources on the network based on the user's settings. Specifically, it sends API requests to obtain the latest information items related to "IT" and "Economy" and stores the information in a database. The APIs used for this purpose are, for example, NewsAPI and NY Times API.

[0778] Filtering and ranking information

[0779] The server then filters and ranks the collected information items based on their relevance and recency. This process uses a machine learning algorithm based on Python's scikit-learn library. Specifically, it performs text analysis on the information items, calculates a relevance score, and assigns a ranking.

[0780] Personalized information delivery

[0781] Based on the filtered and ranked information items, the server generates a customized information feed in HTML or JSON format, customizing the content for each user, and then sends the generated information feed to the user's device.

[0782] Displaying Information

[0783] The device receives the information feed sent from the server and notifies the user at the set time. For example, the push notification function can be used to display a message saying, "The latest IT and economic news has been updated" at a specified time. When the user clicks on this notification, the app opens and the customized information feed is displayed.

[0784] Specific examples

[0785] As a concrete example, suppose User A is interested in "Sports News" and "Entertainment News" and has set up a schedule to receive information at 6:00 PM. The server saves this setting and starts collecting relevant information from 5:55 PM. After filtering and ranking, a customized information feed is delivered to User A's device at 6:00 PM. User A receives a notification on his / her way home and can open the app to check the latest sports and entertainment news.

[0786] Examples of prompt statements

[0787] An example of a prompt to be input to the generative AI model is as follows:

[0788] Explain how a system that provides a customized information feed works, allowing users to set the information categories they are interested in and the time slots they want delivered. For example, explain in detail how a system works if a user selects "IT news" and "Economic news" and sets the time slots to receive them every morning at 7:00.

[0789] The above is an embodiment of the system of the present invention. This system enables users to efficiently collect information that matches their interests and check it in a timely manner at an appropriate time.

[0790] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0791] Step 1:

[0792] The user opens the application and enters the information category and desired delivery time slot. Specifically, the user selects "IT News" or "Economic News" in the application interface and sets "7:00" as the delivery time slot. Once this setting information has been entered, the user presses the "Set" button to send it to the server. The input here is the information category and delivery time slot data, and the output is data sent to the server.

[0793] Step 2:

[0794] The server receives the information category and desired delivery time setting information sent by the user. It then stores the information in a database such as MySQL or PostgreSQL. Specifically, data including the user ID, information category, and delivery time is stored and managed in the database. The input is the user setting data, and the output is the operation of saving it to the database.

[0795] Step 3:

[0796] As the specified delivery time approaches, the server starts the information collection process. For example, if a user has set their preference to receive news at 7:00 in the morning, the server will send a request to a news API (such as NewsAPI or NY Times API) at 6:55 to collect the latest information on "IT" and "Economy." The collected data is then stored in a database as is. The input is the API request, and the output is the data of the retrieved information items.

[0797] Step 4:

[0798] The server filters and ranks the collected information items. Specifically, it uses the scikit-learn library to perform text analysis, selects articles that are highly relevant to the user's preferences, and calculates an importance score to rank them. This process uses relevance and recency as criteria. The input is the collected information items, and the output is the filtered and ranked information items.

[0799] Step 5:

[0800] Based on the filtered and ranked information items, the server generates a customized information feed. The generated information feed is created in HTML or JSON format and is customized to have different content for each user. Once generated, the information feed is sent to the user's device. The input is the filtered and ranked information items, and the output is the customized information feed.

[0801] Step 6:

[0802] The device receives the information feed sent from the server and notifies the user at the set time. The push notification function is used to notify the user of information updates. When the user clicks on the notification, the app opens and a customized information feed is displayed. The input is the information feed from the server, and the output is the customized information feed displayed to the user.

[0803] The above is the processing flow and specific operation of this system's program. By clarifying the detailed input and output at each step, as well as the specific content of data processing and data calculation, users can efficiently collect information that matches their interests and check it at a specified time.

[0804] (Application example 1)

[0805] 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."

[0806] In today's information society, users are required to access a vast amount of information, but it is extremely difficult to select the information that is important to them from that. They are also unable to receive information in a timely manner, and lack the means to efficiently collect and review information at an appropriate time. Furthermore, despite the increasing diversity of information formats, conventional systems tend to be limited to text-based information. There is a need to solve these issues and provide users with useful information at the appropriate time.

[0807] 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.

[0808] In this invention, the server includes means for receiving input of an information category and a desired update time period from a user, means for automatically collecting related information from multiple information sources on a communication network based on the received information category, means for filtering and ranking the collected information, means for generating and distributing a customized information feed according to the desired update time period, means for scheduling to notify the smart device of the customized information, and means for processing information in both video and text format when generating the customized information feed. This allows users to efficiently collect information that matches their interests and check it in a timely manner at an appropriate time.

[0809] An "information category" represents a particular subject or genre that interests a user.

[0810] "Update time period" refers to a specific time period during which a user wishes to receive updates and notifications about the information they desire.

[0811] "Communications network" refers collectively to the network system used to collect and transmit information.

[0812] "Source" refers to the source or service that provides information, such as an internet news site or data provider.

[0813] "Filtering" refers to the process of selecting necessary information from collected information based on specific criteria.

[0814] "Ranking" refers to the process of prioritizing filtered information based on specific criteria.

[0815] "Information Feed" refers to a stream of customized information provided to a user.

[0816] "Scheduling" refers to the process of planning the execution of a particular task or process at a predetermined time.

[0817] "Smart devices" refer to mobile terminals and wearable devices that have Internet connectivity and can manage and display information.

[0818] "Video format" refers to a media format that contains moving images.

[0819] "Text format" refers to a media format that contains text or textual information.

[0820] This invention is a system that provides a customized information feed based on information that a user sets by setting the information categories of interest and the desired update time period.

[0821] User Settings

[0822] The user accesses the system and sets the information category and desired update time. For example, the user selects "News" and "Entertainment" through the application interface and sets that they want to receive information every morning at 7:00. This setting information is sent to the server.

[0823] Receiving and storing configuration information

[0824] The server receives the information category and desired update time period sent by the user and stores it in a database. This assigns a unique ID to each user and manages individual settings information.

[0825] Collection of information

[0826] At the specified update time, the server collects relevant information from sources on the network based on the user's settings, for example by sending an API request to get the latest news and entertainment information, and stores that information in the database.

[0827] Filtering and ranking information

[0828] The server then filters and ranks the most important information from the collected data based on relevance and recency, resulting in the selection of the most relevant information for the user.

[0829] Personalized information delivery

[0830] Based on the filtered and ranked information, the server generates a customized information feed, which is then delivered to the device at the update time specified by the user.

[0831] Displaying Information

[0832] The device receives the information feed sent from the server and notifies the user at the set time. When the user opens the app, the customized information feed is displayed. For example, a user can open the app on their way to work to check the latest "News" and "Entertainment."

[0833] Specific actions

[0834] The system operates using multiple software components. It uses API requests to collect information, a Python scheduling library (schedule), and a library for sending HTTP requests (requests). This allows it to filter the collected information and deliver it at a time specified by the user.

[0835] For example, suppose User A is interested in "sports" and "technology" and has set up a preference to receive information every day at 6:00 PM. The server saves this preference information and starts collecting related information from 5:55 PM. After filtering and ranking, the customized information feed is delivered to User A's device at 6:00 PM. User A can easily check the latest sports news and technology-related information in the evening.

[0836] Prompt Sentence Examples

[0837] You want to create an application that generates a customized news feed based on the user's interest categories and delivers it at a specified time. Provide a Python program that includes the following elements:

[0838] 1. User interface for setting news categories and update times.

[0839] 2. Collect news of a specified category from sources.

[0840] 3. Filter the collected news and rank them based on recency.

[0841] 4. The filtered news feed is sent to the user's device at the specified time.

[0842] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0843] Step 1:

[0844] The user sets the information categories they are interested in and the desired update time slots through the application interface. The information categories (e.g., "News" or "Entertainment") and update time slots (e.g., every morning at 7:00) entered by the user are sent to the server from the settings screen.

[0845] Input: User-defined information category and desired update time period

[0846] Output: User preference data sent to the server

[0847] Step 2:

[0848] The server receives the setting information sent by the user and stores it in a database, which assigns a unique ID to each user and manages individual setting information.

[0849] Input: User-defined data (information category and update time period)

[0850] Output: User preferences stored in the database

[0851] Step 3:

[0852] When the specified update time arrives, the server collects relevant information from multiple sources on the network based on the user's settings. The server sends an API request to collect information and obtains the latest content related to "News" and "Entertainment."

[0853] Input: User setting information (information category and update time period), API request

[0854] Output: Collected information

[0855] Step 4:

[0856] The server filters the collected information and ranks it based on relevance and recency. The server automatically analyzes the information and selects the most relevant information for the user.

[0857] Input: Collected information

[0858] Output: Filtered and ranked information

[0859] Step 5:

[0860] The server generates a customized information feed based on the filtered and ranked information, and the generated information feed is delivered to the terminal at the update time specified by the user.

[0861] Input: Filtered and ranked information

[0862] Output: Customized information feed

[0863] Step 6:

[0864] The device receives the customized information feed sent from the server and notifies the user at the specified update time. When the user opens the app on the device, the customized information feed is displayed.

[0865] Input: Customized information feed

[0866] Output: A customized information feed displayed on your device

[0867] Step 7:

[0868] Users can open their devices on their way to work or in their spare time to check their customized information feed, allowing them to efficiently gather the latest information that matches their interests and view it at the appropriate time.

[0869] Input: A customized information feed displayed on your device

[0870] Output: Customized information for the user to review

[0871] 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.

[0872] The present invention is a system that receives input from a user regarding news genres and desired update times, automatically collects relevant news articles from multiple news sources on a network based on the input, filters and ranks them, and then generates a customized news feed. Furthermore, it incorporates an emotion engine that recognizes the user's emotions, providing a means for filtering and ranking news articles based on the user's emotional state. Specific implementation methods of the present invention are described below.

[0873] User Settings

[0874] Users access the system and set the news genre and desired update time. For example, they may select "IT news" and "Economic news" and want news updates every morning at 7:00. This setting information is entered through the application's user interface and sent to the server.

[0875] Receiving and storing configuration information

[0876] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database, allowing each user's settings information to be managed uniquely.

[0877] News gathering

[0878] At the specified update time, the server collects relevant news from news sources on the network based on the configuration information, for example, sending an API request to get the latest news articles on "IT" and "Economy" and stores them in the database.

[0879] Filtering and Ranking

[0880] The server filters the collected news articles and ranks them based on relevance and recency, a process that selects the most relevant articles for the user.

[0881] Customize and deliver news

[0882] Based on the filtered and ranked news articles, the server generates a customized news feed that is delivered to the user's device at the time of their choice.

[0883] Emotional engine regulation

[0884] The server uses an emotion engine that recognizes the user's emotions. The emotion engine analyzes voice, facial expressions, input data, etc. to identify the user's emotions. For example, if the user is showing positive emotions, it will prioritize displaying more optimistic news, and if the user is showing negative emotions, it will prioritize displaying comforting and encouraging news.

[0885] Viewing news

[0886] The device receives the customized news feed sent from the server and notifies the user at the specified time. When the user opens the app, the customized news feed is displayed.

[0887] Specific examples

[0888] As a specific example, suppose User A is interested in "sports news" and "entertainment news" and has set up a daily news feed at 6:00 PM. The server saves this setting information and starts collecting relevant news from 5:55 PM. After filtering and ranking, a customized news feed is delivered to User A's device at 6:00 PM. If the emotion engine recognizes that User A has been feeling stressed recently, news that helps with relaxation and distraction will be presented preferentially.

[0889] This invention allows users to efficiently collect news that interest them and check it at an appropriate time. Furthermore, the introduction of an emotion engine provides news articles that match the user's current emotional state, further improving the user experience.

[0890] The processing flow will be explained below.

[0891] Step 1:

[0892] When a user installs the application and starts it for the first time, they select the news genre and desired update time. For example, they may select "IT news" and "Economic news" and want news updates every morning at 7:00. This setting information is entered through the application's user interface and sent to the server.

[0893] Step 2:

[0894] The server receives the setting information sent by the user. The received information includes the user's ID, selected news genre, and desired update time period. This information is stored in a database and managed uniquely for each user.

[0895] Step 3:

[0896] A few minutes before the specified update time (e.g., 6:55), the server starts collecting relevant news based on the configuration information. Specifically, it sends API requests to retrieve the latest news articles related to "IT" and "Economy" from multiple reliable news sources. The retrieved news articles are then stored in a database.

[0897] Step 4:

[0898] The server filters the collected news articles based on criteria such as the article's relevance, recency, and credibility, for example, to exclude articles that the user has already seen or that are duplicates.

[0899] Step 5:

[0900] The server then ranks the filtered news articles, taking into account the importance and timeliness of the articles. The more important and up-to-date news is ranked higher and displayed preferentially.

[0901] Step 6:

[0902] The server uses an emotion engine to recognize the user's emotions. The emotion engine identifies the user's emotions through voice analysis, facial expression analysis, text analysis, etc. For example, if the user's recent typing history or voice tone indicates a positive emotion, the corresponding news article will be selected.

[0903] Step 7:

[0904] Based on the results of the emotion engine, the server reprioritizes news articles: for example, if a user expresses negative emotions, news articles that bring encouragement and hope will be prioritized.

[0905] Step 8:

[0906] Based on the filtered and ranked news articles, the server generates a customized news feed that is tailored to the user's preferred update timeframe.

[0907] Step 9:

[0908] At the specified update time (e.g., 7:00), the server delivers the generated customized news feed to the user's device via push notification, in-app notification, or email.

[0909] Step 10:

[0910] The device receives the news feed sent from the server, arranges for the news feed to be displayed at the time set by the user, and displays a notification to inform the user that a new news feed has arrived.

[0911] Step 11:

[0912] Users open the app and check the delivered news feed. They can browse the latest news articles in the genres they are interested in. The articles displayed are tailored to the user's emotional state, improving the user experience.

[0913] This step allows users to efficiently collect news that interests them and check news articles that correspond to their emotions at an appropriate time.

[0914] Example 2

[0915] 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."

[0916] In modern society, users need to efficiently obtain relevant information from a vast amount of news articles. However, conventional news gathering systems provide information without fully considering the user's interests or emotional state, making it difficult for users to find the information they need. Furthermore, a large amount of news information can have a negative impact on the user's emotions and mental state.

[0917] 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.

[0918] In this invention, the server includes means for receiving input of a news genre and a desired update time period from a user, means for automatically collecting related news articles from multiple news sources on a network based on the received news genre, means for filtering the collected news articles and ranking them based on relevance and recency, means for generating and delivering a customized news feed according to the desired update time period, and means for analyzing the user's emotions and adjusting the news feed based on the user's emotional state, thereby enabling the user to efficiently obtain news of interest and providing a news feed optimized according to the user's emotional state.

[0919] "News genre" refers to a particular category of news that interests a user.

[0920] A "desired update time slot" refers to a time at which a user desires to receive a news feed.

[0921] "News Source" means an online source that is consulted to provide relevant news articles.

[0922] "Filtering" refers to the process of sorting collected news articles based on specific criteria.

[0923] "Ranking" refers to the process of ranking the filtered news articles based on relevance and recency.

[0924] "Customized News Feed" means a list of news items that are individually optimized based on a user's preferences and criteria.

[0925] "Delivery" refers to the process of sending a customized news feed to a user's device.

[0926] An "emotion engine" refers to technology that recognizes a user's emotional state by analyzing voice, facial expressions, input data, etc.

[0927] "Emotional state" refers to a state that indicates a user's current feelings or mood.

[0928] MODE FOR CARRYING OUT THE INVENTION

[0929] The present invention is a system that receives input from users regarding news genres and desired update times, automatically collects relevant news articles from multiple news sources on the network based on the input, filters and ranks them, and then generates and distributes a customized news feed. Furthermore, the system aims to combine an emotion engine that recognizes the user's emotions and adjusts the news articles based on the user's emotional state.

[0930] User Settings

[0931] A user accesses the system and sets the news genre and desired update time. For example, if a user selects "sports news" and "entertainment news" and wants news updates every day at 6:00 PM, this setting information is entered through the application's user interface and sent to the server.

[0932] Receiving and storing configuration information

[0933] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database, allowing each user's settings information to be managed uniquely.

[0934] News gathering

[0935] At the specified update time, the server collects relevant news from news sources on the network based on the configuration information. For example, it sends an API request to retrieve the latest news articles on "sports" and "entertainment" and stores them in a database. Examples of news APIs that can be used include NewsAPI and Google News API.

[0936] Filtering and Ranking

[0937] The server filters the collected news articles and ranks them based on relevance and recency, for example by using a machine learning model (such as Scikit-learn) to rank the news articles, thereby selecting the most relevant articles for the user.

[0938] Customize and deliver news

[0939] Based on the filtered and ranked news articles, the server generates a customized news feed that is delivered to the user's device at the time of their choice.

[0940] Emotional engine regulation

[0941] The server uses an emotion engine that recognizes the user's emotions. The emotion engine analyzes voice, facial expressions, input data, etc. to identify the user's emotions. For example, if the user is showing positive emotions, it will prioritize displaying more optimistic news, and if the user is showing negative emotions, it will prioritize displaying comforting and encouraging news. Specific examples include using the Microsoft Emotion API and Amazon Comprehend.

[0942] Viewing news

[0943] The device receives the customized news feed sent from the server and notifies the user at the specified time. When the user opens the app, the customized news feed is displayed.

[0944] Specific examples

[0945] As a specific example, if User A is interested in "sports news" and "entertainment news" and has set his / her preference to receive news every day at 6:00 PM, the server will save this preference information and start collecting related news from 5:55 PM. After filtering and ranking, a customized news feed will be delivered to User A's device at 6:00 PM. Also, if the emotion engine recognizes that User A has been feeling stressed recently, news that will help him / her relax or unwind will be presented preferentially.

[0946] Example prompts for generative AI models

[0947] The following can be input to the generative AI model:

[0948] Example prompt 1:

[0949] "Write a program that automatically gathers and filters relevant news articles to provide a customized feed to users based on their preferred news genre and update time frame."

[0950] Example prompt 2:

[0951] "Write a program to create a system that recognizes a user's emotions and filters and ranks news based on those emotions."

[0952] This helps the generative AI model generate the program for the entire system.

[0953] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0954] Step 1:

[0955] A user accesses the system and sets the news genre and desired update time period.

[0956] Specific behavior:

[0957] The user enters information into the fields for "news genre" and "update time" through the application's user interface. For example, the user might enter "IT news" and "economic news" at 7:00 every morning. The entered data is sent to the server by pressing the send button.

[0958] Input: User-selected news genre and desired update time

[0959] Output: Configuration information sent to the server

[0960] Step 2:

[0961] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database.

[0962] Specific behavior:

[0963] The server receives user setting information via the REST API. It analyzes the received information and saves it as per-user settings in a database (e.g., MySQL or PostgreSQL). After saving is complete, it generates a save confirmation message for the user and sends it to the device.

[0964] Input: Received setting information

[0965] Output: Setting information saved in the database, save confirmation message

[0966] Step 3:

[0967] When the specified update time arrives, the server collects relevant news from news sources on the network based on the setting information.

[0968] Specific behavior:

[0969] Use Chron jobs or CRON scheduling to start the news gathering process at a specified time (e.g., 6:55 every morning). Send an API request to a news API (e.g., News API, Google News API) to retrieve the latest news in a specified genre. Store the retrieved news data in a database.

[0970] Input: User settings, latest news from news API

[0971] Output: A database containing news data

[0972] Step 4:

[0973] The server filters the collected news articles and ranks them based on relevance and recency.

[0974] Specific behavior:

[0975] Applying filtering algorithms based on news article categories, dates, keywords, etc. Ranking news articles using a machine learning model (e.g., a ranking algorithm built with Scikit-learn). Keeping the ranked results in temporary storage or memory.

[0976] Input: Collected news articles

[0977] Output: Filtered and ranked news articles

[0978] Step 5:

[0979] Based on the filtered and ranked news articles, the server generates a customized news feed and delivers it to the device at the specified time.

[0980] Specific behavior:

[0981] Generate a customized news feed at a specified time (e.g., every morning at 7:00). Deliver the news feed to the user's device using email or push notification APIs (e.g., Firebase Cloud Messaging). Log whether the feed was delivered successfully.

[0982] Input: Customized news article

[0983] Output: News feed delivered to the user's device

[0984] Step 6:

[0985] The server uses an emotion engine that recognizes the user's emotions and readjusts the news article.

[0986] Specific behavior:

[0987] Analyze user emotions using sentiment analysis APIs (e.g., Microsoft Emotion API, Amazon Comprehend). Input voice data and text feedback into the emotion engine to get results. Readjust the content of the news feed based on the emotional state. For example, prioritize positive articles.

[0988] Input: User emotion data

[0989] Output: Rebalanced news feed

[0990] Step 7:

[0991] The terminal receives the customized news feed sent from the server and notifies the user at a specified time.

[0992] Specific behavior:

[0993] The device receives push notifications and emails and notifies the user in the configured way. When the user launches the app, a customized news feed is displayed. User feedback is obtained and sent to the server.

[0994] Input: News feed from the server

[0995] Output: Notified news feed and user feedback

[0996] (Application example 2)

[0997] 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."

[0998] Conventional news feed generation systems allow users to set the news genres they are interested in and the update time slots they desire, but they are unable to customize news articles based on the user's emotional state. As a result, inappropriate news articles may be displayed when the user is feeling stressed or in a particular mood. Therefore, there is a need to provide a more user-friendly news feed by filtering and ranking news articles based on the user's emotional state.

[0999] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving input of a news genre and a desired update time period from a user; means for automatically collecting related news articles from multiple news sources on the network based on the received news genre; means for filtering and ranking the collected news articles; means for generating and delivering a customized news feed according to the desired update time period; and means for using an emotion engine that recognizes the user's emotional state to filter and rank the news articles based on the emotional state. This makes it possible to provide an optimal news feed tailored to the user's emotional state.

[1000] A "news genre" refers to news articles in a particular field or category that interests a user.

[1001] A "desired update time" is a specific time period during which a user would like to receive the latest news feed.

[1002] "News sources" are the websites and databases that provide news articles.

[1003] "Related news articles" refer to news articles collected based on the news genre set by the user.

[1004] "Filtering" refers to the process of filtering out collected news articles that are less relevant to the user.

[1005] "Ranking" is the process of prioritizing a collection of news articles based on their relevance and recency.

[1006] A "customized news feed" is a list of news articles generated and optimized based on a user's news genre and preferred update time frame.

[1007] An "emotion engine" refers to algorithms and techniques for recognizing a user's emotional state and filtering and ranking news articles accordingly.

[1008] The present invention is a system that receives input from users regarding news genres and desired update times, automatically collects relevant news articles from multiple news sources on the network based on the input, filters and ranks them, and then generates a customized news feed. Furthermore, it combines an emotion engine that recognizes the user's emotions, providing a means for filtering and ranking news articles based on the user's emotional state.

[1009] A system for implementing the present invention includes the following components:

[1010] User Settings

[1011] Users can set their preferred news genre and update time through the application. For example, they can select "IT news" or "Economic news" and request news updates every morning at 7:00. This setting information is entered through the smartphone application's user interface and sent to the server.

[1012] Receiving and storing configuration information

[1013] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database. This database is managed using a database management system (DBMS) such as SQLite.

[1014] News gathering

[1015] When the specified update time arrives, the server collects relevant news articles from news sources based on the configuration information. For example, it uses a news API to obtain the latest news articles related to "IT" or "Economy" and stores this data in a database.

[1016] Filtering and Ranking

[1017] The server then filters the collected news articles and ranks them based on relevance and recency, a process that involves processing the data using, for example, the Python programming language and scripting libraries.

[1018] Customize and deliver news

[1019] Based on the filtered and ranked news articles, the server generates a customized news feed and delivers it to the user's device, such as a smartphone or tablet, according to the user's desired update time.

[1020] Emotional engine regulation

[1021] The server is equipped with an emotion engine that recognizes the user's emotions. This engine analyzes the user's facial images and voice data using machine learning models such as TensorFlow to identify the user's emotional state. For example, if the user is showing positive emotions, it will prioritize displaying more optimistic news, and if the user is showing negative emotions, it will prioritize displaying comforting and encouraging news.

[1022] Viewing news

[1023] The device receives the customized news feed sent from the server, and when the user opens the app, the system displays the news feed.

[1024] Specific examples

[1025] As a specific example, suppose User A is interested in "Entertainment" and "Sports" and has set his preferences to receive news every day at 6:00 PM. The server saves this preference information and starts collecting relevant news articles from 5:55 PM. After filtering and ranking, a customized news feed is delivered to User A's device at 6:00 PM. If the emotion engine recognizes that User A has been feeling stressed recently, news that will help him relax and unwind will be presented preferentially.

[1026] Prompt Sentence Examples

[1027] "Generate a smartphone app program using Python that collects the latest news based on the news genre and desired update time specified by the user, and uses an emotion engine to prioritize and display news that matches the user's emotional state."

[1028] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1029] Step 1:

[1030] The user inputs the news genre and desired update time into the application. For example, the user selects "IT news" and "Economic news" and requests news updates every morning at 7:00. This input information is sent to the server via the user interface. The news genre and desired update time are provided as input data, and the server receives this setting information as output.

[1031] Step 2:

[1032] The server stores the information received from the user about the news genre and desired update time period in a database. This process uses a database management system (e.g., SQLite). The server receives user setting information as input data and stores it accurately in the database.

[1033] Step 3:

[1034] At the set update time, the server collects relevant news articles from news sources and sends an API request to get the latest news articles based on the news genre set by the user. For example, the news API can be used to get the latest articles related to "IT" or "Economy" and store the data in a database. The news genre and API endpoint are used as input data, and the list of latest news articles is obtained as output.

[1035] Step 4:

[1036] The server filters the collected news articles and ranks them based on relevance and recency. This process is performed using the Python programming language and data processing libraries (e.g., pandas). It receives a list of collected news articles as input, evaluates the articles based on relevance and recency, and outputs a ranked list.

[1037] Step 5:

[1038] The server generates a customized news feed based on the filtered and ranked news articles and delivers it to the device according to the user's desired update time. The server retrieves the ranked news articles from the database, generates a news feed formatted for the user's interface, and sends it to the smartphone. The ranked articles are used as input data, and the customized news feed is delivered as output.

[1039] Step 6:

[1040] The server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's facial and voice data using TensorFlow's machine learning model to identify the user's emotions. It receives the user's facial expression image or voice data as input data, analyzes the data, and outputs the user's emotional state.

[1041] Step 7:

[1042] The server further filters and ranks the news articles based on the user's emotional state as determined by the emotion engine. For example, if the user is expressing positive emotions, it prioritizes optimistic news, and if the user is expressing negative emotions, it prioritizes comforting and encouraging news. The server takes the emotional state information as input data and re-evaluates and outputs the news articles based on it.

[1043] Step 8:

[1044] The device receives the customized news feed sent from the server and notifies the user at the specified time. When the user opens the app, the customized news feed is displayed. The app receives the news feed from the server as input data and displays it in the user interface as output.

[1045] 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.

[1046] 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.

[1047] 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.

[1048] [Fourth embodiment]

[1049] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1050] 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.

[1051] 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).

[1052] 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.

[1053] 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.

[1054] 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).

[1055] 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.

[1056] 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.

[1057] 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.

[1058] 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.

[1059] 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.

[1060] 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.

[1061] 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."

[1062] The present invention provides a system that allows users to set the news genres they are interested in and the update time periods they desire, and provides a news feed that is customized based on that information. Below, an embodiment of this system will be described.

[1063] User Settings

[1064] Users access the system and set their desired news genre and update time. For example, a user can select "IT news" and "economic news" through the application interface and set their preference to receive news at 7:00 a.m. every morning. This setting information is sent to the server.

[1065] Receiving and storing configuration information

[1066] The server receives the news genre and desired update time period sent by the user and stores it in a database, which assigns a unique ID to each user and manages their individual settings.

[1067] News gathering

[1068] When the specified update time arrives, the server collects relevant news from news sources on the network based on the user's settings, for example, by sending an API request to retrieve the latest news articles related to "IT" and "Economy," and stores the news articles in the database.

[1069] News filtering and ranking

[1070] The server filters and ranks the most important articles from the collected news articles based on relevance and recency, a process that results in the most relevant articles being selected for the user.

[1071] Customize and deliver news

[1072] Based on the filtered and ranked news articles, the server generates a customized news feed, which is delivered to the device at the update time specified by the user.

[1073] Viewing news

[1074] The device receives the news feed sent from the server and notifies the user at the set time. When the user opens the app, the customized news feed is displayed. For example, a user can open the app on their way to work and check the latest "IT news" and "economic news."

[1075] Specific examples

[1076] As a concrete example, suppose User A is interested in "sports news" and "entertainment news" and has set up a daily news feed at 6:00 PM. The server saves this setting information and starts collecting relevant news from 5:55 PM. After filtering and ranking, the customized news feed is delivered to User A's device at 6:00 PM. User A can easily check the latest sports and entertainment news on his / her way home.

[1077] The above is an embodiment of the system of the present invention, which enables users to efficiently collect news that matches their interests and check it in a timely manner at an appropriate time.

[1078] The processing flow will be explained below.

[1079] Step 1:

[1080] When the user installs the application and starts it for the first time, they set the news genre and desired update time. Specifically, they select "IT news" and "Economic news" and want news updates every morning at 7:00. The setting information is entered through the application's user interface and sent to the server.

[1081] Step 2:

[1082] The server receives the setting information sent by the user. The received information includes the user's ID, selected news genre, and desired update time period. The server stores this information in a database. This allows the setting information to be managed uniquely for each user, and the data required for subsequent processing is retained.

[1083] Step 3:

[1084] A few minutes before the specified update time (in this case, 7:00 every morning), the server starts collecting news based on the configuration information. Specifically, it sends API requests to multiple reliable news sources for the selected news genres ("IT" and "Economy"), and retrieves the latest news articles.

[1085] Step 4:

[1086] The server filters the retrieved news articles, taking into account criteria such as the relevance, recency, and reliability of the news articles. For example, inappropriate content and duplicate articles are filtered out, and the most relevant news is selected.

[1087] Step 5:

[1088] The server ranks the filtered news articles. The ranking criteria take into account the importance and timeliness of the article. The more important and latest news are ranked higher and displayed preferentially.

[1089] Step 6:

[1090] The server generates a customized news feed from the filtered and ranked news articles, which is configured to include only news genres selected by the user.

[1091] Step 7:

[1092] At the specified update time (in this case, every morning at 7:00), the server delivers the generated customized news feed to the user's device via push notification, email, in-app notification, or other methods depending on the user's settings.

[1093] Step 8:

[1094] The device receives the news feed sent from the server and arranges for the news feed to be displayed at a time set by the user. For example, an application can automatically display a notification to inform the user that a new news feed has arrived.

[1095] Step 9:

[1096] Users open the application at the specified time and check the delivered news feed. Users can efficiently browse the latest news articles in the genres they are interested in. They can select articles that interest them and read detailed information.

[1097] This series of steps allows users to efficiently collect news that interests them and check it at an appropriate time, significantly reducing the time it takes for users to gather news and providing timely access to important information.

[1098] Example 1

[1099] 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."

[1100] In modern society, people have access to a vast amount of information. However, it is difficult to efficiently collect only the information of interest and review it in a timely manner. Conventional information collection systems lack the technology to provide customized information feeds based on specified information categories and update times. They also have limited functionality for filtering and ranking information items based on relevance and recency. Therefore, there is a need to develop a system that provides users with the most appropriate information at the right time.

[1101] 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.

[1102] In this invention, the server includes means for receiving input of an information category and a desired delivery time period from a user, means for automatically collecting related information items from multiple information sources on a network based on the received information category, means for filtering and ranking the collected information items, and means for generating and delivering a customized information feed tailored to the desired delivery time period, thereby enabling users to efficiently collect information that matches their interests and view it in a timely manner at an appropriate time.

[1103] "User" means a user of the system who intends to receive information based on his or her interests.

[1104] An "information category" is a division of a particular type of information that interests a user, such as a news genre or topic area.

[1105] The "desired delivery time period" is the range of time within which the user can receive information, and a specific time or time period can be specified.

[1106] "Multiple information sources on the network" refers to various sources accessible via the Internet, including news sites, blogs, APIs, etc.

[1107] "Relevant information items" refer to specific news articles or data entries collected based on the information categories received.

[1108] "Automatic collection methods" are mechanisms by which programs automatically obtain information based on user settings, such as using web crawlers or API requests.

[1109] "Filtering" is the process of selecting useful information items from collected information based on specific criteria.

[1110] "Ranking" is the process of prioritizing filtered information items based on relevance and recency.

[1111] A "customized information feed" is a collection of news and data delivered as a personalized stream of information generated according to a user's preferences.

[1112] The "means of delivery" refers to a method for sending the generated information feed to the user's terminal, and includes email, push notification, a dedicated application, and the like.

[1113] The present invention provides a system that allows users to set information categories of interest and desired delivery time periods, and provides a customized information feed based on that information. The following describes an embodiment of this system.

[1114] User Settings

[1115] Users access the system and set the information category and desired delivery time. For example, a user can select "IT news" and "economic news" through the application interface and set the information to be delivered at 7:00 every morning. This setting information is sent to the server.

[1116] Receiving and storing configuration information

[1117] The server receives the information category and desired delivery time slot sent by the user and stores it in a database. Specifically, it uses a database such as MySQL or PostgreSQL to manage user IDs, information categories, and delivery time slots.

[1118] Collection of information

[1119] As the specified delivery time approaches, the server collects relevant information from information sources on the network based on the user's settings. Specifically, it sends API requests to obtain the latest information items related to "IT" and "Economy" and stores the information in a database. The APIs used for this purpose are, for example, NewsAPI and NY Times API.

[1120] Filtering and ranking information

[1121] The server then filters and ranks the collected information items based on their relevance and recency. This process uses a machine learning algorithm based on Python's scikit-learn library. Specifically, it performs text analysis on the information items, calculates a relevance score, and assigns a ranking.

[1122] Personalized information delivery

[1123] Based on the filtered and ranked information items, the server generates a customized information feed in HTML or JSON format, customizing the content for each user, and then sends the generated information feed to the user's device.

[1124] Displaying Information

[1125] The device receives the information feed sent from the server and notifies the user at the set time. For example, the push notification function can be used to display a message saying, "The latest IT and economic news has been updated" at a specified time. When the user clicks on this notification, the app opens and the customized information feed is displayed.

[1126] Specific examples

[1127] As a concrete example, suppose User A is interested in "Sports News" and "Entertainment News" and has set up a schedule to receive information at 6:00 PM. The server saves this setting and starts collecting relevant information from 5:55 PM. After filtering and ranking, a customized information feed is delivered to User A's device at 6:00 PM. User A receives a notification on his / her way home and can open the app to check the latest sports and entertainment news.

[1128] Examples of prompt statements

[1129] An example of a prompt to be input to the generative AI model is as follows:

[1130] Explain how a system that provides a customized information feed works, allowing users to set the information categories they are interested in and the time slots they want delivered. For example, explain in detail how a system works if a user selects "IT news" and "Economic news" and sets the time slots to receive them every morning at 7:00.

[1131] The above is an embodiment of the system of the present invention. This system enables users to efficiently collect information that matches their interests and check it in a timely manner at an appropriate time.

[1132] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1133] Step 1:

[1134] The user opens the application and enters the information category and desired delivery time slot. Specifically, the user selects "IT News" or "Economic News" in the application interface and sets "7:00" as the delivery time slot. Once this setting information has been entered, the user presses the "Set" button to send it to the server. The input here is the information category and delivery time slot data, and the output is data sent to the server.

[1135] Step 2:

[1136] The server receives the information category and desired delivery time setting information sent by the user. It then stores the information in a database such as MySQL or PostgreSQL. Specifically, data including the user ID, information category, and delivery time is stored and managed in the database. The input is the user setting data, and the output is the operation of saving it to the database.

[1137] Step 3:

[1138] As the specified delivery time approaches, the server starts the information collection process. For example, if a user has set their preference to receive news at 7:00 in the morning, the server will send a request to a news API (such as NewsAPI or NY Times API) at 6:55 to collect the latest information on "IT" and "Economy." The collected data is then stored in a database as is. The input is the API request, and the output is the data of the retrieved information items.

[1139] Step 4:

[1140] The server filters and ranks the collected information items. Specifically, it uses the scikit-learn library to perform text analysis, selects articles that are highly relevant to the user's preferences, and calculates an importance score to rank them. This process uses relevance and recency as criteria. The input is the collected information items, and the output is the filtered and ranked information items.

[1141] Step 5:

[1142] Based on the filtered and ranked information items, the server generates a customized information feed. The generated information feed is created in HTML or JSON format and is customized to have different content for each user. Once generated, the information feed is sent to the user's device. The input is the filtered and ranked information items, and the output is the customized information feed.

[1143] Step 6:

[1144] The device receives the information feed sent from the server and notifies the user at the set time. The push notification function is used to notify the user of information updates. When the user clicks on the notification, the app opens and a customized information feed is displayed. The input is the information feed from the server, and the output is the customized information feed displayed to the user.

[1145] The above is the processing flow and specific operation of this system's program. By clarifying the detailed input and output at each step, as well as the specific content of data processing and data calculation, users can efficiently collect information that matches their interests and check it at a specified time.

[1146] (Application example 1)

[1147] 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."

[1148] In today's information society, users are required to access a vast amount of information, but it is extremely difficult to select the information that is important to them from that. They are also unable to receive information in a timely manner, and lack the means to efficiently collect and review information at an appropriate time. Furthermore, despite the increasing diversity of information formats, conventional systems tend to be limited to text-based information. There is a need to solve these issues and provide users with useful information at the appropriate time.

[1149] 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.

[1150] In this invention, the server includes means for receiving input of an information category and a desired update time period from a user, means for automatically collecting related information from multiple information sources on a communication network based on the received information category, means for filtering and ranking the collected information, means for generating and distributing a customized information feed according to the desired update time period, means for scheduling to notify the smart device of the customized information, and means for processing information in both video and text format when generating the customized information feed. This allows users to efficiently collect information that matches their interests and check it in a timely manner at an appropriate time.

[1151] An "information category" represents a particular subject or genre that interests a user.

[1152] "Update time period" refers to a specific time period during which a user wishes to receive updates and notifications about the information they desire.

[1153] "Communications network" refers collectively to the network system used to collect and transmit information.

[1154] "Source" refers to the source or service that provides information, such as an internet news site or data provider.

[1155] "Filtering" refers to the process of selecting necessary information from collected information based on specific criteria.

[1156] "Ranking" refers to the process of prioritizing filtered information based on specific criteria.

[1157] "Information Feed" refers to a stream of customized information provided to a user.

[1158] "Scheduling" refers to the process of planning the execution of a particular task or process at a predetermined time.

[1159] "Smart devices" refer to mobile terminals and wearable devices that have Internet connectivity and can manage and display information.

[1160] "Video format" refers to a media format that contains moving images.

[1161] "Text format" refers to a media format that contains text or textual information.

[1162] This invention is a system that provides a customized information feed based on information that a user sets by setting the information categories of interest and the desired update time period.

[1163] User Settings

[1164] The user accesses the system and sets the information category and desired update time. For example, the user selects "News" and "Entertainment" through the application interface and sets that they want to receive information every morning at 7:00. This setting information is sent to the server.

[1165] Receiving and storing configuration information

[1166] The server receives the information category and desired update time period sent by the user and stores it in a database. This assigns a unique ID to each user and manages individual settings information.

[1167] Collection of information

[1168] At the specified update time, the server collects relevant information from sources on the network based on the user's settings, for example by sending an API request to get the latest information on "News" and "Entertainment," and stores that information in the database.

[1169] Filtering and ranking information

[1170] The server filters and ranks the most important information from the collected data based on relevance and recency, a process that results in the most relevant information being selected for the user.

[1171] Personalized information delivery

[1172] Based on the filtered and ranked information, the server generates a customized information feed, which is then delivered to the device at the update time specified by the user.

[1173] Displaying Information

[1174] The device receives the information feed sent from the server and notifies the user at the set time. When the user opens the app, the customized information feed is displayed. For example, a user can open the app on their way to work to check the latest "News" and "Entertainment."

[1175] Specific actions

[1176] The system operates using multiple software components. It uses API requests to collect information, a Python scheduling library (schedule), and a library for sending HTTP requests (requests). This allows it to filter the collected information and deliver it at a time specified by the user.

[1177] For example, suppose User A is interested in "sports" and "technology" and has set up a preference to receive information every day at 6:00 PM. The server saves this preference information and starts collecting related information from 5:55 PM. After filtering and ranking, the customized information feed is delivered to User A's device at 6:00 PM. User A can easily check the latest sports news and technology-related information in the evening.

[1178] Prompt Sentence Examples

[1179] You want to create an application that generates a customized news feed based on the user's interest categories and delivers it at a specified time. Provide a Python program that includes the following elements:

[1180] 1. User interface for setting news categories and update times.

[1181] 2. Collect news of a specified category from sources.

[1182] 3. Filter the collected news and rank them based on recency.

[1183] 4. The filtered news feed is sent to the user's device at the specified time.

[1184] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1185] Step 1:

[1186] The user sets the information categories they are interested in and the desired update time slots through the application interface. The information categories (e.g., "News" or "Entertainment") and update time slots (e.g., every morning at 7:00) entered by the user are sent to the server from the settings screen.

[1187] Input: User-defined information category and desired update time period

[1188] Output: User preference data sent to the server

[1189] Step 2:

[1190] The server receives the setting information sent by the user and stores it in a database, which assigns a unique ID to each user and manages individual setting information.

[1191] Input: User-defined data (information category and update time period)

[1192] Output: User preferences stored in the database

[1193] Step 3:

[1194] When the specified update time arrives, the server collects relevant information from multiple sources on the network based on the user's settings. The server sends an API request to collect information and obtains the latest content related to "News" and "Entertainment."

[1195] Input: User setting information (information category and update time period), API request

[1196] Output: Collected information

[1197] Step 4:

[1198] The server filters the collected information and ranks it based on relevance and recency. The server automatically analyzes the information and selects the most relevant information for the user.

[1199] Input: Collected information

[1200] Output: Filtered and ranked information

[1201] Step 5:

[1202] The server generates a customized information feed based on the filtered and ranked information, and the generated information feed is delivered to the terminal at the update time specified by the user.

[1203] Input: Filtered and ranked information

[1204] Output: Customized information feed

[1205] Step 6:

[1206] The device receives the customized information feed sent from the server and notifies the user at the specified update time. When the user opens the app on the device, the customized information feed is displayed.

[1207] Input: Customized information feed

[1208] Output: A customized information feed displayed on your device

[1209] Step 7:

[1210] Users can open their devices on their way to work or in their spare time to check their customized information feed, allowing them to efficiently gather the latest information that matches their interests and view it at the appropriate time.

[1211] Input: A customized information feed displayed on your device

[1212] Output: Customized information for the user to review

[1213] 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.

[1214] The present invention is a system that receives input from a user regarding news genres and desired update times, automatically collects relevant news articles from multiple news sources on a network based on the input, filters and ranks them, and then generates a customized news feed. Furthermore, it incorporates an emotion engine that recognizes the user's emotions, providing a means for filtering and ranking news articles based on the user's emotional state. Specific implementation methods of the present invention are described below.

[1215] User Settings

[1216] Users access the system and set the news genre and desired update time. For example, they may select "IT news" and "Economic news" and want news updates every morning at 7:00. This setting information is entered through the application's user interface and sent to the server.

[1217] Receiving and storing configuration information

[1218] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database, allowing each user's settings information to be managed uniquely.

[1219] News gathering

[1220] At the specified update time, the server collects relevant news from news sources on the network based on the configuration information, for example, sending an API request to get the latest news articles on "IT" and "Economy" and stores them in the database.

[1221] Filtering and Ranking

[1222] The server filters the collected news articles and ranks them based on relevance and recency, a process that selects the most relevant articles for the user.

[1223] Customize and deliver news

[1224] Based on the filtered and ranked news articles, the server generates a customized news feed that is delivered to the user's device at the time of their choice.

[1225] Emotional engine regulation

[1226] The server uses an emotion engine that recognizes the user's emotions. The emotion engine analyzes voice, facial expressions, input data, etc. to identify the user's emotions. For example, if the user is showing positive emotions, it will prioritize displaying more optimistic news, and if the user is showing negative emotions, it will prioritize displaying comforting and encouraging news.

[1227] Viewing news

[1228] The device receives the customized news feed sent from the server and notifies the user at the specified time. When the user opens the app, the customized news feed is displayed.

[1229] Specific examples

[1230] As a specific example, suppose User A is interested in "sports news" and "entertainment news" and has set up a daily news feed at 6:00 PM. The server saves this setting information and starts collecting relevant news from 5:55 PM. After filtering and ranking, a customized news feed is delivered to User A's device at 6:00 PM. If the emotion engine recognizes that User A has been feeling stressed recently, news that helps with relaxation and distraction will be presented preferentially.

[1231] This invention allows users to efficiently collect news that interest them and check it at an appropriate time. Furthermore, the introduction of an emotion engine provides news articles that match the user's current emotional state, further improving the user experience.

[1232] The processing flow will be explained below.

[1233] Step 1:

[1234] When a user installs the application and starts it for the first time, they select the news genre and desired update time. For example, they may select "IT news" and "Economic news" and want news updates every morning at 7:00. This setting information is entered through the application's user interface and sent to the server.

[1235] Step 2:

[1236] The server receives the setting information sent by the user. The received information includes the user's ID, selected news genre, and desired update time period. This information is stored in a database and managed uniquely for each user.

[1237] Step 3:

[1238] A few minutes before the specified update time (e.g., 6:55), the server starts collecting relevant news based on the configuration information. Specifically, it sends API requests to retrieve the latest news articles related to "IT" and "Economy" from multiple reliable news sources. The retrieved news articles are then stored in a database.

[1239] Step 4:

[1240] The server filters the collected news articles based on criteria such as the article's relevance, recency, and credibility, for example, to exclude articles that the user has already seen or that are duplicates.

[1241] Step 5:

[1242] The server then ranks the filtered news articles, taking into account the importance and timeliness of the articles. The more important and up-to-date news is ranked higher and displayed preferentially.

[1243] Step 6:

[1244] The server uses an emotion engine to recognize the user's emotions. The emotion engine identifies the user's emotions through voice analysis, facial expression analysis, text analysis, etc. For example, if the user's recent typing history or voice tone indicates a positive emotion, the corresponding news article will be selected.

[1245] Step 7:

[1246] Based on the results of the emotion engine, the server reprioritizes news articles: for example, if a user expresses negative emotions, news articles that bring encouragement and hope will be prioritized.

[1247] Step 8:

[1248] Based on the filtered and ranked news articles, the server generates a customized news feed that is tailored to the user's preferred update timeframe.

[1249] Step 9:

[1250] At the specified update time (e.g., 7:00), the server delivers the generated customized news feed to the user's device via push notification, in-app notification, or email.

[1251] Step 10:

[1252] The device receives the news feed sent from the server, arranges for the news feed to be displayed at the time set by the user, and displays a notification to inform the user that a new news feed has arrived.

[1253] Step 11:

[1254] Users open the app and check the delivered news feed. They can browse the latest news articles in the genres they are interested in. The articles displayed are tailored to the user's emotional state, improving the user experience.

[1255] This step allows users to efficiently collect news that interests them and check news articles that correspond to their emotions at an appropriate time.

[1256] Example 2

[1257] 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."

[1258] In modern society, users need to efficiently obtain relevant information from a vast amount of news articles. However, conventional news gathering systems provide information without fully considering the user's interests or emotional state, making it difficult for users to find the information they need. Furthermore, a large amount of news information can have a negative impact on the user's emotions and mental state.

[1259] 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.

[1260] In this invention, the server includes means for receiving input of a news genre and a desired update time period from a user, means for automatically collecting related news articles from multiple news sources on a network based on the received news genre, means for filtering the collected news articles and ranking them based on relevance and recency, means for generating and delivering a customized news feed according to the desired update time period, and means for analyzing the user's emotions and adjusting the news feed based on the user's emotional state, thereby enabling the user to efficiently obtain news of interest and providing a news feed optimized according to the user's emotional state.

[1261] "News genre" refers to a particular category of news that interests a user.

[1262] A "desired update time slot" refers to a time at which a user desires to receive a news feed.

[1263] "News Source" means an online source that is consulted to provide relevant news articles.

[1264] "Filtering" refers to the process of sorting collected news articles based on specific criteria.

[1265] "Ranking" refers to the process of ranking the filtered news articles based on relevance and recency.

[1266] "Customized News Feed" means a list of news items that are individually optimized based on a user's preferences and criteria.

[1267] "Delivery" refers to the process of sending a customized news feed to a user's device.

[1268] An "emotion engine" refers to technology that recognizes a user's emotional state by analyzing voice, facial expressions, input data, etc.

[1269] "Emotional state" refers to a state that indicates a user's current feelings or mood.

[1270] MODE FOR CARRYING OUT THE INVENTION

[1271] The present invention is a system that receives input from users regarding news genres and desired update times, automatically collects relevant news articles from multiple news sources on the network based on the input, filters and ranks them, and then generates and distributes a customized news feed. Furthermore, the system aims to combine an emotion engine that recognizes the user's emotions and adjusts the news articles based on the user's emotional state.

[1272] User Settings

[1273] A user accesses the system and sets the news genre and desired update time. For example, if a user selects "sports news" and "entertainment news" and wants news updates every day at 6:00 PM, this setting information is entered through the application's user interface and sent to the server.

[1274] Receiving and storing configuration information

[1275] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database, allowing each user's settings information to be managed uniquely.

[1276] News gathering

[1277] At the specified update time, the server collects relevant news from news sources on the network based on the configuration information. For example, it sends an API request to retrieve the latest news articles on "sports" and "entertainment" and stores them in a database. Examples of news APIs that can be used include NewsAPI and Google News API.

[1278] Filtering and Ranking

[1279] The server filters the collected news articles and ranks them based on relevance and recency, for example by using a machine learning model (such as Scikit-learn) to rank the news articles, thereby selecting the most relevant articles for the user.

[1280] Customize and deliver news

[1281] Based on the filtered and ranked news articles, the server generates a customized news feed that is delivered to the user's device at the time of their choice.

[1282] Emotional engine regulation

[1283] The server uses an emotion engine that recognizes the user's emotions. The emotion engine analyzes voice, facial expressions, input data, etc. to identify the user's emotions. For example, if the user is showing positive emotions, it will prioritize displaying more optimistic news, and if the user is showing negative emotions, it will prioritize displaying comforting and encouraging news. Specific examples include using the Microsoft Emotion API and Amazon Comprehend.

[1284] Viewing news

[1285] The device receives the customized news feed sent from the server and notifies the user at the specified time. When the user opens the app, the customized news feed is displayed.

[1286] Specific examples

[1287] As a specific example, if User A is interested in "sports news" and "entertainment news" and has set his / her preference to receive news every day at 6:00 PM, the server will save this preference information and start collecting related news from 5:55 PM. After filtering and ranking, a customized news feed will be delivered to User A's device at 6:00 PM. Also, if the emotion engine recognizes that User A has been feeling stressed recently, news that will help him / her relax or unwind will be presented preferentially.

[1288] Example prompts for generative AI models

[1289] The following can be input to the generative AI model:

[1290] Example prompt 1:

[1291] "Write a program that automatically gathers and filters relevant news articles to provide a customized feed to users based on their preferred news genre and update time frame."

[1292] Example prompt 2:

[1293] "Write a program to create a system that recognizes a user's emotions and filters and ranks news based on those emotions."

[1294] This helps the generative AI model generate the program for the entire system.

[1295] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1296] Step 1:

[1297] A user accesses the system and sets the news genre and desired update time period.

[1298] Specific behavior:

[1299] The user enters information into the fields for "news genre" and "update time" through the application's user interface. For example, the user might enter "IT news" and "economic news" at 7:00 every morning. The entered data is sent to the server by pressing the send button.

[1300] Input: User-selected news genre and desired update time

[1301] Output: Configuration information sent to the server

[1302] Step 2:

[1303] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database.

[1304] Specific behavior:

[1305] The server receives user setting information via the REST API. It analyzes the received information and saves it as per-user settings in a database (e.g., MySQL or PostgreSQL). After saving is complete, it generates a save confirmation message for the user and sends it to the device.

[1306] Input: Received setting information

[1307] Output: Setting information saved in the database, save confirmation message

[1308] Step 3:

[1309] When the specified update time arrives, the server collects relevant news from news sources on the network based on the setting information.

[1310] Specific behavior:

[1311] Use Chron jobs or CRON scheduling to start the news gathering process at a specified time (e.g., 6:55 every morning). Send an API request to a news API (e.g., News API, Google News API) to retrieve the latest news in a specified genre. Store the retrieved news data in a database.

[1312] Input: User settings, latest news from news API

[1313] Output: A database containing news data

[1314] Step 4:

[1315] The server filters the collected news articles and ranks them based on relevance and recency.

[1316] Specific behavior:

[1317] Applying filtering algorithms based on news article categories, dates, keywords, etc. Ranking news articles using a machine learning model (e.g., a ranking algorithm built with Scikit-learn). Keeping the ranked results in temporary storage or memory.

[1318] Input: Collected news articles

[1319] Output: Filtered and ranked news articles

[1320] Step 5:

[1321] Based on the filtered and ranked news articles, the server generates a customized news feed and delivers it to the device at the specified time.

[1322] Specific behavior:

[1323] Generate a customized news feed at a specified time (e.g., every morning at 7:00). Deliver the news feed to the user's device using email or push notification APIs (e.g., Firebase Cloud Messaging). Log whether the feed was delivered successfully.

[1324] Input: Customized news article

[1325] Output: News feed delivered to the user's device

[1326] Step 6:

[1327] The server uses an emotion engine that recognizes the user's emotions and readjusts the news article.

[1328] Specific behavior:

[1329] Analyze user emotions using sentiment analysis APIs (e.g., Microsoft Emotion API, Amazon Comprehend). Input voice data and text feedback into the emotion engine to get results. Readjust the content of the news feed based on the emotional state. For example, prioritize positive articles.

[1330] Input: User emotion data

[1331] Output: Rebalanced news feed

[1332] Step 7:

[1333] The terminal receives the customized news feed sent from the server and notifies the user at a specified time.

[1334] Specific behavior:

[1335] The device receives push notifications and emails and notifies the user in the configured way. When the user launches the app, a customized news feed is displayed. User feedback is obtained and sent to the server.

[1336] Input: News feed from the server

[1337] Output: Notified news feed and user feedback

[1338] (Application example 2)

[1339] 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."

[1340] Conventional news feed generation systems allow users to set the news genres they are interested in and the update time slots they desire, but they are unable to customize news articles based on the user's emotional state. As a result, inappropriate news articles may be displayed when the user is feeling stressed or in a particular mood. Therefore, there is a need to provide a more user-friendly news feed by filtering and ranking news articles based on the user's emotional state.

[1341] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving input of a news genre and a desired update time period from a user; means for automatically collecting related news articles from multiple news sources on the network based on the received news genre; means for filtering and ranking the collected news articles; means for generating and delivering a customized news feed according to the desired update time period; and means for using an emotion engine that recognizes the user's emotional state to filter and rank the news articles based on the emotional state. This makes it possible to provide an optimal news feed tailored to the user's emotional state.

[1342] A "news genre" refers to news articles in a particular field or category that interests a user.

[1343] A "desired update time" is a specific time period during which a user would like to receive the latest news feed.

[1344] "News sources" are the websites and databases that provide news articles.

[1345] "Related news articles" refer to news articles collected based on the news genre set by the user.

[1346] "Filtering" refers to the process of filtering out collected news articles that are less relevant to the user.

[1347] "Ranking" is the process of prioritizing a collection of news articles based on their relevance and recency.

[1348] A "customized news feed" is a list of news articles generated and optimized based on a user's news genre and preferred update time frame.

[1349] An "emotion engine" refers to algorithms and techniques for recognizing a user's emotional state and filtering and ranking news articles based on that.

[1350] The present invention is a system that receives input from users regarding news genres and desired update times, automatically collects relevant news articles from multiple news sources on the network based on the input, filters and ranks them, and then generates a customized news feed. Furthermore, it combines an emotion engine that recognizes the user's emotions, providing a means for filtering and ranking news articles based on the user's emotional state.

[1351] A system for implementing the present invention includes the following components:

[1352] User Settings

[1353] Users can set their preferred news genre and update time through the application. For example, they can select "IT news" or "Economic news" and request news updates every morning at 7:00. This setting information is entered through the smartphone application's user interface and sent to the server.

[1354] Receiving and storing configuration information

[1355] The server receives the information on the news genre and desired update time period sent by the user and stores it in a database. This database is managed using a database management system (DBMS) such as SQLite.

[1356] News gathering

[1357] When the specified update time arrives, the server collects relevant news articles from news sources based on the configuration information. For example, it uses a news API to obtain the latest news articles related to "IT" or "Economy" and stores this data in a database.

[1358] Filtering and Ranking

[1359] The server then filters the collected news articles and ranks them based on relevance and recency, a process that involves processing the data using, for example, the Python programming language and scripting libraries.

[1360] Customize and deliver news

[1361] Based on the filtered and ranked news articles, the server generates a customized news feed and delivers it to the user's device, such as a smartphone or tablet, according to the user's desired update time.

[1362] Emotional engine regulation

[1363] The server is equipped with an emotion engine that recognizes the user's emotions. This engine analyzes the user's facial images and voice data using machine learning models such as TensorFlow to identify the user's emotional state. For example, if the user is showing positive emotions, it will prioritize displaying more optimistic news, and if the user is showing negative emotions, it will prioritize displaying comforting and encouraging news.

[1364] Viewing news

[1365] The device receives the customized news feed sent from the server, and when the user opens the app, the system displays the news feed.

[1366] Specific examples

[1367] As a specific example, suppose User A is interested in "Entertainment" and "Sports" and has set his preferences to receive news every day at 6:00 PM. The server saves this preference information and starts collecting relevant news articles from 5:55 PM. After filtering and ranking, a customized news feed is delivered to User A's device at 6:00 PM. If the emotion engine recognizes that User A has been feeling stressed recently, news that will help him relax and unwind will be presented preferentially.

[1368] Prompt Sentence Examples

[1369] "Generate a smartphone app program using Python that collects the latest news based on the news genre and desired update time specified by the user, and uses an emotion engine to prioritize and display news that matches the user's emotional state."

[1370] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1371] Step 1:

[1372] The user inputs the news genre and desired update time into the application. For example, the user selects "IT news" and "Economic news" and requests news updates every morning at 7:00. This input information is sent to the server via the user interface. The news genre and desired update time are provided as input data, and the server receives this setting information as output.

[1373] Step 2:

[1374] The server stores the information received from the user about the news genre and desired update time period in a database. This process uses a database management system (e.g., SQLite). The server receives user setting information as input data and stores it accurately in the database.

[1375] Step 3:

[1376] At the set update time, the server collects relevant news articles from news sources and sends an API request to get the latest news articles based on the news genre set by the user. For example, the news API can be used to get the latest articles related to "IT" or "Economy" and store the data in a database. The news genre and API endpoint are used as input data, and the list of latest news articles is obtained as output.

[1377] Step 4:

[1378] The server filters the collected news articles and ranks them based on relevance and recency. This process is performed using the Python programming language and data processing libraries (e.g., pandas). It receives a list of collected news articles as input, evaluates the articles based on relevance and recency, and outputs a ranked list.

[1379] Step 5:

[1380] The server generates a customized news feed based on the filtered and ranked news articles and delivers it to the device according to the user's desired update time. The server retrieves the ranked news articles from the database, generates a news feed formatted for the user's interface, and sends it to the smartphone. The ranked articles are used as input data, and the customized news feed is delivered as output.

[1381] Step 6:

[1382] The server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's facial and voice data using TensorFlow's machine learning model to identify the user's emotions. It receives the user's facial expression image or voice data as input data, analyzes the data, and outputs the user's emotional state.

[1383] Step 7:

[1384] The server further filters and ranks the news articles based on the user's emotional state as determined by the emotion engine. For example, if the user is expressing positive emotions, it prioritizes optimistic news, and if the user is expressing negative emotions, it prioritizes comforting and encouraging news. The server takes the emotional state information as input data and re-evaluates and outputs the news articles based on it.

[1385] Step 8:

[1386] The device receives the customized news feed sent from the server and notifies the user at the specified time. When the user opens the app, the customized news feed is displayed. The app receives the news feed from the server as input data and displays it in the user interface as output.

[1387] 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.

[1388] 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.

[1389] 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.

[1390] 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.

[1391] 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.

[1392] 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.

[1393] 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).

[1394] 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.

[1395] 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."

[1396] 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.

[1397] 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).

[1398] 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.

[1399] 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.

[1400] 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.

[1401] 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.

[1402] 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.

[1403] 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.

[1404] 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.

[1405] 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.

[1406] 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.

[1407] 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.

[1408] The following is further disclosed regarding the above embodiment.

[1409] (Claim 1)

[1410] means for receiving input from a user regarding a news genre and a desired update time period;

[1411] means for automatically collecting relevant news articles from multiple news sources on a network based on the received news genre;

[1412] a means for filtering and ranking the collected news articles;

[1413] A means for generating and delivering a customized news feed for your desired update times;

[1414] A system including:

[1415] (Claim 2)

[1416] 10. The system of claim 1, further comprising means for automatically displaying the news feed at a specified update time based on user input.

[1417] (Claim 3)

[1418] 10. The system of claim 1, further comprising means for determining a display order based on relevance and recency of collected news articles when generating a news feed.

[1419] "Example 1"

[1420] (Claim 1)

[1421] means for receiving input from a user of information categories and desired delivery times;

[1422] means for automatically collecting relevant information items from multiple information sources on a network based on the received information categories;

[1423] means for filtering and ranking the collected information items;

[1424] means for generating and distributing customized information feeds according to desired distribution times;

[1425] …

[1426] A system including:

[1427] (Claim 2)

[1428] 10. The system of claim 1, further comprising means for automatically displaying the information feed at a designated delivery time based on user input.

[1429] (Claim 3)

[1430] 10. The system of claim 1, further comprising means for determining a display order based on relevance and recency of the collected information items when generating the information feed.

[1431] "Application Example 1"

[1432] (Claim 1)

[1433] means for receiving input from a user of information categories and desired update times;

[1434] means for automatically collecting relevant information from multiple sources on a communications network based on the received information categories;

[1435] a means for filtering and ranking the collected information;

[1436] a means for generating and distributing customized information feeds according to desired update times;

[1437] a scheduling means for notifying the smart device of customized information;

[1438] means for including and processing information in video and text format when generating the customized information feed;

[1439] A system including:

[1440] (Claim 2)

[1441] 10. The system of claim 1, further comprising means for automatically displaying the information feed at a specified update time based on user input.

[1442] (Claim 3)

[1443] 10. The system of claim 1, further comprising means for determining a display order based on relevance and recency of collected information when generating an information feed.

[1444] "Example 2: Combining Emotion Engines"

[1445] (Claim 1)

[1446] means for receiving input from a user regarding a news genre and a desired update time period;

[1447] means for automatically collecting relevant news articles from multiple news sources on a network based on the received news genre;

[1448] a means for filtering and ranking the collected news articles based on relevance and recency;

[1449] A means for generating and delivering a customized news feed for your desired update times;

[1450] means for analyzing a user's emotions and adjusting the news feed based on the user's emotional state;

[1451] A system including:

[1452] (Claim 2)

[1453] 10. The system of claim 1, further comprising means for automatically displaying the news feed at a specified update time based on user input.

[1454] (Claim 3)

[1455] 10. The system of claim 1, further comprising means for determining a display order based on relevance and recency of collected news articles when generating a news feed.

[1456] "Application example 2 when combining emotion engines"

[1457] (Claim 1)

[1458] means for receiving input from a user regarding a news genre and a desired update time period;

[1459] means for automatically collecting relevant news articles from multiple news sources on a network based on the received news genre;

[1460] a means for filtering and ranking the collected news articles;

[1461] A means for generating and delivering a customized news feed for your desired update times;

[1462] means for utilizing an emotion engine that recognizes the emotional state of a user and filtering and ranking news articles based on the emotional state;

[1463] A system including:

[1464] (Claim 2)

[1465] 10. The system of claim 1, further comprising means for automatically displaying the news feed at a specified update time based on user input.

[1466] (Claim 3)

[1467] 10. The system of claim 1, further comprising means for determining a display order based on relevance and recency of collected news articles when generating a news feed. [Explanation of symbols]

[1468] 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. means for receiving input from a user regarding a news genre and a desired update time period; means for automatically collecting relevant news articles from multiple news sources on a network based on the received news genre; a means for filtering and ranking the collected news articles; a means for generating and delivering a customized news feed according to desired update times; A system including:

2. 10. The system of claim 1, further comprising means for automatically displaying the news feed at a specified update time based on user input.

3. 10. The system of claim 1, further comprising means for determining a display order based on relevance and recency of the collected news articles when generating the news feed.

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