System

Abstract

A system is provided.SOLUTION: The system includes an information collection means, an analysis means, a notification means, a purchase support means, a generation means, and a strategy formulation means.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] Fans who strongly support specific targets and follow their activities face challenges such as gathering new information, tracking information in real time, gaining a deep understanding of the target, and making optimal use of limited resources. Furthermore, to ensure an efficient and enriching fan experience, it is necessary to effectively manage and appropriately process a wide variety of information. However, doing this manually is extremely labor-intensive and difficult to cover all information. Therefore, a system is needed to improve the efficiency of fan activities for specific targets and provide a better experience. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems with a system including an information collection means, an analysis means, a notification means, a purchase support means, a generation means, and a strategy formulation means. Specifically, the information collection means collects the latest information about a specific target from public databases on the Internet, news sites, social networking services, and official websites. The analysis means then evaluates the importance and relevance of the collected information and filters it. The notification means provides the filtered information to the user's device via push notification or email. The purchase support means recommends related items based on the user's past purchase history. The generation means generates original content based on the style of the specific target. The strategy formulation means provides an optimal ticket purchasing strategy based on event information related to the specific target. Integrating functions to support diverse fan activities in this way significantly improves the efficiency of fan activities and provides a richer experience.

[0006] "Information gathering means" refers to means that have the function of gathering the latest information about a specific subject from public databases, news sites, social networking services, and official websites on the Internet.

[0007] The "analysis means" is a means having the function of evaluating the importance and relevance of collected information and filtering out inappropriate information.

[0008] The "notification means" is a means having a function of providing filtered information to a user terminal by push notification or email.

[0009] The "purchase support means" is a means having a function of recommending related items based on the user's past purchase history and presenting them to the user.

[0010] The "generation means" is a means having a function of generating original content based on the style and characteristics of a specific target and providing it to a user.

[0011] The "strategy formulation means" is a means having the function of conducting analysis based on information about events related to a specific target, and providing users with the optimal participation method and ticket purchasing strategy. [Brief explanation of the drawings]

[0012] [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

[0013] 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.

[0014] First, the terms used in the following description will be explained.

[0015] 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).

[0016] 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.

[0017] 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.

[0018] 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.

[0019] 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."

[0020] [First embodiment]

[0021] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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."

[0033] The present invention relates to a system that efficiently collects and analyzes the latest information about a specific subject (hereinafter referred to as "artist") and supports fan activities. This system includes information collection means, analysis means, notification means, purchase support means, generation means, and strategy formulation means.

[0034] 1. Providing new information

[0035] Program processing

[0036] The server periodically collects new information from multiple sources, including public databases on the Internet, news sites, social networking services, and official websites, using the artist's name as a key. The information collected by the server is analyzed using natural language processing technology and filtered based on relevance and importance. The filtered information is then delivered to the user's device via push notification or email.

[0037] Specific examples

[0038] A user wants to keep track of the latest information about a particular artist, so they input the artist's name into the system. The server then collects information about the artist from multiple sources on the Internet, filters out important news, articles, and social media posts, and notifies the user's device.

[0039] 2. Support for creating original songs

[0040] Program processing

[0041] The server acquires the artist's song data and analyzes musical elements such as rhythm, melody, chords, tempo, etc. Based on the analysis results, it provides an original song creation tool that users can use to create original songs.

[0042] Specific examples

[0043] If a user wants to create a song in the style of a certain artist, they specify the artist's musical style to the system. The server analyzes the artist's song data and extracts musical characteristics. The user can then use the provided templates and tools to create a song in the artist's style.

[0044] 3. Social media posting support

[0045] Program processing

[0046] The server retrieves the user's past social media posts and analyzes their content and engagement. The server then uses natural language generation technology to generate text for new posts and presents it to the user. The user can then review the generated text, edit it, and post it.

[0047] Specific examples

[0048] If a user is thinking about posting their impressions of a concert on social media but is unsure of how to write it, they can link their past social media posts to the system. The server analyzes past trends, generates text for a new post, and presents it to the user. The user can use that text as a reference when posting.

[0049] 4. Performance Analysis

[0050] Program processing

[0051] The server collects past live performance footage and audio, analyzes performance trends, song lists, and audience reactions, and based on the analysis results, suggests songs that are likely to be played at the next live performance and effective ways to cheer on the band.

[0052] Specific examples

[0053] If a user wants to predict what songs will be played at an upcoming live concert, they register the concert information in the system. The server analyzes past performance data and shares with the user a list of songs that are likely to be played at the next live concert.

[0054] 5. Real-time tracking

[0055] Program processing

[0056] The server monitors artists' social media accounts and official websites, collecting new posts and news in real time. The collected information is organized and instantly sent to the user's device.

[0057] Specific examples

[0058] If users want to keep up with the latest news about their favorite artists, they can register the artists' social media accounts in the system. The server monitors the accounts in real time, and users are immediately notified of any new posts or news.

[0059] 6. Item Recommendations

[0060] Program processing

[0061] The server analyzes the user's purchasing history and selects items that match the user's preferences from a database of artist-related products. The selected items are then sent to the user via push notification or email.

[0062] Specific examples

[0063] When a user wants to purchase new merchandise from an artist, they can connect their past purchase history to the system. The server analyzes their preferences, recommends related items, and supports the user in making the purchase.

[0064] 7. Fan Art Generation

[0065] Program processing

[0066] The server collects image data of artists, analyzes their style and characteristics, and generates fan art based on the analysis results, which is then made available for users to download.

[0067] Specific examples

[0068] When a user wants to create fan art of an artist, they provide an image of the artist to the system, and the server analyzes the style and provides the user with AI-generated fan art.

[0069] 8. Develop an event strategy

[0070] Program processing

[0071] The server collects information about artists' tours and live events, formulates the optimal ticket purchasing strategy, and notifies users of the timing of purchases and how to select the best tickets.

[0072] Specific examples

[0073] If a user wants to buy tickets to an upcoming live event but doesn't know the best way to do so, they register the tour information in the system. The server analyzes the event information and suggests the best ticket purchasing strategy to the user.

[0074] In this way, this system effectively manages and analyzes a wide variety of information and provides a multifunctional service to support fan activities. By using this system, users can improve the efficiency of their fan activities and have a richer experience.

[0075] The processing flow will be explained below.

[0076] 1. Providing new information

[0077] Program processing

[0078] Step 1:

[0079] The server uses the name of a specific artist as a key to collect information from public databases, news sites, social networking services, and official websites on the Internet.

[0080] Step 2:

[0081] The server analyzes the collected information using natural language processing (NLP) techniques to evaluate its importance and relevance.

[0082] Step 3:

[0083] The server filters the information based on the evaluation results and removes unnecessary data.

[0084] Step 4:

[0085] The server sends the filtered information to the user's device via push notification or email.

[0086] 2. Support for creating original songs

[0087] Program processing

[0088] Step 1:

[0089] The server acquires music data of the specified artist.

[0090] Step 2:

[0091] The server analyzes the music data and extracts musical features such as rhythm, melody, chords, and tempo.

[0092] Step 3:

[0093] The server generates a music composition tool based on the extracted features and provides it to the user's terminal.

[0094] Step 4:

[0095] The user creates an original piece of music using the provided music creation tool.

[0096] 3. Social media posting support

[0097] Program processing

[0098] Step 1:

[0099] The server retrieves the user's past SNS posting data.

[0100] Step 2:

[0101] The server analyzes past posts' content, tone, and engagement.

[0102] Step 3:

[0103] The server uses natural language generation (NLG) technology to generate text for new posts.

[0104] Step 4:

[0105] The server presents the generated text to the user's terminal.

[0106] Step 5:

[0107] The user checks the presented text, edits it, and posts it to a social networking site.

[0108] 4. Performance Analysis

[0109] Program processing

[0110] Step 1:

[0111] The server collects past live footage and audio data.

[0112] Step 2:

[0113] The server analyzes the collected data and extracts information about the songs being performed, audience reactions, and performance trends.

[0114] Step 3:

[0115] Based on the analysis results, the server predicts the list of songs that are likely to be played at the next live concert and how to support the band.

[0116] Step 4:

[0117] The server provides the prediction information to the user's terminal.

[0118] 5. Real-time tracking

[0119] Program processing

[0120] Step 1:

[0121] The server monitors the artist's social media accounts and official website.

[0122] Step 2:

[0123] The server collects new posts and news in real time.

[0124] Step 3:

[0125] The server organizes the collected information and selects information that is important to the user.

[0126] Step 4:

[0127] The server immediately notifies the user's device of important information.

[0128] 6. Item Recommendations

[0129] Program processing

[0130] Step 1:

[0131] The server acquires the user's past purchase history.

[0132] Step 2:

[0133] The server analyzes the purchase history and understands the user's preferences.

[0134] Step 3:

[0135] The server selects items that match the user's preferences from a database of artist-related products available on the market.

[0136] Step 4:

[0137] The server will then suggest the selected items to the user's device via push notification or email.

[0138] 7. Fan Art Generation

[0139] Program processing

[0140] Step 1:

[0141] The server collects image data of artists and analyzes their styles and characteristics.

[0142] Step 2:

[0143] The server uses AI to generate fan art based on the analysis results.

[0144] Step 3:

[0145] The server provides the generated fan art in a downloadable format to the user's device.

[0146] 8. Develop an event strategy

[0147] Program processing

[0148] Step 1:

[0149] The server collects information about artists' tours and live events.

[0150] Step 2:

[0151] Based on the event information collected by the server, the optimal ticket purchasing strategy is developed.

[0152] Step 3:

[0153] The server provides the strategic information formulated by the server to the user's device to support the purchase process.

[0154] Step 4:

[0155] Based on the information provided by the user, the user purchases tickets at the optimal time and participates in the event.

[0156] Example 1

[0157] 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."

[0158] Conventional fan activity support systems are inefficient in collecting and analyzing the latest information on specific subjects, making it difficult for users to efficiently obtain information and improve the quality of their activities. Furthermore, they lack support for music creation and posting to social networking services, performance analysis, and real-time information tracking, making it difficult for users to centrally manage a wide range of activities. Analytical methods for properly evaluating the relevance and importance of information are also inadequate, creating a need for a method that provides only useful information to users.

[0159] 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.

[0160] In this invention, the server includes an information collection means, an analysis means, a notification means, a purchase support means, a generation means, a strategy formulation means, a music creation support means, a social network service posting support means, a performance analysis means, a real-time tracking means, an item recommendation means, and an artwork creation means, thereby enabling centralized and effective support for a wide range of fan activities, such as efficient collection and analysis of the latest information on a specific subject, timely notification to users, music creation support, social network service posting support, performance analysis, real-time information tracking, item recommendation, and fan art generation.

[0161] "Information gathering means" refers to the means of gathering the latest information on a specific subject from public databases, news sites, social networking services, and official websites on the Internet.

[0162] "Analysis means" refers to means for evaluating importance and relevance based on collected information and song data, data posted in the past on social networking services, and live performance data, and for filtering and analyzing the data.

[0163] "Notification means" refers to a means for sending filtered information to the user's device via push notification or email.

[0164] The "purchase support means" is a means for analyzing the user's purchase history and selecting and suggesting items that match the user's preferences from a database of artist-related products.

[0165] The "generation means" is a means for automatically generating new content and suggestions based on collected and analyzed data and providing them to users.

[0166] The "strategy formulation means" is a means for formulating an optimal ticket purchasing strategy based on artist tour information and live event information, and notifying the user of the strategy.

[0167] "Music composition support means" is a means for analyzing an artist's music data and providing a tool that enables a user to create original music based on the analysis results.

[0168] The "social network service posting support means" is a means for analyzing a user's past SNS posting data, automatically generating text for a new post, and providing it to the user.

[0169] "Performance analysis means" refers to a method of collecting past live performance footage and audio recordings, analyzing that data, and evaluating performance trends, song lists, and audience reactions.

[0170] "Real-time tracking means" refers to a means of monitoring an artist's social media accounts and official websites, collecting new posts and news in real time, and notifying users.

[0171] The "item recommendation means" is a means for analyzing the purchase history of a user and recommending highly relevant artist-related merchandise items.

[0172] The "artwork generation means" is a means for automatically generating fan art based on the artist's style and characteristics by analyzing the artist's image data and providing it to the user.

[0173] The present invention relates to a system for efficiently collecting and analyzing the latest information on a specific subject and supporting fan activities. The system includes an information collection means, an analysis means, a notification means, a purchasing support means, a creation means, a strategy formulation means, a music creation support means, a social network service posting support means, a performance analysis means, a real-time tracking means, an item recommendation means, and an art creation means.

[0174] Information gathering methods

[0175] The server uses information gathering tools to collect the latest information about the artist from public databases, news sites, social networking services, and official websites on the Internet, specifically using web scraping tools (e.g., Beautiful Soup, Scrapy) and APIs.

[0176] Example: A user wants to track the latest information about a particular artist and enters the artist's name into the system. The server collects information about the artist from multiple sources on the Internet, filters out important news, articles, and social media posts, and notifies the user's device.

[0177] Example prompt: "Please gather the latest information on the artist's name."

[0178] Analysis means

[0179] The server uses analytical tools to analyze the collected information, song data, past SNS posting data, and live performance data. Specifically, it uses text analysis tools (e.g., SpaCy, NLTK), music analysis tools (e.g., LibROSA, Essentia), and video analysis tools (e.g., OpenCV, Dlib).

[0180] Examples: Analyzing data collected by a server to evaluate importance and relevance and filter out noise on the Internet. Analyzing the content of news articles to extract important keywords and rank information based on importance and relevance.

[0181] Example prompt: "Analyze a news article about the artist's name."

[0182] Notification means

[0183] The server sends the filtered information to the user's device via push notification or email, using notification services such as Firebase or SendGrid.

[0184] Example: The server immediately sends filtered information to the user, allowing the user to grasp important information without missing it.

[0185] Example prompt: "Push important information to users."

[0186] Purchasing support methods

[0187] The server analyzes the user's purchase history and selects and suggests items that match the user's preferences from a database of artist-related products, using a purchase history analysis tool (e.g., Google Analytics, Tableau).

[0188] Example: If a user wants to buy new merchandise from an artist, the system analyzes their past purchase history and recommends related items.

[0189] Example prompt: "Recommend artist-related products based on the user's purchasing history."

[0190] generation means

[0191] The server uses a generating means to automatically generate new content and suggestions based on the collected and analyzed data and provide them to the user.

[0192] Example: The server analyzes the collected data and generates and provides useful articles and posts to users.

[0193] Example prompt: "Generate the latest news article about an artist."

[0194] Strategy formulation tools

[0195] This is a method for the server to create the optimal ticket purchasing strategy based on artist tour information and live event information and notify users. Event information acquisition tools (e.g., Eventbrite, Ticketmaster API) are used to collect this information.

[0196] Example: If a user wants to purchase tickets to an upcoming live event but isn't sure how best to do so, the server analyzes the event information and suggests the best ticket purchasing strategy to the user.

[0197] Example prompt: "Suggest a ticket purchasing strategy for the next live event."

[0198] Music creation support tools

[0199] The server retrieves the artist's music data and analyzes the rhythm, melody, chords, and tempo using music analysis software (e.g., Sonic Visualiser, MADM), and provides original music creation tools (e.g., Magix Music Maker, Ableton Live) based on the analysis results.

[0200] Example: Providing an interface that allows users to create original music based on the musical characteristics of artists analyzed by the server.

[0201] Example prompt: "Give me a tool to create music in the style of the artist."

[0202] Social networking service posting support tool

[0203] The server retrieves the user's past social media posts, analyzes the content and engagement of the posts, and uses social media data analysis tools (e.g., Hootsuite, Sprout Social) to generate text for new posts using natural language generation technology (e.g., GPT-3, BERT).

[0204] Example: If a user wants to post their impressions of a concert on social media but isn't sure how to write it, the server analyzes past trends and generates and provides new text for the post.

[0205] Example prompt: "Generate text to post on social media about your impressions of the concert."

[0206] Performance Analysis Tools

[0207] The server collects past live video and audio recordings and analyzes performance trends, track lists, and audience reactions using video analysis tools (e.g., OpenCV, FFmpeg) and audio analysis tools (e.g., LibROSA, Praat).

[0208] Example: A server provides a user with a list of songs that are likely to be played at an upcoming live show.

[0209] Example prompt: "Predict the song most likely to be played at the next live show."

[0210] Real-time tracking methods

[0211] The server monitors the artist's social media accounts and official website, collecting new posts and news in real time using web scraping tools (e.g., Beautiful Soup, Scrapy) and APIs.

[0212] Example: The server monitors in real time and notifies users immediately when there is a new post or news.

[0213] Example prompt: "Please notify me of real-time updates on artist names."

[0214] Item recommendation method

[0215] The server analyzes the user's purchase history and selects items that match the user's preferences from a database of artist-related products. The analysis is performed using a purchase history analysis tool (e.g., Google Analytics, Tableau).

[0216] Example: The server analyzes the user's preferences and recommends related items to assist with purchasing.

[0217] Example prompt: "Recommend artist-related products based on the user's purchasing history."

[0218] Art creation means

[0219] The server collects the artist's image data and analyzes its style and characteristics using image analysis tools (e.g., TensorFlow, Keras). Based on the analysis results, fan art is generated and made available for users to download.

[0220] Example: If a user wants to create fan art of an artist, the server analyzes the style and serves the generated fan art to the user.

[0221] Example prompt: "Generate fan art of artist name."

[0222] This allows the system to effectively manage and analyze a wide range of information and provide multifunctional services to support fan activities, allowing users to improve the efficiency of their fan activities and enjoy a richer experience.

[0223] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0224] Providing new information

[0225] Step 1:

[0226] The server receives the artist name as input from the user, specifically, the server retrieves the artist name through a web interface.

[0227] Step 2:

[0228] The server collects data from public databases, news sites, social networking services, and official websites on the Internet using web scraping tools (e.g., Beautiful Soup, Scrapy) or APIs. The input is artist names, and the output is the collected, unparsed data.

[0229] Step 3:

[0230] The server analyzes the collected data using natural language processing techniques (e.g., SpaCy, NLTK) to evaluate its relevance and importance. The input is the collected data, and the output is the analyzed information.

[0231] Step 4:

[0232] The server filters the results of the analysis and extracts only the information that is deemed important to the user. The input is the analyzed information, and the output is the filtered information.

[0233] Step 5:

[0234] The server sends the filtered information to the user's device via push notification or email. It uses a notification service such as Firebase or SendGrid. The input is the filtered information, and the output is the notification sent to the user.

[0235] Original song creation support

[0236] Step 1:

[0237] The user inputs the artist's musical style into the system, and the server retrieves the artist's name through a web interface.

[0238] Step 2:

[0239] The server uses the music streaming service API (e.g., Spotify API, YouTube Data API) to obtain the artist's song data. The input is the artist name, and the output is the obtained song data.

[0240] Step 3:

[0241] The server uses a music analysis tool (e.g., LibROSA, Essentia) to analyze the rhythm, melody, chords, tempo, etc. of the song. The input is the song data, and the output is the analysis results.

[0242] Step 4:

[0243] The server provides users with original music creation tools (e.g., Magix Music Maker, Ableton Live). The input is the analysis results, and the output is the creation tools provided to users.

[0244] Step 5:

[0245] Users create original music using the provided tools. The input is the creation tool and the user's actions, and the output is a new original piece of music.

[0246] SNS posting support

[0247] Step 1:

[0248] The server connects to SNS APIs (e.g., Twitter API, Facebook Graph API) to retrieve users' past SNS posts. The input is user account information, and the output is the retrieved past post data.

[0249] Step 2:

[0250] The server analyzes the post content and engagement using a social media data analysis tool (e.g., Hootsuite, Sprout Social Analytics). The input is past post data, and the output is the analysis results.

[0251] Step 3:

[0252] The server generates text for new posts using natural language generation techniques (e.g., GPT-3, BERT). The input is the analysis result, and the output is the generated text.

[0253] Step 4:

[0254] The user checks and edits the generated text and posts it to the social networking site. The input is the generated text and the user's edits, and the output is the posted social networking site content.

[0255] Performance Analysis

[0256] Step 1:

[0257] The server uses the YouTube Data API and Spotify API to collect past live video and audio data. The input is live event information, and the output is the captured video and audio data.

[0258] Step 2:

[0259] The server analyzes the performance data using video analysis tools (e.g., OpenCV, Dlib) and audio analysis tools (e.g., LibROSA, Praat). The input is video and audio data, and the output is the analysis results.

[0260] Step 3:

[0261] The server uses machine learning models (e.g., LSTM, Random Forest) to predict the songs that are likely to be played at the next live show based on the analysis results. The input is the analysis results, and the output is the predicted song list.

[0262] Step 4:

[0263] The server proposes effective cheering methods to the user. The input is a predicted song list, and the output is a suggested cheering method.

[0264] Real-time tracking

[0265] Step 1:

[0266] The server sets up a web scraping tool (e.g., Beautiful Soup, Scrapy) or API to monitor artists' social media accounts and official websites. The input is the monitored account information, and the output is the collected real-time information.

[0267] Step 2:

[0268] The server analyzes and organizes the collected information in real time. The input is real-time information, and the output is organized information.

[0269] Step 3:

[0270] The server immediately sends a notification to the user's device. It uses a notification service such as Firebase or SendGrid. The input is organized information, and the output is the notification sent to the user.

[0271] Item Recommendations

[0272] Step 1:

[0273] The server obtains the user's purchase history. Specifically, it retrieves information from a database where purchase history is stored. The input is the user's account information, and the output is the obtained purchase history data.

[0274] Step 2:

[0275] The server analyzes the purchase history using a purchase history analysis tool (e.g., Google Analytics, Tableau). The input is the purchase history data, and the output is the analysis results.

[0276] Step 3:

[0277] The server selects items that match the user's preferences from a database of artist-related products. The input is the analysis results, and the output is a list of recommended items.

[0278] Step 4:

[0279] The server proposes a recommended item list to the user. The input is the item list, and the output is the item recommendations notified to the user.

[0280] Artwork Creation

[0281] Step 1:

[0282] The server collects image data of artists. Specifically, it retrieves images from the Internet using a web crawler or API. The input is the artist's name, and the output is the collected image data.

[0283] Step 2:

[0284] The server analyzes the image data using image analysis tools (e.g., TensorFlow, Keras). The analysis includes extracting styles and features. The input is the image data, and the output is the analysis results.

[0285] Step 3:

[0286] The server uses a generative AI model to generate fan art based on the analysis results. The input is the analysis results, and the output is the generated fan art.

[0287] Step 4:

[0288] The server prepares the generated fan art as a download resource for the user. The input is the generated fan art, and the output is a download link provided to the user.

[0289] (Application example 1)

[0290] 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."

[0291] The goal of this project is to solve the problem of fans finding it difficult to efficiently gather the latest information on specific topics and obtain it in real time. In particular, there is a lack of means to gather news and social media information in a timely manner and notify users every five minutes.

[0292] 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.

[0293] In this invention, the server includes an information collection means, an analysis means, a notification means, a purchase support means, a generation means, a strategy formulation means, a means for collecting news and SNS information related to a specific target in real time, and a means for notifying the collected information every five minutes, thereby enabling fans to receive the latest information related to the specific target in a timely manner.

[0294] "Information gathering means" refers to means of gathering information about a specific subject from public databases, news sites, social networking services, official websites, etc. on the Internet.

[0295] The "analysis means" is a means for evaluating the importance and relevance of collected information and filtering it.

[0296] "Notification means" refers to a means of providing filtered information to a user's device via push notification or email.

[0297] "Purchase support means" refers to means for supporting a user's purchase.

[0298] "Generation means" refers to the means for creating new data or content.

[0299] "Strategy formulation tools" are means for creating optimal action plans based on collected and analyzed information.

[0300] "Means for collecting news and social media information about a specific subject in real time" refers to means for instantly collecting the latest news articles and posts on social networking services about a specific subject.

[0301] "Means for notifying collected information every 5 minutes" refers to means for notifying the user of the latest collected information every 5 minutes.

[0302] This invention relates to a system that efficiently collects, analyzes, and provides users with the latest information on a specific subject in real time. This system includes information collection means, analysis means, notification means, purchase support means, generation means, strategy formulation means, means for collecting news and SNS information on the specific subject in real time, and means for notifying users of the collected information every five minutes.

[0303] Program processing

[0304] The server executes a program in the following procedure to collect the latest information on a specific subject. First, it uses an information collection means to collect information on the specific subject from public databases on the Internet, news sites, social networking services, official websites, etc. Next, it uses an analysis means to analyze the collected information and filter it according to importance and relevance. Then, it uses a notification means to send the filtered information to the user's device every five minutes. This allows the user to receive the latest information on the specific subject in real time.

[0305] Hardware and software used

[0306] The hardware used includes a server, the user's smartphone or head-mounted display, and the software used is a Python program, the Twitter API, BeautifulSoup (a scraping library), APScheduler (a scheduling library), and SMTP (an email sending protocol).

[0307] Specific examples

[0308] As a concrete example, consider the case where a user wants to track the latest information about an artist named "Your Favorite Artist." In this system, all a user needs to do is enter the artist's name, and the server will monitor news sites and social media in real time, collecting data whenever new information is posted. The collected data is filtered using an analysis method to select important information. The filtered information is then sent to the user's smartphone every five minutes using a notification method, ensuring that the user always has the latest information at their fingertips.

[0309] Prompt Sentence Examples

[0310] An example of a prompt to input to a generative AI model would be:

[0311] "Please create a system that notifies me of the latest updates about my favorite artist. This system will use the Twitter API to collect the artist's latest tweets, scrape Google News to get related news, and send me an email with the collected information every 5 minutes."

[0312] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0313] Step 1:

[0314] The server uses information gathering tools to collect the latest information about a specific subject from public databases, news sites, social networking services, and official websites on the Internet. The input is the name of the target (e.g., artist name), and the output is the collected raw data. Specifically, the server performs web scraping or API requests to retrieve articles and posts related to the target.

[0315] Step 2:

[0316] The server analyzes the collected raw data using analytical methods. The input is the collected raw data, and the output is filtered information. Specifically, the server uses natural language processing technology to analyze the text data and filter it according to importance and relevance. For example, it scores news article headlines and social media posts and selects only those with high scores.

[0317] Step 3:

[0318] The server uses a notification method to send the filtered information to the user's device. The input is the filtered information, and the output is a notification displayed on the user's device. Specifically, the server uses the SMTP protocol to send emails or an API that implements push notifications to the user's smartphone or head-mounted display.

[0319] Step 4:

[0320] The server constantly monitors the latest information using a method for collecting news and social media information about a specific subject in real time. The input is the name of the specific subject (e.g., artist name), and the output is the collected real-time data. Specifically, the server collects information at set intervals (e.g., every 5 minutes) and continuously performs API requests and web scraping.

[0321] Step 5:

[0322] The server periodically sends the latest information to the user's device using a method that notifies the collected information every 5 minutes. The input is the collected real-time data, and the output is a notification sent every 5 minutes. Specifically, the server uses APScheduler to schedule and notify the user of filtered information at regular intervals.

[0323] Step 6:

[0324] By receiving notifications, users can obtain the latest information about specific subjects in real time. The input is the notification sent from the server, and the output is the latest information received by the user. Specifically, notifications are displayed on the user's smartphone or head-mounted display, allowing the user to instantly check the latest information.

[0325] 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.

[0326] The present invention relates to a system that efficiently collects and analyzes the latest information about a specific subject (hereinafter referred to as "artist"), supports fan activities, recognizes user emotions, and provides services based on those emotions. This system includes information collection means, analysis means, notification means, purchase support means, generation means, strategy formulation means, and an emotion engine.

[0327] 1. Providing new information

[0328] Program processing

[0329] The server uses the artist's name as a key to collect information from public databases on the Internet, news sites, social networking services, and official websites. The information collected by the server is analyzed using natural language processing technology and filtered based on relevance and importance. The filtered information is then delivered to the user's device via push notification or email. Furthermore, an emotion engine analyzes the user's emotions and delivers the filtered results in a format appropriate to the emotion.

[0330] Specific examples

[0331] A user wants to track the latest information about a particular artist and enters the artist's name into the system. The server collects information about the artist from multiple sources on the Internet and filters out important news, articles, and social media posts. The emotion engine analyzes the user's emotions, determines which information is most relevant, and notifies the user.

[0332] 2. Support for creating original songs

[0333] Program processing

[0334] The server acquires the artist's song data and analyzes musical elements such as rhythm, melody, chords, and tempo. Based on the analysis results, it provides an original song creation tool that users can use to create original songs. The emotion engine analyzes the user's emotions and makes song creation suggestions.

[0335] Specific examples

[0336] If a user wants to create a song in the style of a certain artist, they specify the artist's musical style to the system. The server analyzes the artist's song data and extracts musical characteristics. The emotion engine analyzes the user's emotions when creating the song and suggests appropriate templates and tools to help create a song that is more suited to the user.

[0337] 3. Social media posting support

[0338] Program processing

[0339] The server retrieves the user's past social media posts and analyzes their content and engagement. The server uses natural language generation technology to generate text for new posts and presents it to the user. The emotion engine analyzes the user's current emotions and adjusts the post text to match those emotions. The user can then review the generated text, edit it, and post it.

[0340] Specific examples

[0341] If a user is thinking about posting their impressions of a concert on social media but is unsure how to write it, they can link their past social media posts to the system. The server analyzes past trends and generates text for a new post, and an emotion engine analyzes the user's current emotions and adjusts the text accordingly. The user can use that text as a reference when posting.

[0342] 4. Performance Analysis

[0343] Program processing

[0344] The server collects past live footage and audio, and analyzes performance trends, track lists, and audience reactions. Based on the analysis results, it suggests songs that are likely to be played at the next live show and effective cheering methods to users. The emotion engine analyzes the user's emotions and adjusts cheering methods and performance analysis results based on their emotions.

[0345] Specific examples

[0346] If a user wants to predict what songs will be played at the next live concert, they register the live concert information in the system. The server analyzes past performance data and creates a list of songs that are likely to be played at the next live concert. The emotion engine analyzes the user's emotions and suggests appropriate ways to cheer.

[0347] 5. Real-time tracking

[0348] Program processing

[0349] The server monitors artists' social media accounts and official websites, collecting new posts and news in real time. The collected information is organized and instantly sent to the user's device. The emotion engine analyzes the user's emotions, selecting important information and adjusting the content of notifications.

[0350] Specific examples

[0351] If a user wants to keep up with the latest news about their favorite artist, they can register the artist's social media account in the system. The server monitors the account in real time and notifies the user immediately when new posts or news are posted. The emotion engine analyzes the user's emotions, determines which information is most useful to the user, and adjusts the notification content accordingly.

[0352] 6. Item Recommendations

[0353] Program processing

[0354] The server analyzes the user's purchasing history and selects items that match the user's preferences from a database of artist-related products. The selected items are then recommended to the user via push notification or email. The emotion engine analyzes the user's emotions and suggests the optimal items to increase their desire to purchase.

[0355] Specific examples

[0356] When a user wants to purchase new merchandise from an artist, they connect their past purchase history to the system. The server analyzes their preferences and recommends related items, and the emotion engine analyzes the user's emotions and suggests items that will increase their desire to purchase.

[0357] 7. Fan Art Generation

[0358] Program processing

[0359] The server collects image data of artists and analyzes their style and characteristics. Based on the analysis results, AI is used to generate fan art, which is then provided to the user in a downloadable format. An emotion engine analyzes the user's emotions and adjusts the style and content of the generated fan art.

[0360] Specific examples

[0361] When a user wants to create fan art of an artist, they provide an image of the artist to the system. The server analyzes the style and provides AI-generated fan art. The emotion engine analyzes the user's emotions and adjusts the style and content of the fan art to provide fan art that is more suited to the user.

[0362] 8. Develop an event strategy

[0363] Program processing

[0364] The server collects artist tour information and live event information. Based on the collected information, it formulates the optimal ticket purchasing strategy. The server analyzes the user's emotions using an emotion engine, adjusts the existing strategy, and provides it to the user. The server supports the purchasing process by notifying the user of information on the best time to purchase and how to select the best tickets.

[0365] Specific examples

[0366] If a user wants to buy tickets to an upcoming live event but doesn't know the best way to do so, they register the tour information in the system. The server analyzes the event information and formulates the optimal ticket purchasing strategy. The emotion engine analyzes the user's emotions, adjusts the strategy, provides the user with appropriate information, and assists the user in the purchasing process.

[0367] In this way, this system effectively manages and analyzes a wide variety of information, and provides a multifunctional service that supports fan activities while taking into account users' emotions. By using this system, users can improve the efficiency of their fan activities and enjoy a richer experience.

[0368] The processing flow will be explained below.

[0369] 1. Providing new information

[0370] Program processing

[0371] Step 1:

[0372] The server uses the name of a specific artist as a key to collect information from public databases, news sites, social networking services, and official websites on the Internet.

[0373] Step 2:

[0374] The server analyzes the collected information using natural language processing (NLP) techniques to evaluate its importance and relevance.

[0375] Step 3:

[0376] The server filters the information based on the evaluation results and removes unnecessary data.

[0377] Step 4:

[0378] The emotion engine analyzes the user's emotions and adjusts the filtered information to suit the user's current emotions.

[0379] Step 5:

[0380] The server sends the adjusted information to the user's device via push notification or email.

[0381] 2. Support for creating original songs

[0382] Program processing

[0383] Step 1:

[0384] The server acquires music data of the specified artist.

[0385] Step 2:

[0386] The server analyzes the music data and extracts musical features such as rhythm, melody, chords, and tempo.

[0387] Step 3:

[0388] The server generates a music composition tool based on the extracted features and provides it to the user's device.

[0389] Step 4:

[0390] The emotion engine analyzes the user's emotions and adjusts song-making suggestions based on the user's current emotions.

[0391] Step 5:

[0392] The user creates an original piece of music using the provided music creation tool.

[0393] 3. Social media posting support

[0394] Program processing

[0395] Step 1:

[0396] The server retrieves the user's past SNS posting data.

[0397] Step 2:

[0398] The server analyzes past posts' content, tone, and engagement.

[0399] Step 3:

[0400] The emotion engine analyzes the user's current emotions and predicts the content of the text based on past posting data and current emotions.

[0401] Step 4:

[0402] The server uses natural language generation (NLG) technology to generate text for new posts.

[0403] Step 5:

[0404] The server presents the generated text to the user's terminal.

[0405] Step 6:

[0406] The user checks the presented text, edits it, and posts it to a social networking site.

[0407] 4. Performance Analysis

[0408] Program processing

[0409] Step 1:

[0410] The server collects past live footage and audio data.

[0411] Step 2:

[0412] The server analyzes the collected data and extracts information about the songs being performed, audience reactions, and performance trends.

[0413] Step 3:

[0414] The emotion engine analyzes the user's emotions and adjusts the performance analysis results based on the user's current emotions.

[0415] Step 4:

[0416] The server predicts the likely song list and cheering methods for the next live show.

[0417] Step 5:

[0418] The server provides the prediction information to the user's terminal.

[0419] 5. Real-time tracking

[0420] Program processing

[0421] Step 1:

[0422] The server monitors the artist's social media accounts and official website.

[0423] Step 2:

[0424] The server collects new posts and news in real time.

[0425] Step 3:

[0426] The server organizes the collected information and selects information that is important to the user.

[0427] Step 4:

[0428] The emotion engine analyzes the user's emotions and adjusts the information it notifies based on the user's current emotions.

[0429] Step 5:

[0430] The server immediately notifies the user's terminal of the adjusted important information.

[0431] 6. Item Recommendations

[0432] Program processing

[0433] Step 1:

[0434] The server acquires the user's past purchase history.

[0435] Step 2:

[0436] The server analyzes the purchase history and understands the user's preferences.

[0437] Step 3:

[0438] The emotion engine analyzes user emotions and adjusts item recommendations based on preferences and emotions.

[0439] Step 4:

[0440] The server selects items that match the user's preferences from a database of artist-related products available on the market.

[0441] Step 5:

[0442] The server will then suggest the selected items to the user's device via push notification or email.

[0443] 7. Fan Art Generation

[0444] Program processing

[0445] Step 1:

[0446] The server collects image data of artists and analyzes their styles and characteristics.

[0447] Step 2:

[0448] The server uses AI to generate fan art based on the analysis results.

[0449] Step 3:

[0450] The emotion engine analyzes the user's emotions and adjusts the style and content of the generated fan art.

[0451] Step 4:

[0452] The server provides the generated fan art in a downloadable format to the user's device.

[0453] 8. Develop an event strategy

[0454] Program processing

[0455] Step 1:

[0456] The server collects information about artists' tours and live events.

[0457] Step 2:

[0458] Based on the event information collected by the server, the optimal ticket purchasing strategy is developed.

[0459] Step 3:

[0460] The emotion engine analyzes users' emotions and adjusts strategies based on their preferences when attending events.

[0461] Step 4:

[0462] The server provides the strategic information formulated by the server to the user's device to support the purchase process.

[0463] Step 5:

[0464] Based on the information provided by the user, the user purchases tickets at the optimal time and participates in the event.

[0465] Example 2

[0466] 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."

[0467] Many users need a system that efficiently collects and analyzes the latest information about a specific subject and supports fan activities. Additionally, recognizing users' emotions and providing appropriate information and services based on those emotions offers new value not found in conventional systems. However, current methods lack the accuracy of information collection and appropriate information filtering, and it is difficult to provide services that take users' emotions into account.

[0468] 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.

[0469] In this invention, the server includes an information collection means, an analysis means, and a notification means. This makes it possible to efficiently collect and analyze the latest information on a specific subject and provide information filtered based on importance to the user's terminal. Furthermore, by including an emotion analysis means, it is possible to provide appropriate information based on the user's emotions and more effectively support fan activities.

[0470] "Information gathering means" refers to means for gathering information from public databases, news sites, social networking services, and official websites on the Internet.

[0471] "Analysis means" refers to a means for analyzing collected information using natural language processing technology, evaluating its relevance and importance, and filtering it.

[0472] The "notification means" is a means for providing filtered information to a user's device via push notification or email.

[0473] The "purchase support means" is a means for recommending appropriate items and supporting the purchase process to assist users in purchasing artist-related products.

[0474] "Information generation means" means a means for generating new text or content for a user using a generative AI model.

[0475] "Strategy formulation tools" are tools for formulating strategies for taking optimal actions and decisions based on collected and analyzed information.

[0476] The "emotion analysis means" is a means for analyzing the user's emotions and adjusting the information provided and service content based on the analysis.

[0477] The present invention relates to a system that efficiently collects and analyzes the latest information about a specific subject (hereinafter referred to as "artist"), supports fan activities, recognizes user emotions, and provides services based on those emotions. This system includes information collection means, analysis means, notification means, purchase support means, information generation means, strategy formulation means, and emotion analysis means.

[0478] Information gathering methods

[0479] The server uses the artist's name as a key to collect information from public databases on the Internet, news sites, social networking services, and official websites. The server then uses scraping technology and APIs to obtain text data and stores it in a database. This allows data collected from a wide variety of sources to be managed centrally.

[0480] Analysis means

[0481] The server analyzes the collected information using natural language processing (NLP) technology. Specifically, it performs entity recognition, article summarization, sentiment analysis, etc., and scores the information for its relevance and importance. Based on the results of this analysis, it filters out information with high scores and excludes data with low scores, extracting only useful information.

[0482] Notification means

[0483] The server then provides the filtered information to the user's device via push notification or email. The notification method includes a custom notification function based on user settings, providing information at the optimal time based on the user's time and interests. Furthermore, an emotion analysis method is used to analyze the user's current emotions and adjust the notification content to suit the user's state, resulting in more user-friendly notifications.

[0484] Purchasing support methods

[0485] The server analyzes the user's purchasing history and selects items that match the user's preferences from a database of artist-related products. The selected items are then recommended to the user via push notification or email, and sentiment analysis techniques are used to suggest optimal items to increase purchasing motivation.

[0486] Information generation means

[0487] The server uses the generative AI model to generate new text and content for the user. For example, when generating text for a user to post on social media, the server analyzes the user's past posting data and engagement data to create an effective post. It also uses sentiment analysis to adjust the generated text to match the user's current emotions.

[0488] Example prompt sentence:

[0489] Describe how you would handle a system that helps users create original music in the style of a specific artist.

[0490] Strategy formulation tools

[0491] The server formulates strategies for optimal actions and decisions based on the collected and analyzed information. In particular, it formulates optimal ticket purchasing strategies based on artist tour information and live event information, and notifies users of the appropriate timing for purchase and how to select tickets. Emotion analysis takes into account the user's emotional state and adjusts the strategy to provide optimal support to the user.

[0492] Emotion analysis means

[0493] The server uses emotion analysis tools to analyze the user's emotions. This involves analyzing the user's social media posts, email content, and system action logs to understand the user's current emotional state. The analysis results are used in conjunction with other tools to adjust notification content and personalize information provision.

[0494] This system allows users to efficiently collect the latest information about specific artists in real time and receive filtered information based on analysis results. Furthermore, through sentiment analysis, it provides users with the information they need most at the optimal time, enhancing their fan activities.

[0495] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0496] Step 1: Gather information

[0497] The server uses the artist's name as a key to collect information from public databases, news sites, social networking services, and official websites on the Internet. Specifically, it uses scraping technology and APIs to obtain text data and stores it in a database. The input is the artist's name and the URL of the source of information, and the output is reviewable text data.

[0498] Step 2: Information analysis

[0499] The server analyzes the collected information using natural language processing (NLP) technology. Specifically, it performs entity recognition, article summarization, and sentiment analysis, and scores the relevance and importance of the information. The input is the text data collected in Step 1, and the output is the analyzed data with an importance score.

[0500] Step 3: Information filtering

[0501] The server filters the information based on the analysis results. Specifically, it keeps information with high scores and filters out data with low importance. The input is the analysis data generated in step 2, and the output is the filtered, useful information.

[0502] Step 4: Prepare for notification

[0503] The server prepares the filtered information for notification. Specifically, it formats it into a push notification or email format based on the user's settings. The input is the filtered information, and the output is the message data for notification.

[0504] Step 5: Sentiment analysis

[0505] The server analyzes the user's emotions. Specifically, it analyzes the user's social media posts and the system's action logs to understand the user's current emotional state. The input is the user's past data, and the output is data that represents the user's current emotional state.

[0506] Step 6: Send notification

[0507] The server sends the notification message data to the user's device. It reflects the emotion analysis data and adjusts the notification content according to the user's emotion. The input is the message data prepared in step 4 and the emotion analysis data generated in step 5, and the output is the notification sent to the user.

[0508] Step 7: User Verification

[0509] The user checks the notification through their device. Specifically, they receive a push notification or email on their device and view the content. The input is the notification data, and the output is the user's confirmation action.

[0510] Step 8: Gather feedback

[0511] The server collects user feedback, for example, by logging user reactions and actions to notifications. The input is the user action log, and the output is the feedback data.

[0512] In this way, by clearly indicating the specific operations and data flow at each step, it becomes easier to understand the processing of the entire system.

[0513] (Application example 2)

[0514] 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."

[0515] Conventional entertainment systems lack a means for users to obtain real-time updates about their favorite artists in autonomous vehicles, making it difficult to analyze users' emotions and provide appropriate information. Therefore, to improve the user experience, a comprehensive entertainment system that includes real-time information provision and emotion analysis is needed.

[0516] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an information collection means, an analysis means, a notification means, an emotion analysis means, an in-vehicle entertainment system, and a real-time information provision means. This enables a user in an autonomous vehicle to obtain the latest information about their favorite artist in real time and to provide optimal information and services based on the user's emotions.

[0517] "Information gathering means" refers to the means of gathering the latest information about a specific subject from public databases, news sites, social networking services, official websites, etc. on the Internet.

[0518] "Analysis means" refers to a means for evaluating the importance and relevance of collected information and for filtering it.

[0519] "Notification means" refers to a means for notifying the user of the analyzed information, and includes push notifications, emails, voice alerts, etc.

[0520] "Purchase support means" refers to means for supporting the process of users purchasing products and services related to their favorite artists.

[0521] The "generation means" is a means for generating new content or information based on a user's request.

[0522] "Strategy formulation means" is a means for formulating optimal action strategies based on collected and analyzed information.

[0523] "Emotion analysis means" is a means for analyzing a user's emotions and providing appropriate information and services based on the results.

[0524] An "in-vehicle entertainment system" is a system that provides entertainment content such as music, videos, and games for users to enjoy inside an autonomous vehicle.

[0525] The "real-time information providing means" is a means for instantly providing users with the latest information collected in real time.

[0526] This invention constitutes an entertainment system that allows users in self-driving vehicles to obtain the latest information about their favorite artists in real time and provide optimal content and services through emotion analysis.

[0527] The server is equipped with information collection means, analysis means, notification means, sentiment analysis means, an in-vehicle entertainment system, and real-time information provision means, improving the user experience and enabling users to enjoy important information about artists even while on the move.

[0528] Hardware and Software Description

[0529] Hardware:

[0530] Infotainment displays for autonomous vehicles

[0531] Network Module

[0532] Sensor and camera system (for analyzing user emotions)

[0533] software:

[0534] Python script

[0535] News API

[0536] Twitter API

[0537] smtplib (Python email library)

[0538] TextBlob (text analysis library)

[0539] Program processing explanation

[0540] The server uses News API and Twitter API to gather the latest information about the artist from public databases, news sites, social networking services, and official websites on the Internet. The collected information undergoes sentiment analysis using TextBlob, an analytical tool, and is filtered based on its importance and relevance. The filtered information is then sent in real time to the user's email address and the infotainment display in the autonomous vehicle via a notification tool.

[0541] In addition, as a means of emotion analysis, the vehicle uses sensors and camera systems inside the vehicle to analyze the user's facial expressions and voice, and provides information optimized for the user based on the results. As a means of providing real-time information, the vehicle is equipped with a mechanism to immediately notify the user of new data collected in real time.

[0542] Specific examples

[0543] While traveling in an autonomous vehicle, users may not want to miss the latest information on their favorite artists. In such cases, users register the artist's name in the system. The server collects information about the artist from multiple sources on the Internet in real time and performs sentiment analysis and filtering using TextBlob. Important and relevant information is immediately notified to the user and displayed on the vehicle's infotainment display. In addition, sensors and camera systems analyze the user's facial expressions and voice to provide optimal content based on the user's emotions.

[0544] Example prompts for generative AI models:

[0545] "Create an application that provides real-time updates about a favorite artist in an autonomous vehicle's entertainment system. Analyze user sentiment, filter news and social media posts, and notify the user of the appropriate information."

[0546] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0547] Step 1:

[0548] The server receives the name of the artist registered by the user in the system. The input is the artist name registered by the user, and it sends a request to the News API or Twitter API using this as a key. The output is news articles or tweets about the artist.

[0549] Step 2:

[0550] The server analyzes collected news articles and tweets using Python's TextBlob library. The collected text data is used as input, and sentiment analysis and importance / relevance evaluation are performed. The output is filtered positive information.

[0551] Step 3:

[0552] The server sends the filtered information to the user's email address or the infotainment display in the autonomous vehicle. The filtered information and the user's notification settings are input, and based on this, the information is sent in the form of a push notification or email. The output is the user receiving the latest information in real time.

[0553] Step 4:

[0554] The server uses the in-car sensors and camera system to analyze the user's facial expressions and voice to understand their emotional state. The input is the user's facial expression data and voice data, and emotion analysis is performed based on this. The output is the user's emotional state.

[0555] Step 5:

[0556] The server selects the most appropriate content based on the user's emotional state and sends the notification again. The input is the user's emotional state and filtered information, and based on this, the server selects the most appropriate content and notification content. The output is information optimized for the user's emotions.

[0557] Step 6:

[0558] The user views the information notified via the infotainment display in the autonomous vehicle or on their smartphone. The input is the notified information, and by checking it, the user can grasp the latest information about the artist in real time. The output is an update of the user's knowledge about the artist.

[0559] 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.

[0560] 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.

[0561] 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.

[0562] [Second embodiment]

[0563] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0564] 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.

[0565] 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).

[0566] 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.

[0567] 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.

[0568] 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).

[0569] 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.

[0570] 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.

[0571] 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.

[0572] 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.

[0573] 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.

[0574] 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."

[0575] The present invention relates to a system that efficiently collects and analyzes the latest information about a specific subject (hereinafter referred to as "artist") and supports fan activities. This system includes information collection means, analysis means, notification means, purchase support means, generation means, and strategy formulation means.

[0576] 1. Providing new information

[0577] Program processing

[0578] The server periodically collects new information from multiple sources, including public databases on the Internet, news sites, social networking services, and official websites, using the artist's name as a key. The information collected by the server is analyzed using natural language processing technology and filtered based on relevance and importance. The filtered information is then delivered to the user's device via push notification or email.

[0579] Specific examples

[0580] A user wants to keep track of the latest information about a particular artist, so they input the artist's name into the system. The server then collects information about the artist from multiple sources on the Internet, filters out important news, articles, and social media posts, and notifies the user's device.

[0581] 2. Support for creating original songs

[0582] Program processing

[0583] The server acquires the artist's song data and analyzes musical elements such as rhythm, melody, chords, tempo, etc. Based on the analysis results, it provides an original song creation tool that users can use to create original songs.

[0584] Specific examples

[0585] If a user wants to create a song in the style of a certain artist, they specify the artist's musical style to the system. The server analyzes the artist's song data and extracts musical characteristics. The user can then use the provided templates and tools to create a song in the artist's style.

[0586] 3. Social media posting support

[0587] Program processing

[0588] The server retrieves the user's past social media posts and analyzes their content and engagement. The server then uses natural language generation technology to generate text for new posts and presents it to the user. The user can then review the generated text, edit it, and post it.

[0589] Specific examples

[0590] If a user is thinking about posting their impressions of a concert on social media but is unsure of how to write it, they can link their past social media posts to the system. The server analyzes past trends, generates text for a new post, and presents it to the user. The user can use that text as a reference when posting.

[0591] 4. Performance Analysis

[0592] Program processing

[0593] The server collects past live performance footage and audio, analyzes performance trends, song lists, and audience reactions, and based on the analysis results, suggests songs that are likely to be played at the next live performance and suggests effective ways to cheer on the band.

[0594] Specific examples

[0595] If a user wants to predict what songs will be played at an upcoming live concert, they register the concert information in the system. The server analyzes past performance data and shares with the user a list of songs that are likely to be played at the next live concert.

[0596] 5. Real-time tracking

[0597] Program processing

[0598] The server monitors artists' social media accounts and official websites, collecting new posts and news in real time. The collected information is organized and instantly sent to the user's device.

[0599] Specific examples

[0600] If a user wants to keep up with the latest news about their favorite artist, they can register the artist's social media account in the system. The server monitors the account in real time, and users are immediately notified of any new posts or news.

[0601] 6. Item Recommendations

[0602] Program processing

[0603] The server analyzes the user's purchasing history and selects items that match the user's preferences from a database of artist-related products. The selected items are then suggested to the user via push notification or email.

[0604] Specific examples

[0605] When a user wants to purchase new merchandise from an artist, they can connect their past purchase history to the system. The server analyzes their preferences, recommends related items, and supports the user in making the purchase.

[0606] 7. Fan Art Generation

[0607] Program processing

[0608] The server collects image data of artists, analyzes their style and characteristics, and generates fan art based on the analysis results, which is then made available for users to download.

[0609] Specific examples

[0610] When a user wants to create fan art of an artist, they provide an image of the artist to the system, and the server analyzes the style and provides the user with AI-generated fan art.

[0611] 8. Develop an event strategy

[0612] Program processing

[0613] The server collects information about artists' tours and live events, formulates the optimal ticket purchasing strategy, and notifies users of the timing of purchases and how to select the best tickets.

[0614] Specific examples

[0615] If a user wants to buy tickets to an upcoming live event but doesn't know the best way to do so, they register the tour information in the system. The server analyzes the event information and suggests the best ticket purchasing strategy to the user.

[0616] In this way, this system effectively manages and analyzes a wide variety of information and provides a multifunctional service to support fan activities. By using this system, users can improve the efficiency of their fan activities and have a richer experience.

[0617] The processing flow will be explained below.

[0618] 1. Providing new information

[0619] Program processing

[0620] Step 1:

[0621] The server uses the name of a specific artist as a key to collect information from public databases, news sites, social networking services, and official websites on the Internet.

[0622] Step 2:

[0623] The server analyzes the collected information using natural language processing (NLP) techniques to evaluate its importance and relevance.

[0624] Step 3:

[0625] The server filters the information based on the evaluation results and removes unnecessary data.

[0626] Step 4:

[0627] The server sends the filtered information to the user's device via push notification or email.

[0628] 2. Support for creating original songs

[0629] Program processing

[0630] Step 1:

[0631] The server acquires music data of the specified artist.

[0632] Step 2:

[0633] The server analyzes the music data and extracts musical features such as rhythm, melody, chords, and tempo.

[0634] Step 3:

[0635] The server generates a music composition tool based on the extracted features and provides it to the user's terminal.

[0636] Step 4:

[0637] The user creates an original piece of music using the provided music creation tool.

[0638] 3. Social media posting support

[0639] Program processing

[0640] Step 1:

[0641] The server retrieves the user's past SNS posting data.

[0642] Step 2:

[0643] The server analyzes past posts' content, tone, and engagement.

[0644] Step 3:

[0645] The server uses natural language generation (NLG) technology to generate text for new posts.

[0646] Step 4:

[0647] The server presents the generated text to the user's terminal.

[0648] Step 5:

[0649] The user checks the presented text, edits it, and posts it to a social networking site.

[0650] 4. Performance Analysis

[0651] Program processing

[0652] Step 1:

[0653] The server collects past live footage and audio data.

[0654] Step 2:

[0655] The server analyzes the collected data and extracts information about the songs being performed, audience reactions, and performance trends.

[0656] Step 3:

[0657] Based on the analysis results, the server predicts the list of songs that are likely to be played at the next live concert and how to support the band.

[0658] Step 4:

[0659] The server provides the prediction information to the user's terminal.

[0660] 5. Real-time tracking

[0661] Program processing

[0662] Step 1:

[0663] The server monitors the artist's social media accounts and official website.

[0664] Step 2:

[0665] The server collects new posts and news in real time.

[0666] Step 3:

[0667] The server organizes the collected information and selects information that is important to the user.

[0668] Step 4:

[0669] The server immediately notifies the user's device of important information.

[0670] 6. Item Recommendations

[0671] Program processing

[0672] Step 1:

[0673] The server acquires the user's past purchase history.

[0674] Step 2:

[0675] The server analyzes the purchase history and understands the user's preferences.

[0676] Step 3:

[0677] The server selects items that match the user's preferences from a database of artist-related products available on the market.

[0678] Step 4:

[0679] The server will then suggest the selected items to the user's device via push notification or email.

[0680] 7. Fan Art Generation

[0681] Program processing

[0682] Step 1:

[0683] The server collects image data of artists and analyzes their styles and characteristics.

[0684] Step 2:

[0685] The server uses AI to generate fan art based on the analysis results.

[0686] Step 3:

[0687] The server provides the generated fan art in a downloadable format to the user's device.

[0688] 8. Develop an event strategy

[0689] Program processing

[0690] Step 1:

[0691] The server collects information about artists' tours and live events.

[0692] Step 2:

[0693] Based on the event information collected by the server, the optimal ticket purchasing strategy is developed.

[0694] Step 3:

[0695] The server provides the strategic information formulated by the server to the user's device to support the purchase process.

[0696] Step 4:

[0697] Based on the information provided by the user, the user purchases tickets at the optimal time and participates in the event.

[0698] Example 1

[0699] 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."

[0700] Conventional fan activity support systems are inefficient in collecting and analyzing the latest information on specific subjects, making it difficult for users to efficiently obtain information and improve the quality of their activities. Furthermore, they lack support for music creation and posting to social networking services, performance analysis, and real-time information tracking, making it difficult for users to centrally manage a wide range of activities. Analytical methods for properly evaluating the relevance and importance of information are also inadequate, creating a need for a method that provides only useful information to users.

[0701] 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.

[0702] In this invention, the server includes an information collection means, an analysis means, a notification means, a purchase support means, a generation means, a strategy formulation means, a music creation support means, a social network service posting support means, a performance analysis means, a real-time tracking means, an item recommendation means, and an artwork creation means, thereby enabling centralized and effective support for a wide range of fan activities, such as efficient collection and analysis of the latest information on a specific subject, timely notification to users, music creation support, social network service posting support, performance analysis, real-time information tracking, item recommendation, and fan art generation.

[0703] "Information gathering means" refers to the means of gathering the latest information on a specific subject from public databases, news sites, social networking services, and official websites on the Internet.

[0704] "Analysis means" refers to means for evaluating importance and relevance based on collected information and song data, data posted in the past on social networking services, and live performance data, and for filtering and analyzing the data.

[0705] "Notification means" refers to a means for sending filtered information to the user's device via push notification or email.

[0706] The "purchase support means" is a means for analyzing the user's purchase history and selecting and suggesting items that match the user's preferences from a database of artist-related products.

[0707] The "generation means" is a means for automatically generating new content and suggestions based on collected and analyzed data and providing them to users.

[0708] The "strategy formulation means" is a means for formulating an optimal ticket purchasing strategy based on artist tour information and live event information, and notifying the user of the strategy.

[0709] "Music composition support means" is a means for analyzing an artist's music data and providing a tool that enables a user to create original music based on the analysis results.

[0710] The "social network service posting support means" is a means for analyzing a user's past SNS posting data, automatically generating text for a new post, and providing it to the user.

[0711] "Performance analysis means" refers to a method of collecting past live performance footage and audio recordings, analyzing that data, and evaluating performance trends, song lists, and audience reactions.

[0712] "Real-time tracking means" refers to a means of monitoring an artist's social media accounts and official websites, collecting new posts and news in real time, and notifying users.

[0713] The "item recommendation means" is a means for analyzing the purchase history of a user and recommending highly relevant artist-related merchandise items.

[0714] The "artwork generation means" is a means for automatically generating fan art based on the artist's style and characteristics by analyzing the artist's image data and providing it to the user.

[0715] The present invention relates to a system for efficiently collecting and analyzing the latest information on a specific subject and supporting fan activities. The system includes an information collection means, an analysis means, a notification means, a purchasing support means, a creation means, a strategy formulation means, a music creation support means, a social network service posting support means, a performance analysis means, a real-time tracking means, an item recommendation means, and an art creation means.

[0716] Information gathering methods

[0717] The server uses information gathering tools to collect the latest information about the artist from public databases, news sites, social networking services, and official websites on the Internet, specifically using web scraping tools (e.g., Beautiful Soup, Scrapy) and APIs.

[0718] Example: A user wants to track the latest information about a particular artist and enters the artist's name into the system. The server collects information about the artist from multiple sources on the Internet, filters out important news, articles, and social media posts, and notifies the user's device.

[0719] Example prompt: "Please gather the latest information on the artist's name."

[0720] Analysis means

[0721] The server uses analytical tools to analyze the collected information, song data, past SNS posting data, and live performance data. Specifically, it uses text analysis tools (e.g., SpaCy, NLTK), music analysis tools (e.g., LibROSA, Essentia), and video analysis tools (e.g., OpenCV, Dlib).

[0722] Examples: Analyzing data collected by a server to evaluate importance and relevance and filter out noise on the Internet. Analyzing the content of news articles to extract important keywords and rank information based on importance and relevance.

[0723] Example prompt: "Analyze a news article about the artist's name."

[0724] Notification means

[0725] The server sends the filtered information to the user's device via push notification or email, using notification services such as Firebase or SendGrid.

[0726] Example: The server immediately sends filtered information to the user, allowing the user to grasp important information without missing it.

[0727] Example prompt: "Push important information to users."

[0728] Purchasing support methods

[0729] The server analyzes the user's purchase history and selects and suggests items that match the user's preferences from a database of artist-related products, using a purchase history analysis tool (e.g., Google Analytics, Tableau).

[0730] Example: If a user wants to buy new merchandise from an artist, the system analyzes their past purchase history and recommends related items.

[0731] Example prompt: "Recommend artist-related products based on the user's purchasing history."

[0732] generation means

[0733] The server uses a generating means to automatically generate new content and suggestions based on the collected and analyzed data and provide them to the user.

[0734] Example: The server analyzes the collected data and generates and provides useful articles and posts to users.

[0735] Example prompt: "Generate the latest news article about an artist."

[0736] Strategy formulation tools

[0737] This is a method for the server to create the optimal ticket purchasing strategy based on artist tour information and live event information and notify users. Event information acquisition tools (e.g., Eventbrite, Ticketmaster API) are used to collect this information.

[0738] Example: If a user wants to purchase tickets to an upcoming live event but isn't sure how best to do so, the server analyzes the event information and suggests the best ticket purchasing strategy to the user.

[0739] Example prompt: "Suggest a ticket purchasing strategy for the next live event."

[0740] Music creation support tools

[0741] The server retrieves the artist's music data and analyzes the rhythm, melody, chords, and tempo using music analysis software (e.g., Sonic Visualiser, MADM), and provides original music creation tools (e.g., Magix Music Maker, Ableton Live) based on the analysis results.

[0742] Example: Providing an interface that allows users to create original music based on the musical characteristics of artists analyzed by the server.

[0743] Example prompt: "Give me a tool to create music in the style of the artist."

[0744] Social networking service posting support tool

[0745] The server retrieves the user's past social media posts, analyzes the content and engagement of the posts, and uses social media data analysis tools (e.g., Hootsuite, Sprout Social) to generate text for new posts using natural language generation technology (e.g., GPT-3, BERT).

[0746] Example: If a user wants to post their impressions of a concert on social media but isn't sure how to write it, the server analyzes past trends and generates and provides new text for the post.

[0747] Example prompt: "Generate text to post on social media about your impressions of the concert."

[0748] Performance Analysis Tools

[0749] The server collects past live video and audio recordings and analyzes performance trends, track lists, and audience reactions using video analysis tools (e.g., OpenCV, FFmpeg) and audio analysis tools (e.g., LibROSA, Praat).

[0750] Example: A server provides a user with a list of songs that are likely to be played at an upcoming live show.

[0751] Example prompt: "Predict the song most likely to be played at the next live show."

[0752] Real-time tracking methods

[0753] The server monitors the artist's social media accounts and official website, collecting new posts and news in real time using web scraping tools (e.g., Beautiful Soup, Scrapy) and APIs.

[0754] Example: The server monitors in real time and notifies users immediately when there is a new post or news.

[0755] Example prompt: "Please notify me of real-time updates on artist names."

[0756] Item recommendation method

[0757] The server analyzes the user's purchase history and selects items that match the user's preferences from a database of artist-related products. The analysis is performed using a purchase history analysis tool (e.g., Google Analytics, Tableau).

[0758] Example: The server analyzes the user's preferences and recommends related items to assist with purchasing.

[0759] Example prompt: "Recommend artist-related products based on the user's purchasing history."

[0760] Art creation means

[0761] The server collects image data of artists and analyzes their style and characteristics using image analysis tools (e.g., TensorFlow, Keras). Based on the analysis results, fan art is generated and made available for users to download.

[0762] Example: If a user wants to create fan art of an artist, the server analyzes the style and serves the generated fan art to the user.

[0763] Example prompt: "Generate fan art of artist name."

[0764] This allows the system to effectively manage and analyze a wide range of information and provide multifunctional services to support fan activities, allowing users to improve the efficiency of their fan activities and enjoy a richer experience.

[0765] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0766] Providing new information

[0767] Step 1:

[0768] The server receives the artist name as input from the user, specifically, the server retrieves the artist name through a web interface.

[0769] Step 2:

[0770] The server collects data from public databases, news sites, social networking services, and official websites on the Internet using web scraping tools (e.g., Beautiful Soup, Scrapy) or APIs. The input is artist names, and the output is the collected, unparsed data.

[0771] Step 3:

[0772] The server analyzes the collected data using natural language processing techniques (e.g., SpaCy, NLTK) to evaluate its relevance and importance. The input is the collected data, and the output is the analyzed information.

[0773] Step 4:

[0774] The server filters the results of the analysis and extracts only the information that is deemed important to the user. The input is the analyzed information, and the output is the filtered information.

[0775] Step 5:

[0776] The server sends the filtered information to the user's device via push notification or email. It uses a notification service such as Firebase or SendGrid. The input is the filtered information, and the output is the notification sent to the user.

[0777] Original song creation support

[0778] Step 1:

[0779] The user inputs the artist's musical style into the system, and the server retrieves the artist's name through a web interface.

[0780] Step 2:

[0781] The server uses the music streaming service API (e.g., Spotify API, YouTube Data API) to obtain the artist's song data. The input is the artist name, and the output is the obtained song data.

[0782] Step 3:

[0783] The server uses a music analysis tool (e.g., LibROSA, Essentia) to analyze the rhythm, melody, chords, tempo, etc. of the song. The input is the song data, and the output is the analysis results.

[0784] Step 4:

[0785] The server provides users with original music creation tools (e.g., Magix Music Maker, Ableton Live). The input is the analysis results, and the output is the creation tools provided to users.

[0786] Step 5:

[0787] Users create original music using the provided tools. The input is the creation tool and the user's actions, and the output is a new original piece of music.

[0788] SNS posting support

[0789] Step 1:

[0790] The server connects to SNS APIs (e.g., Twitter API, Facebook Graph API) to retrieve users' past SNS posts. The input is user account information, and the output is the retrieved past post data.

[0791] Step 2:

[0792] The server analyzes the post content and engagement using a social media data analysis tool (e.g., Hootsuite, Sprout Social Analytics). The input is past post data, and the output is the analysis results.

[0793] Step 3:

[0794] The server generates text for new posts using natural language generation techniques (e.g., GPT-3, BERT). The input is the analysis result, and the output is the generated text.

[0795] Step 4:

[0796] The user checks and edits the generated text and posts it to the social networking site. The input is the generated text and the user's edits, and the output is the posted social networking site content.

[0797] Performance Analysis

[0798] Step 1:

[0799] The server uses the YouTube Data API and Spotify API to collect past live video and audio data. The input is live event information, and the output is the captured video and audio data.

[0800] Step 2:

[0801] The server analyzes the performance data using video analysis tools (e.g., OpenCV, Dlib) and audio analysis tools (e.g., LibROSA, Praat). The input is video and audio data, and the output is the analysis results.

[0802] Step 3:

[0803] The server uses machine learning models (e.g., LSTM, Random Forest) to predict the songs that are likely to be played at the next live show based on the analysis results. The input is the analysis results, and the output is the predicted song list.

[0804] Step 4:

[0805] The server proposes effective cheering methods to the user. The input is a predicted song list, and the output is a suggested cheering method.

[0806] Real-time tracking

[0807] Step 1:

[0808] The server sets up a web scraping tool (e.g., Beautiful Soup, Scrapy) or API to monitor artists' social media accounts and official websites. The input is the monitored account information, and the output is the collected real-time information.

[0809] Step 2:

[0810] The server analyzes and organizes the collected information in real time. The input is real-time information, and the output is organized information.

[0811] Step 3:

[0812] The server immediately sends a notification to the user's device. It uses a notification service such as Firebase or SendGrid. The input is organized information, and the output is the notification sent to the user.

[0813] Item Recommendations

[0814] Step 1:

[0815] The server obtains the user's purchase history. Specifically, it retrieves information from a database where purchase history is stored. The input is the user's account information, and the output is the obtained purchase history data.

[0816] Step 2:

[0817] The server analyzes the purchase history using a purchase history analysis tool (e.g., Google Analytics, Tableau). The input is the purchase history data, and the output is the analysis results.

[0818] Step 3:

[0819] The server selects items that match the user's preferences from a database of artist-related products. The input is the analysis results, and the output is a list of recommended items.

[0820] Step 4:

[0821] The server proposes a recommended item list to the user. The input is the item list, and the output is the item recommendations notified to the user.

[0822] Artwork Creation

[0823] Step 1:

[0824] The server collects image data of artists. Specifically, it retrieves images from the Internet using a web crawler or API. The input is the artist's name, and the output is the collected image data.

[0825] Step 2:

[0826] The server analyzes the image data using image analysis tools (e.g., TensorFlow, Keras). The analysis includes extracting styles and features. The input is the image data, and the output is the analysis results.

[0827] Step 3:

[0828] The server uses a generative AI model to generate fan art based on the analysis results. The input is the analysis results, and the output is the generated fan art.

[0829] Step 4:

[0830] The server prepares the generated fan art as a download resource for the user. The input is the generated fan art, and the output is a download link provided to the user.

[0831] (Application example 1)

[0832] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0833] The goal of this project is to solve the problem of fans finding it difficult to efficiently gather the latest information on specific topics and obtain it in real time. In particular, there is a lack of means to gather news and social media information in a timely manner and notify users every five minutes.

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

[0835] In this invention, the server includes an information collection means, an analysis means, a notification means, a purchase support means, a generation means, a strategy formulation means, a means for collecting news and SNS information related to a specific target in real time, and a means for notifying the collected information every five minutes, thereby enabling fans to receive the latest information related to the specific target in a timely manner.

[0836] "Information gathering means" refers to means of gathering information about a specific subject from public databases, news sites, social networking services, official websites, etc. on the Internet.

[0837] The "analysis means" is a means for evaluating the importance and relevance of collected information and filtering it.

[0838] "Notification means" refers to a means of providing filtered information to a user's device via push notification or email.

[0839] "Purchase support means" refers to means for supporting a user's purchase.

[0840] "Generation means" refers to the means for creating new data or content.

[0841] "Strategy formulation tools" are means for creating optimal action plans based on collected and analyzed information.

[0842] "Means for collecting news and social media information about a specific subject in real time" refers to means for instantly collecting the latest news articles and posts on social networking services about a specific subject.

[0843] "Means for notifying collected information every 5 minutes" refers to means for notifying the user of the latest collected information every 5 minutes.

[0844] This invention relates to a system that efficiently collects, analyzes, and provides users with the latest information on a specific subject in real time. This system includes information collection means, analysis means, notification means, purchase support means, generation means, strategy formulation means, means for collecting news and SNS information on the specific subject in real time, and means for notifying users of the collected information every five minutes.

[0845] Program processing

[0846] The server executes a program in the following procedure to collect the latest information on a specific subject. First, it uses an information collection means to collect information on the specific subject from public databases on the Internet, news sites, social networking services, official websites, etc. Next, it uses an analysis means to analyze the collected information and filter it according to importance and relevance. Then, it uses a notification means to send the filtered information to the user's device every five minutes. This allows the user to receive the latest information on the specific subject in real time.

[0847] Hardware and software used

[0848] The hardware used includes a server, the user's smartphone or head-mounted display, and the software used is a Python program, the Twitter API, BeautifulSoup (a scraping library), APScheduler (a scheduling library), and SMTP (an email sending protocol).

[0849] Specific examples

[0850] As a concrete example, consider the case where a user wants to track the latest information about an artist named "Your Favorite Artist." In this system, all a user needs to do is enter the artist's name, and the server will monitor news sites and social media in real time, collecting data whenever new information is posted. The collected data is filtered using an analysis method to select important information. The filtered information is then sent to the user's smartphone every five minutes using a notification method, ensuring that the user always has the latest information at their fingertips.

[0851] Prompt Sentence Examples

[0852] An example of a prompt to input to a generative AI model would be:

[0853] "Please create a system that notifies me of the latest updates about my favorite artist. This system will use the Twitter API to collect the artist's latest tweets, scrape Google News to get related news, and send me an email with the collected information every 5 minutes."

[0854] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0855] Step 1:

[0856] The server uses information gathering tools to collect the latest information about a specific subject from public databases, news sites, social networking services, and official websites on the Internet. The input is the name of the target (e.g., artist name), and the output is the collected raw data. Specifically, the server performs web scraping or API requests to retrieve articles and posts related to the target.

[0857] Step 2:

[0858] The server analyzes the collected raw data using analytical methods. The input is the collected raw data, and the output is filtered information. Specifically, the server uses natural language processing technology to analyze the text data and filter it according to importance and relevance. For example, it scores news article headlines and social media posts and selects only those with high scores.

[0859] Step 3:

[0860] The server uses a notification method to send the filtered information to the user's device. The input is the filtered information, and the output is a notification displayed on the user's device. Specifically, the server uses the SMTP protocol to send emails or an API that implements push notifications to the user's smartphone or head-mounted display.

[0861] Step 4:

[0862] The server constantly monitors the latest information using a method for collecting news and social media information about a specific subject in real time. The input is the name of the specific subject (e.g., artist name), and the output is the collected real-time data. Specifically, the server collects information at set intervals (e.g., every 5 minutes) and continuously performs API requests and web scraping.

[0863] Step 5:

[0864] The server periodically sends the latest information to the user's device using a method that notifies the collected information every 5 minutes. The input is the collected real-time data, and the output is a notification sent every 5 minutes. Specifically, the server uses APScheduler to schedule and notify the user of filtered information at regular intervals.

[0865] Step 6:

[0866] By receiving notifications, users can obtain the latest information about specific subjects in real time. The input is the notification sent from the server, and the output is the latest information received by the user. Specifically, notifications are displayed on the user's smartphone or head-mounted display, allowing the user to instantly check the latest information.

[0867] 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.

[0868] The present invention relates to a system that efficiently collects and analyzes the latest information about a specific subject (hereinafter referred to as "artist"), supports fan activities, recognizes user emotions, and provides services based on those emotions. This system includes information collection means, analysis means, notification means, purchase support means, generation means, strategy formulation means, and an emotion engine.

[0869] 1. Providing new information

[0870] Program processing

[0871] The server uses the artist's name as a key to collect information from public databases on the Internet, news sites, social networking services, and official websites. The information collected by the server is analyzed using natural language processing technology and filtered based on relevance and importance. The filtered information is then delivered to the user's device via push notification or email. Furthermore, an emotion engine analyzes the user's emotions and delivers the filtered results in a format appropriate to the emotion.

[0872] Specific examples

[0873] A user wants to track the latest information about a particular artist and enters the artist's name into the system. The server collects information about the artist from multiple sources on the Internet and filters out important news, articles, and social media posts. The emotion engine analyzes the user's emotions, determines which information is most relevant, and notifies the user.

[0874] 2. Support for creating original songs

[0875] Program processing

[0876] The server acquires the artist's song data and analyzes musical elements such as rhythm, melody, chords, and tempo. Based on the analysis results, it provides an original song creation tool that users can use to create original songs. The emotion engine analyzes the user's emotions and makes song creation suggestions.

[0877] Specific examples

[0878] If a user wants to create a song in the style of a certain artist, they specify the artist's musical style to the system. The server analyzes the artist's song data and extracts musical characteristics. The emotion engine analyzes the user's emotions when creating the song and suggests appropriate templates and tools to help create a song that is more suited to the user.

[0879] 3. Social media posting support

[0880] Program processing

[0881] The server retrieves the user's past social media posts and analyzes their content and engagement. The server uses natural language generation technology to generate text for new posts and presents it to the user. The emotion engine analyzes the user's current emotions and adjusts the post text to match those emotions. The user can then review the generated text, edit it, and post it.

[0882] Specific examples

[0883] If a user is thinking about posting their impressions of a concert on social media but is unsure how to write it, they can link their past social media posts to the system. The server analyzes past trends and generates text for a new post, and an emotion engine analyzes the user's current emotions and adjusts the text accordingly. The user can use that text as a reference when posting.

[0884] 4. Performance Analysis

[0885] Program processing

[0886] The server collects past live footage and audio, and analyzes performance trends, track lists, and audience reactions. Based on the analysis results, it suggests songs that are likely to be played at the next live show and effective cheering methods to users. The emotion engine analyzes the user's emotions and adjusts cheering methods and performance analysis results based on their emotions.

[0887] Specific examples

[0888] If a user wants to predict what songs will be played at the next live concert, they register the live concert information in the system. The server analyzes past performance data and creates a list of songs that are likely to be played at the next live concert. The emotion engine analyzes the user's emotions and suggests appropriate ways to cheer.

[0889] 5. Real-time tracking

[0890] Program processing

[0891] The server monitors artists' social media accounts and official websites, collecting new posts and news in real time. The collected information is organized and instantly sent to the user's device. The emotion engine analyzes the user's emotions, selecting important information and adjusting the content of notifications.

[0892] Specific examples

[0893] If a user wants to keep up with the latest news about their favorite artist, they can register the artist's social media account in the system. The server monitors the account in real time and notifies the user immediately when new posts or news are posted. The emotion engine analyzes the user's emotions, determines which information is most useful to the user, and adjusts the notification content accordingly.

[0894] 6. Item Recommendations

[0895] Program processing

[0896] The server analyzes the user's purchasing history and selects items that match the user's preferences from a database of artist-related products. The selected items are then recommended to the user via push notification or email. The emotion engine analyzes the user's emotions and suggests the optimal items to increase their desire to purchase.

[0897] Specific examples

[0898] When a user wants to purchase new merchandise from an artist, they connect their past purchase history to the system. The server analyzes their preferences and recommends related items, and the emotion engine analyzes the user's emotions and suggests items that will increase their desire to purchase.

[0899] 7. Fan Art Generation

[0900] Program processing

[0901] The server collects image data of artists and analyzes their style and characteristics. Based on the analysis results, AI is used to generate fan art, which is then provided to the user in a downloadable format. An emotion engine analyzes the user's emotions and adjusts the style and content of the generated fan art.

[0902] Specific examples

[0903] When a user wants to create fan art of an artist, they provide an image of the artist to the system. The server analyzes the style and provides AI-generated fan art. The emotion engine analyzes the user's emotions and adjusts the style and content of the fan art to provide fan art that is more suited to the user.

[0904] 8. Develop an event strategy

[0905] Program processing

[0906] The server collects artist tour information and live event information. Based on the collected information, it formulates the optimal ticket purchasing strategy. The server analyzes the user's emotions using an emotion engine, adjusts the existing strategy, and provides it to the user. The server supports the purchasing process by notifying the user of information on the best time to purchase and how to select the best tickets.

[0907] Specific examples

[0908] If a user wants to buy tickets to an upcoming live event but doesn't know the best way to do so, they register the tour information in the system. The server analyzes the event information and formulates the optimal ticket purchasing strategy. The emotion engine analyzes the user's emotions, adjusts the strategy, provides the user with appropriate information, and assists the user in the purchasing process.

[0909] In this way, this system effectively manages and analyzes a wide variety of information, and provides a multifunctional service that supports fan activities while taking into account users' emotions. By using this system, users can improve the efficiency of their fan activities and enjoy a richer experience.

[0910] The processing flow will be explained below.

[0911] 1. Providing new information

[0912] Program processing

[0913] Step 1:

[0914] The server uses the name of a specific artist as a key to collect information from public databases, news sites, social networking services, and official websites on the Internet.

[0915] Step 2:

[0916] The server analyzes the collected information using natural language processing (NLP) techniques to evaluate its importance and relevance.

[0917] Step 3:

[0918] The server filters the information based on the evaluation results and removes unnecessary data.

[0919] Step 4:

[0920] The emotion engine analyzes the user's emotions and adjusts the filtered information to suit the user's current emotions.

[0921] Step 5:

[0922] The server sends the adjusted information to the user's device via push notification or email.

[0923] 2. Support for creating original songs

[0924] Program processing

[0925] Step 1:

[0926] The server acquires music data of the specified artist.

[0927] Step 2:

[0928] The server analyzes the music data and extracts musical features such as rhythm, melody, chords, and tempo.

[0929] Step 3:

[0930] The server generates a music composition tool based on the extracted features and provides it to the user's device.

[0931] Step 4:

[0932] The emotion engine analyzes the user's emotions and adjusts song-making suggestions based on the user's current emotions.

[0933] Step 5:

[0934] The user creates an original piece of music using the provided music creation tool.

[0935] 3. Social media posting support

[0936] Program processing

[0937] Step 1:

[0938] The server retrieves the user's past SNS posting data.

[0939] Step 2:

[0940] The server analyzes past posts' content, tone, and engagement.

[0941] Step 3:

[0942] The emotion engine analyzes the user's current emotions and predicts the content of the text based on past posting data and current emotions.

[0943] Step 4:

[0944] The server uses natural language generation (NLG) technology to generate text for new posts.

[0945] Step 5:

[0946] The server presents the generated text to the user's terminal.

[0947] Step 6:

[0948] The user checks the presented text, edits it, and posts it to a social networking site.

[0949] 4. Performance Analysis

[0950] Program processing

[0951] Step 1:

[0952] The server collects past live footage and audio data.

[0953] Step 2:

[0954] The server analyzes the collected data and extracts information about the songs being performed, audience reactions, and performance trends.

[0955] Step 3:

[0956] The emotion engine analyzes the user's emotions and adjusts the performance analysis results based on the user's current emotions.

[0957] Step 4:

[0958] The server predicts the likely song list and cheering methods for the next live show.

[0959] Step 5:

[0960] The server provides the prediction information to the user's terminal.

[0961] 5. Real-time tracking

[0962] Program processing

[0963] Step 1:

[0964] The server monitors the artist's social media accounts and official website.

[0965] Step 2:

[0966] The server collects new posts and news in real time.

[0967] Step 3:

[0968] The server organizes the collected information and selects information that is important to the user.

[0969] Step 4:

[0970] The emotion engine analyzes the user's emotions and adjusts the information it notifies based on the user's current emotions.

[0971] Step 5:

[0972] The server immediately notifies the user's terminal of the adjusted important information.

[0973] 6. Item Recommendations

[0974] Program processing

[0975] Step 1:

[0976] The server acquires the user's past purchase history.

[0977] Step 2:

[0978] The server analyzes the purchase history and understands the user's preferences.

[0979] Step 3:

[0980] The emotion engine analyzes user emotions and adjusts item recommendations based on preferences and emotions.

[0981] Step 4:

[0982] The server selects items that match the user's preferences from a database of artist-related products available on the market.

[0983] Step 5:

[0984] The server will then suggest the selected items to the user's device via push notification or email.

[0985] 7. Fan Art Generation

[0986] Program processing

[0987] Step 1:

[0988] The server collects image data of artists and analyzes their styles and characteristics.

[0989] Step 2:

[0990] The server uses AI to generate fan art based on the analysis results.

[0991] Step 3:

[0992] The emotion engine analyzes the user's emotions and adjusts the style and content of the generated fan art.

[0993] Step 4:

[0994] The server provides the generated fan art in a downloadable format to the user's device.

[0995] 8. Develop an event strategy

[0996] Program processing

[0997] Step 1:

[0998] The server collects information about artists' tours and live events.

[0999] Step 2:

[1000] Based on the event information collected by the server, the optimal ticket purchasing strategy is developed.

[1001] Step 3:

[1002] The emotion engine analyzes users' emotions and adjusts strategies based on their preferences when attending events.

[1003] Step 4:

[1004] The server provides the strategic information formulated by the server to the user's device to support the purchase process.

[1005] Step 5:

[1006] Based on the information provided by the user, the user purchases tickets at the optimal time and participates in the event.

[1007] Example 2

[1008] 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."

[1009] Many users need a system that efficiently collects and analyzes the latest information about a specific subject and supports fan activities. Additionally, recognizing users' emotions and providing appropriate information and services based on those emotions offers new value not found in conventional systems. However, current methods lack the accuracy of information collection and appropriate information filtering, and it is difficult to provide services that take users' emotions into account.

[1010] 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.

[1011] In this invention, the server includes an information collection means, an analysis means, and a notification means. This makes it possible to efficiently collect and analyze the latest information on a specific subject and provide information filtered based on importance to the user's terminal. Furthermore, by including an emotion analysis means, it is possible to provide appropriate information based on the user's emotions and more effectively support fan activities.

[1012] "Information gathering means" refers to means for gathering information from public databases, news sites, social networking services, and official websites on the Internet.

[1013] "Analysis means" refers to a means for analyzing collected information using natural language processing technology, evaluating its relevance and importance, and filtering it.

[1014] The "notification means" is a means for providing filtered information to a user's device via push notification or email.

[1015] The "purchase support means" is a means for recommending appropriate items and supporting the purchase process to assist users in purchasing artist-related products.

[1016] "Information generation means" means a means for generating new text or content for a user using a generative AI model.

[1017] "Strategy formulation tools" are tools for formulating strategies for taking optimal actions and decisions based on collected and analyzed information.

[1018] The "emotion analysis means" is a means for analyzing the user's emotions and adjusting the information provided and service content based on the analysis.

[1019] The present invention relates to a system that efficiently collects and analyzes the latest information about a specific subject (hereinafter referred to as "artist"), supports fan activities, recognizes user emotions, and provides services based on those emotions. This system includes information collection means, analysis means, notification means, purchase support means, information generation means, strategy formulation means, and emotion analysis means.

[1020] Information gathering methods

[1021] The server uses the artist's name as a key to collect information from public databases on the Internet, news sites, social networking services, and official websites. The server then uses scraping technology and APIs to obtain text data and stores it in a database. This allows data collected from a wide variety of sources to be managed centrally.

[1022] Analysis means

[1023] The server analyzes the collected information using natural language processing (NLP) technology. Specifically, it performs entity recognition, article summarization, sentiment analysis, etc., and scores the information for its relevance and importance. Based on the results of this analysis, it filters out information with high scores and excludes data with low scores, extracting only useful information.

[1024] Notification means

[1025] The server then provides the filtered information to the user's device via push notification or email. The notification method includes a custom notification function based on user settings, providing information at the optimal time based on the user's time and interests. Furthermore, an emotion analysis method is used to analyze the user's current emotions and adjust the notification content to suit the user's state, resulting in more user-friendly notifications.

[1026] Purchasing support methods

[1027] The server analyzes the user's purchasing history and selects items that match the user's preferences from a database of artist-related products. The selected items are then recommended to the user via push notification or email, and sentiment analysis techniques are used to suggest optimal items to increase purchasing motivation.

[1028] Information generation means

[1029] The server uses the generative AI model to generate new text and content for the user. For example, when generating text for a user to post on social media, the server analyzes the user's past posting data and engagement data to create an effective post. It also uses sentiment analysis to adjust the generated text to match the user's current emotions.

[1030] Example prompt sentence:

[1031] Describe how you would handle a system that helps users create original music in the style of a specific artist.

[1032] Strategy formulation tools

[1033] The server formulates strategies for optimal actions and decisions based on the collected and analyzed information. In particular, it formulates optimal ticket purchasing strategies based on artist tour information and live event information, and notifies users of the appropriate timing for purchase and how to select tickets. Emotion analysis takes into account the user's emotional state and adjusts the strategy to provide optimal support to the user.

[1034] Emotion analysis means

[1035] The server uses emotion analysis tools to analyze the user's emotions. This involves analyzing the user's social media posts, email content, and system action logs to understand the user's current emotional state. The analysis results are used in conjunction with other tools to adjust notification content and personalize information provision.

[1036] This system allows users to efficiently collect the latest information about specific artists in real time and receive filtered information based on analysis results. Furthermore, through sentiment analysis, it provides users with the information they need most at the optimal time, enhancing their fan activities.

[1037] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1038] Step 1: Gather information

[1039] The server uses the artist's name as a key to collect information from public databases, news sites, social networking services, and official websites on the Internet. Specifically, it uses scraping technology and APIs to obtain text data and stores it in a database. The input is the artist's name and the URL of the source of information, and the output is reviewable text data.

[1040] Step 2: Information analysis

[1041] The server analyzes the collected information using natural language processing (NLP) technology. Specifically, it performs entity recognition, article summarization, and sentiment analysis, and scores the relevance and importance of the information. The input is the text data collected in Step 1, and the output is the analyzed data with an importance score.

[1042] Step 3: Information filtering

[1043] The server filters the information based on the analysis results. Specifically, it keeps information with high scores and filters out data with low importance. The input is the analysis data generated in step 2, and the output is the filtered, useful information.

[1044] Step 4: Prepare for notification

[1045] The server prepares the filtered information for notification. Specifically, it formats it into a push notification or email format based on the user's settings. The input is the filtered information, and the output is the message data for notification.

[1046] Step 5: Sentiment analysis

[1047] The server analyzes the user's emotions. Specifically, it analyzes the user's social media posts and the system's action logs to understand the user's current emotional state. The input is the user's past data, and the output is data that represents the user's current emotional state.

[1048] Step 6: Send notification

[1049] The server sends the notification message data to the user's device. It reflects the emotion analysis data and adjusts the notification content according to the user's emotion. The input is the message data prepared in step 4 and the emotion analysis data generated in step 5, and the output is the notification sent to the user.

[1050] Step 7: User Verification

[1051] The user checks the notification through their device. Specifically, they receive a push notification or email on their device and view the content. The input is the notification data, and the output is the user's confirmation action.

[1052] Step 8: Gather feedback

[1053] The server collects user feedback, for example, by logging user reactions and actions to notifications. The input is the user action log, and the output is the feedback data.

[1054] In this way, by clearly indicating the specific operations and data flow at each step, it becomes easier to understand the processing of the entire system.

[1055] (Application example 2)

[1056] 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."

[1057] Conventional entertainment systems lack a means for users to obtain real-time updates about their favorite artists in autonomous vehicles, making it difficult to analyze users' emotions and provide appropriate information. Therefore, to improve the user experience, a comprehensive entertainment system that includes real-time information provision and emotion analysis is needed.

[1058] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an information collection means, an analysis means, a notification means, an emotion analysis means, an in-vehicle entertainment system, and a real-time information provision means. This enables a user in an autonomous vehicle to obtain the latest information about their favorite artist in real time and to provide optimal information and services based on the user's emotions.

[1059] "Information gathering means" refers to the means of gathering the latest information about a specific subject from public databases, news sites, social networking services, official websites, etc. on the Internet.

[1060] "Analysis means" refers to a means for evaluating the importance and relevance of collected information and for filtering it.

[1061] "Notification means" refers to a means for notifying the user of the analyzed information, and includes push notifications, emails, voice alerts, etc.

[1062] "Purchase support means" refers to means for supporting the process of users purchasing products and services related to their favorite artists.

[1063] The "generation means" is a means for generating new content or information based on a user's request.

[1064] "Strategy formulation means" is a means for formulating optimal action strategies based on collected and analyzed information.

[1065] "Emotion analysis means" is a means for analyzing a user's emotions and providing appropriate information and services based on the results.

[1066] An "in-vehicle entertainment system" is a system that provides entertainment content such as music, videos, and games for users to enjoy inside an autonomous vehicle.

[1067] The "real-time information providing means" is a means for instantly providing users with the latest information collected in real time.

[1068] This invention constitutes an entertainment system that allows users in self-driving vehicles to obtain the latest information about their favorite artists in real time and provide optimal content and services through emotion analysis.

[1069] The server is equipped with information collection means, analysis means, notification means, sentiment analysis means, an in-vehicle entertainment system, and real-time information provision means, improving the user experience and enabling users to enjoy important information about artists even while on the move.

[1070] Hardware and Software Description

[1071] Hardware:

[1072] Infotainment displays for autonomous vehicles

[1073] Network Module

[1074] Sensor and camera system (for analyzing user emotions)

[1075] software:

[1076] Python script

[1077] News API

[1078] Twitter API

[1079] smtplib (Python email library)

[1080] TextBlob (text analysis library)

[1081] Program processing explanation

[1082] The server uses News API and Twitter API to gather the latest information about the artist from public databases, news sites, social networking services, and official websites on the Internet. The collected information undergoes sentiment analysis using TextBlob, an analytical tool, and is filtered based on its importance and relevance. The filtered information is then sent in real time to the user's email address and the infotainment display in the autonomous vehicle via a notification tool.

[1083] In addition, as a means of emotion analysis, the vehicle uses sensors and camera systems inside the vehicle to analyze the user's facial expressions and voice, and provides information optimized for the user based on the results. As a means of providing real-time information, the vehicle is equipped with a mechanism to immediately notify the user of new data collected in real time.

[1084] Specific examples

[1085] While traveling in an autonomous vehicle, users may not want to miss the latest information on their favorite artists. In such cases, users register the artist's name in the system. The server collects information about the artist from multiple sources on the Internet in real time and performs sentiment analysis and filtering using TextBlob. Important and relevant information is immediately notified to the user and displayed on the vehicle's infotainment display. In addition, sensors and camera systems analyze the user's facial expressions and voice to provide optimal content based on the user's emotions.

[1086] Example prompts for generative AI models:

[1087] "Create an application that provides real-time updates about a favorite artist in an autonomous vehicle's entertainment system. Analyze user sentiment, filter news and social media posts, and notify the user of the appropriate information."

[1088] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1089] Step 1:

[1090] The server receives the name of the artist registered by the user in the system. The input is the artist name registered by the user, and it sends a request to the News API or Twitter API using this as a key. The output is news articles or tweets about the artist.

[1091] Step 2:

[1092] The server analyzes collected news articles and tweets using Python's TextBlob library. The collected text data is used as input, and sentiment analysis and importance / relevance evaluation are performed. The output is filtered positive information.

[1093] Step 3:

[1094] The server sends the filtered information to the user's email address or the infotainment display in the autonomous vehicle. The filtered information and the user's notification settings are input, and based on this, the information is sent in the form of a push notification or email. The output is the user receiving the latest information in real time.

[1095] Step 4:

[1096] The server uses the in-car sensors and camera system to analyze the user's facial expressions and voice to understand their emotional state. The input is the user's facial expression data and voice data, and emotion analysis is performed based on this. The output is the user's emotional state.

[1097] Step 5:

[1098] The server selects the most appropriate content based on the user's emotional state and sends the notification again. The input is the user's emotional state and filtered information, and based on this, the server selects the most appropriate content and notification content. The output is information optimized for the user's emotions.

[1099] Step 6:

[1100] The user views the information notified via the infotainment display in the autonomous vehicle or on their smartphone. The input is the notified information, and by checking it, the user can grasp the latest information about the artist in real time. The output is an update of the user's knowledge about the artist.

[1101] 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.

[1102] 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.

[1103] 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.

[1104] [Third embodiment]

[1105] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1106] 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.

[1107] 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).

[1108] 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.

[1109] 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.

[1110] 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).

[1111] 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.

[1112] 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.

[1113] 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.

[1114] 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.

[1115] 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.

[1116] 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."

[1117] The present invention relates to a system that efficiently collects and analyzes the latest information about a specific subject (hereinafter referred to as "artist") and supports fan activities. This system includes information collection means, analysis means, notification means, purchase support means, generation means, and strategy formulation means.

[1118] 1. Providing new information

[1119] Program processing

[1120] The server periodically collects new information from multiple sources, including public databases on the Internet, news sites, social networking services, and official websites, using the artist's name as a key. The information collected by the server is analyzed using natural language processing technology and filtered based on relevance and importance. The filtered information is then delivered to the user's device via push notification or email.

[1121] Specific examples

[1122] A user wants to keep track of the latest information about a particular artist, so they input the artist's name into the system. The server then collects information about the artist from multiple sources on the Internet, filters out important news, articles, and social media posts, and notifies the user's device.

[1123] 2. Support for creating original songs

[1124] Program processing

[1125] The server acquires the artist's song data and analyzes musical elements such as rhythm, melody, chords, tempo, etc. Based on the analysis results, it provides an original song creation tool that users can use to create original songs.

[1126] Specific examples

[1127] If a user wants to create a song in the style of a certain artist, they specify the artist's musical style to the system. The server analyzes the artist's song data and extracts musical characteristics. The user can then use the provided templates and tools to create a song in the artist's style.

[1128] 3. Social media posting support

[1129] Program processing

[1130] The server retrieves the user's past social media posts and analyzes their content and engagement. The server then uses natural language generation technology to generate text for new posts and presents it to the user. The user can then review the generated text, edit it, and post it.

[1131] Specific examples

[1132] If a user is thinking about posting their impressions of a concert on social media but is unsure of how to write it, they can link their past social media posts to the system. The server analyzes past trends, generates text for a new post, and presents it to the user. The user can use that text as a reference when posting.

[1133] 4. Performance Analysis

[1134] Program processing

[1135] The server collects past live performance footage and audio, analyzes performance trends, song lists, and audience reactions, and based on the analysis results, suggests songs that are likely to be played at the next live performance and suggests effective ways to cheer on the band.

[1136] Specific examples

[1137] If a user wants to predict what songs will be played at an upcoming live concert, they register the concert information in the system. The server analyzes past performance data and shares with the user a list of songs that are likely to be played at the next live concert.

[1138] 5. Real-time tracking

[1139] Program processing

[1140] The server monitors artists' social media accounts and official websites, collecting new posts and news in real time. The collected information is organized and instantly sent to the user's device.

[1141] Specific examples

[1142] If a user wants to keep up with the latest news about their favorite artist, they can register the artist's social media account in the system. The server monitors the account in real time, and users are immediately notified of any new posts or news.

[1143] 6. Item Recommendations

[1144] Program processing

[1145] The server analyzes the user's purchasing history and selects items that match the user's preferences from a database of artist-related products. The selected items are then suggested to the user via push notification or email.

[1146] Specific examples

[1147] When a user wants to purchase new merchandise from an artist, they can connect their past purchase history to the system. The server analyzes their preferences, recommends related items, and supports the user in making the purchase.

[1148] 7. Fan Art Generation

[1149] Program processing

[1150] The server collects image data of artists, analyzes their style and characteristics, and generates fan art based on the analysis results, which is then made available for users to download.

[1151] Specific examples

[1152] When a user wants to create fan art of an artist, they provide an image of the artist to the system, and the server analyzes the style and provides the user with AI-generated fan art.

[1153] 8. Develop an event strategy

[1154] Program processing

[1155] The server collects information about artists' tours and live events, formulates the optimal ticket purchasing strategy, and notifies users of the timing of purchases and how to select the best tickets.

[1156] Specific examples

[1157] If a user wants to buy tickets to an upcoming live event but doesn't know the best way to do so, they register the tour information in the system. The server analyzes the event information and suggests the best ticket purchasing strategy to the user.

[1158] In this way, this system effectively manages and analyzes a wide variety of information and provides a multifunctional service to support fan activities. By using this system, users can improve the efficiency of their fan activities and have a richer experience.

[1159] The processing flow will be explained below.

[1160] 1. Providing new information

[1161] Program processing

[1162] Step 1:

[1163] The server uses the name of a specific artist as a key to collect information from public databases, news sites, social networking services, and official websites on the Internet.

[1164] Step 2:

[1165] The server analyzes the collected information using natural language processing (NLP) techniques to evaluate its importance and relevance.

[1166] Step 3:

[1167] The server filters the information based on the evaluation results and removes unnecessary data.

[1168] Step 4:

[1169] The server sends the filtered information to the user's device via push notification or email.

[1170] 2. Support for creating original songs

[1171] Program processing

[1172] Step 1:

[1173] The server acquires music data of the specified artist.

[1174] Step 2:

[1175] The server analyzes the music data and extracts musical features such as rhythm, melody, chords, and tempo.

[1176] Step 3:

[1177] The server generates a music composition tool based on the extracted features and provides it to the user's terminal.

[1178] Step 4:

[1179] The user creates an original piece of music using the provided music creation tool.

[1180] 3. Social media posting support

[1181] Program processing

[1182] Step 1:

[1183] The server retrieves the user's past SNS posting data.

[1184] Step 2:

[1185] The server analyzes past posts' content, tone, and engagement.

[1186] Step 3:

[1187] The server uses natural language generation (NLG) technology to generate text for new posts.

[1188] Step 4:

[1189] The server presents the generated text to the user's terminal.

[1190] Step 5:

[1191] The user checks the presented text, edits it, and posts it to a social networking site.

[1192] 4. Performance Analysis

[1193] Program processing

[1194] Step 1:

[1195] The server collects past live footage and audio data.

[1196] Step 2:

[1197] The server analyzes the collected data and extracts information about the songs being performed, audience reactions, and performance trends.

[1198] Step 3:

[1199] Based on the analysis results, the server predicts the list of songs that are likely to be played at the next live concert and how to support the band.

[1200] Step 4:

[1201] The server provides the prediction information to the user's terminal.

[1202] 5. Real-time tracking

[1203] Program processing

[1204] Step 1:

[1205] The server monitors the artist's social media accounts and official website.

[1206] Step 2:

[1207] The server collects new posts and news in real time.

[1208] Step 3:

[1209] The server organizes the collected information and selects information that is important to the user.

[1210] Step 4:

[1211] The server immediately notifies the user's device of important information.

[1212] 6. Item Recommendations

[1213] Program processing

[1214] Step 1:

[1215] The server acquires the user's past purchase history.

[1216] Step 2:

[1217] The server analyzes the purchase history and understands the user's preferences.

[1218] Step 3:

[1219] The server selects items that match the user's preferences from a database of artist-related products available on the market.

[1220] Step 4:

[1221] The server will then suggest the selected items to the user's device via push notification or email.

[1222] 7. Fan Art Generation

[1223] Program processing

[1224] Step 1:

[1225] The server collects image data of artists and analyzes their styles and characteristics.

[1226] Step 2:

[1227] The server uses AI to generate fan art based on the analysis results.

[1228] Step 3:

[1229] The server provides the generated fan art in a downloadable format to the user's device.

[1230] 8. Develop an event strategy

[1231] Program processing

[1232] Step 1:

[1233] The server collects information about artists' tours and live events.

[1234] Step 2:

[1235] Based on the event information collected by the server, the optimal ticket purchasing strategy is developed.

[1236] Step 3:

[1237] The server provides the strategic information formulated by the server to the user's device to support the purchase process.

[1238] Step 4:

[1239] Based on the information provided by the user, the user purchases tickets at the optimal time and participates in the event.

[1240] Example 1

[1241] 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."

[1242] Conventional fan activity support systems are inefficient in collecting and analyzing the latest information on specific subjects, making it difficult for users to efficiently obtain information and improve the quality of their activities. Furthermore, they lack support for music creation and posting to social networking services, performance analysis, and real-time information tracking, making it difficult for users to centrally manage a wide range of activities. Analytical methods for properly evaluating the relevance and importance of information are also inadequate, creating a need for a method that provides only useful information to users.

[1243] 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.

[1244] In this invention, the server includes an information collection means, an analysis means, a notification means, a purchase support means, a generation means, a strategy formulation means, a music creation support means, a social network service posting support means, a performance analysis means, a real-time tracking means, an item recommendation means, and an artwork creation means, thereby enabling centralized and effective support for a wide range of fan activities, such as efficient collection and analysis of the latest information on a specific subject, timely notification to users, music creation support, social network service posting support, performance analysis, real-time information tracking, item recommendation, and fan art generation.

[1245] "Information gathering means" refers to the means of gathering the latest information on a specific subject from public databases, news sites, social networking services, and official websites on the Internet.

[1246] "Analysis means" refers to means for evaluating importance and relevance based on collected information and song data, past posting data from social networking services, and live performance data, and for filtering and analyzing the data.

[1247] "Notification means" refers to a means for sending filtered information to the user's device via push notification or email.

[1248] The "purchase support means" is a means for analyzing the user's purchase history and selecting and suggesting items that match the user's preferences from a database of artist-related products.

[1249] The "generation means" is a means for automatically generating new content and suggestions based on collected and analyzed data and providing them to users.

[1250] The "strategy formulation means" is a means for formulating an optimal ticket purchasing strategy based on artist tour information and live event information, and notifying the user of the strategy.

[1251] "Music composition support means" is a means for analyzing an artist's music data and providing a tool that enables a user to create original music based on the analysis results.

[1252] The "social network service posting support means" is a means for analyzing a user's past SNS posting data, automatically generating text for a new post, and providing it to the user.

[1253] "Performance analysis means" refers to a method of collecting past live performance footage and audio recordings, analyzing that data, and evaluating performance trends, song lists, and audience reactions.

[1254] "Real-time tracking means" refers to a means of monitoring an artist's social media accounts and official websites, collecting new posts and news in real time, and notifying users.

[1255] The "item recommendation means" is a means for analyzing the purchase history of a user and recommending highly relevant artist-related merchandise items.

[1256] The "artwork generation means" is a means for automatically generating fan art based on the artist's style and characteristics by analyzing the artist's image data and providing it to the user.

[1257] The present invention relates to a system for efficiently collecting and analyzing the latest information on a specific subject and supporting fan activities. The system includes an information collection means, an analysis means, a notification means, a purchasing support means, a creation means, a strategy formulation means, a music creation support means, a social network service posting support means, a performance analysis means, a real-time tracking means, an item recommendation means, and an art creation means.

[1258] Information gathering methods

[1259] The server uses information gathering tools to collect the latest information about the artist from public databases, news sites, social networking services, and official websites on the Internet, specifically using web scraping tools (e.g., Beautiful Soup, Scrapy) and APIs.

[1260] Example: A user wants to track the latest information about a particular artist and enters the artist's name into the system. The server collects information about the artist from multiple sources on the Internet, filters out important news, articles, and social media posts, and notifies the user's device.

[1261] Example prompt: "Please gather the latest information on the artist's name."

[1262] Analysis means

[1263] The server uses analytical tools to analyze the collected information, song data, past SNS posting data, and live performance data. Specifically, it uses text analysis tools (e.g., SpaCy, NLTK), music analysis tools (e.g., LibROSA, Essentia), and video analysis tools (e.g., OpenCV, Dlib).

[1264] Examples: Analyzing data collected by a server to evaluate importance and relevance and filter out noise on the Internet. Analyzing the content of news articles to extract important keywords and rank information based on importance and relevance.

[1265] Example prompt: "Analyze a news article about the artist's name."

[1266] Notification means

[1267] The server sends the filtered information to the user's device via push notification or email, using notification services such as Firebase or SendGrid.

[1268] Example: The server immediately sends filtered information to the user, allowing the user to grasp important information without missing it.

[1269] Example prompt: "Push important information to users."

[1270] Purchasing support methods

[1271] The server analyzes the user's purchase history and selects and suggests items that match the user's preferences from a database of artist-related products, using a purchase history analysis tool (e.g., Google Analytics, Tableau).

[1272] Example: If a user wants to buy new merchandise from an artist, the system analyzes their past purchase history and recommends related items.

[1273] Example prompt: "Recommend artist-related products based on the user's purchasing history."

[1274] generation means

[1275] The server uses a generating means to automatically generate new content and suggestions based on the collected and analyzed data and provide them to the user.

[1276] Example: The server analyzes the collected data and generates and provides useful articles and posts to users.

[1277] Example prompt: "Generate the latest news article about an artist."

[1278] Strategy formulation tools

[1279] This is a method for the server to create the optimal ticket purchasing strategy based on artist tour information and live event information and notify users. Event information acquisition tools (e.g., Eventbrite, Ticketmaster API) are used to collect this information.

[1280] Example: If a user wants to purchase tickets to an upcoming live event but isn't sure how best to do so, the server analyzes the event information and suggests the best ticket purchasing strategy to the user.

[1281] Example prompt: "Suggest a ticket purchasing strategy for the next live event."

[1282] Music creation support tools

[1283] The server retrieves the artist's music data and analyzes the rhythm, melody, chords, and tempo using music analysis software (e.g., Sonic Visualiser, MADM), and provides original music creation tools (e.g., Magix Music Maker, Ableton Live) based on the analysis results.

[1284] Example: Providing an interface that allows users to create original music based on the musical characteristics of artists analyzed by the server.

[1285] Example prompt: "Give me a tool to create music in the style of the artist."

[1286] Social networking service posting support tool

[1287] The server retrieves the user's past social media posts, analyzes the content and engagement of the posts, and uses social media data analysis tools (e.g., Hootsuite, Sprout Social) to generate text for new posts using natural language generation technology (e.g., GPT-3, BERT).

[1288] Example: If a user wants to post their impressions of a concert on social media but isn't sure how to write it, the server analyzes past trends and generates and provides new text for the post.

[1289] Example prompt: "Generate text to post on social media about your impressions of the concert."

[1290] Performance Analysis Tools

[1291] The server collects past live video and audio recordings and analyzes performance trends, track lists, and audience reactions using video analysis tools (e.g., OpenCV, FFmpeg) and audio analysis tools (e.g., LibROSA, Praat).

[1292] Example: A server provides a user with a list of songs that are likely to be played at an upcoming live show.

[1293] Example prompt: "Predict the song most likely to be played at the next live show."

[1294] Real-time tracking methods

[1295] The server monitors the artist's social media accounts and official website, collecting new posts and news in real time using web scraping tools (e.g., Beautiful Soup, Scrapy) and APIs.

[1296] Example: The server monitors in real time and notifies users immediately when there is a new post or news.

[1297] Example prompt: "Please notify me of real-time updates on artist names."

[1298] Item recommendation method

[1299] The server analyzes the user's purchase history and selects items that match the user's preferences from a database of artist-related products. The analysis is performed using a purchase history analysis tool (e.g., Google Analytics, Tableau).

[1300] Example: The server analyzes the user's preferences and recommends related items to assist with purchasing.

[1301] Example prompt: "Recommend artist-related products based on the user's purchasing history."

[1302] Art creation means

[1303] The server collects image data of artists and analyzes their style and characteristics using image analysis tools (e.g., TensorFlow, Keras). Based on the analysis results, fan art is generated and made available for users to download.

[1304] Example: If a user wants to create fan art of an artist, the server analyzes the style and serves the generated fan art to the user.

[1305] Example prompt: "Generate fan art of artist name."

[1306] This allows the system to effectively manage and analyze a wide range of information and provide multifunctional services to support fan activities, allowing users to improve the efficiency of their fan activities and enjoy a richer experience.

[1307] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1308] Providing new information

[1309] Step 1:

[1310] The server receives the artist name as input from the user, specifically, the server retrieves the artist name through a web interface.

[1311] Step 2:

[1312] The server collects data from public databases, news sites, social networking services, and official websites on the Internet using web scraping tools (e.g., Beautiful Soup, Scrapy) or APIs. The input is artist names, and the output is the collected, unparsed data.

[1313] Step 3:

[1314] The server analyzes the collected data using natural language processing techniques (e.g., SpaCy, NLTK) to evaluate its relevance and importance. The input is the collected data, and the output is the analyzed information.

[1315] Step 4:

[1316] The server filters the results of the analysis and extracts only the information that is deemed important to the user. The input is the analyzed information, and the output is the filtered information.

[1317] Step 5:

[1318] The server sends the filtered information to the user's device via push notification or email. It uses a notification service such as Firebase or SendGrid. The input is the filtered information, and the output is the notification sent to the user.

[1319] Original song creation support

[1320] Step 1:

[1321] The user inputs the artist's musical style into the system, and the server retrieves the artist's name through a web interface.

[1322] Step 2:

[1323] The server uses the music streaming service API (e.g., Spotify API, YouTube Data API) to obtain the artist's song data. The input is the artist name, and the output is the obtained song data.

[1324] Step 3:

[1325] The server uses a music analysis tool (e.g., LibROSA, Essentia) to analyze the rhythm, melody, chords, tempo, etc. of the song. The input is the song data, and the output is the analysis results.

[1326] Step 4:

[1327] The server provides users with original music creation tools (e.g., Magix Music Maker, Ableton Live). The input is the analysis results, and the output is the creation tools provided to users.

[1328] Step 5:

[1329] Users create original music using the provided tools. The input is the creation tool and the user's actions, and the output is a new original piece of music.

[1330] SNS posting support

[1331] Step 1:

[1332] The server connects to SNS APIs (e.g., Twitter API, Facebook Graph API) to retrieve users' past SNS posts. The input is user account information, and the output is the retrieved past post data.

[1333] Step 2:

[1334] The server analyzes the post content and engagement using a social media data analysis tool (e.g., Hootsuite, Sprout Social Analytics). The input is past post data, and the output is the analysis results.

[1335] Step 3:

[1336] The server generates text for new posts using natural language generation techniques (e.g., GPT-3, BERT). The input is the analysis result, and the output is the generated text.

[1337] Step 4:

[1338] The user checks and edits the generated text and posts it to the social networking site. The input is the generated text and the user's edits, and the output is the posted social networking site content.

[1339] Performance Analysis

[1340] Step 1:

[1341] The server uses the YouTube Data API and Spotify API to collect past live video and audio data. The input is live event information, and the output is the captured video and audio data.

[1342] Step 2:

[1343] The server analyzes the performance data using video analysis tools (e.g., OpenCV, Dlib) and audio analysis tools (e.g., LibROSA, Praat). The input is video and audio data, and the output is the analysis results.

[1344] Step 3:

[1345] The server uses machine learning models (e.g., LSTM, Random Forest) to predict the songs that are likely to be played at the next live show based on the analysis results. The input is the analysis results, and the output is the predicted song list.

[1346] Step 4:

[1347] The server proposes effective cheering methods to the user. The input is a predicted song list, and the output is a suggested cheering method.

[1348] Real-time tracking

[1349] Step 1:

[1350] The server sets up a web scraping tool (e.g., Beautiful Soup, Scrapy) or API to monitor artists' social media accounts and official websites. The input is the monitored account information, and the output is the collected real-time information.

[1351] Step 2:

[1352] The server analyzes and organizes the collected information in real time. The input is real-time information, and the output is organized information.

[1353] Step 3:

[1354] The server immediately sends a notification to the user's device. It uses a notification service such as Firebase or SendGrid. The input is organized information, and the output is the notification sent to the user.

[1355] Item Recommendations

[1356] Step 1:

[1357] The server obtains the user's purchase history. Specifically, it retrieves information from a database where purchase history is stored. The input is the user's account information, and the output is the obtained purchase history data.

[1358] Step 2:

[1359] The server analyzes the purchase history using a purchase history analysis tool (e.g., Google Analytics, Tableau). The input is the purchase history data, and the output is the analysis results.

[1360] Step 3:

[1361] The server selects items that match the user's preferences from a database of artist-related products. The input is the analysis results, and the output is a list of recommended items.

[1362] Step 4:

[1363] The server proposes a recommended item list to the user. The input is the item list, and the output is the item recommendations notified to the user.

[1364] Artwork Creation

[1365] Step 1:

[1366] The server collects image data of artists. Specifically, it retrieves images from the Internet using a web crawler or API. The input is the artist's name, and the output is the collected image data.

[1367] Step 2:

[1368] The server analyzes the image data using image analysis tools (e.g., TensorFlow, Keras). The analysis includes extracting styles and features. The input is the image data, and the output is the analysis results.

[1369] Step 3:

[1370] The server uses a generative AI model to generate fan art based on the analysis results. The input is the analysis results, and the output is the generated fan art.

[1371] Step 4:

[1372] The server prepares the generated fan art as a download resource for users to use. The input is the generated fan art, and the output is a download link provided to the user.

[1373] (Application example 1)

[1374] 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."

[1375] The goal of this project is to solve the problem of fans finding it difficult to efficiently gather the latest information on specific topics and obtain it in real time. In particular, there is a lack of means to gather news and social media information in a timely manner and notify users every five minutes.

[1376] 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.

[1377] In this invention, the server includes an information collection means, an analysis means, a notification means, a purchase support means, a generation means, a strategy formulation means, a means for collecting news and SNS information related to a specific target in real time, and a means for notifying the collected information every five minutes, thereby enabling fans to receive the latest information related to the specific target in a timely manner.

[1378] "Information gathering means" refers to means of gathering information about a specific subject from public databases, news sites, social networking services, official websites, etc. on the Internet.

[1379] The "analysis means" is a means for evaluating the importance and relevance of collected information and filtering it.

[1380] "Notification means" refers to a means of providing filtered information to a user's device via push notification or email.

[1381] "Purchase support means" refers to means for supporting a user's purchase.

[1382] "Generation means" refers to the means for creating new data or content.

[1383] "Strategy formulation tools" are means for creating optimal action plans based on collected and analyzed information.

[1384] "Means for collecting news and social media information about a specific subject in real time" refers to means for instantly collecting the latest news articles and posts on social networking services about a specific subject.

[1385] "Means for notifying collected information every 5 minutes" refers to means for notifying the user of the latest collected information every 5 minutes.

[1386] This invention relates to a system that efficiently collects, analyzes, and provides users with the latest information on a specific subject in real time. This system includes information collection means, analysis means, notification means, purchase support means, generation means, strategy formulation means, means for collecting news and SNS information on the specific subject in real time, and means for notifying users of the collected information every five minutes.

[1387] Program processing

[1388] The server executes a program in the following procedure to collect the latest information on a specific subject. First, it uses an information collection means to collect information on the specific subject from public databases on the Internet, news sites, social networking services, official websites, etc. Next, it uses an analysis means to analyze the collected information and filter it according to importance and relevance. Then, it uses a notification means to send the filtered information to the user's device every five minutes. This allows the user to receive the latest information on the specific subject in real time.

[1389] Hardware and software used

[1390] The hardware used includes a server, the user's smartphone or head-mounted display, and the software used is a Python program, the Twitter API, BeautifulSoup (a scraping library), APScheduler (a scheduling library), and SMTP (an email sending protocol).

[1391] Specific examples

[1392] As a concrete example, consider the case where a user wants to track the latest information about an artist named "Your Favorite Artist." In this system, all a user needs to do is enter the artist's name, and the server will monitor news sites and social media in real time, collecting data whenever new information is posted. The collected data is filtered using an analysis method to select important information. The filtered information is then sent to the user's smartphone every five minutes using a notification method, ensuring that the user always has the latest information at their fingertips.

[1393] Prompt Sentence Examples

[1394] An example of a prompt to input to a generative AI model would be:

[1395] "Please create a system that notifies me of the latest updates about my favorite artist. This system will use the Twitter API to collect the artist's latest tweets, scrape Google News to get related news, and send me an email with the collected information every 5 minutes."

[1396] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1397] Step 1:

[1398] The server uses information gathering tools to collect the latest information about a specific subject from public databases, news sites, social networking services, and official websites on the Internet. The input is the name of the target (e.g., artist name), and the output is the collected raw data. Specifically, the server performs web scraping or API requests to retrieve articles and posts related to the target.

[1399] Step 2:

[1400] The server analyzes the collected raw data using analytical methods. The input is the collected raw data, and the output is filtered information. Specifically, the server uses natural language processing technology to analyze the text data and filter it according to importance and relevance. For example, it scores news article headlines and social media posts and selects only those with high scores.

[1401] Step 3:

[1402] The server uses a notification method to send the filtered information to the user's device. The input is the filtered information, and the output is a notification displayed on the user's device. Specifically, the server uses the SMTP protocol to send emails or an API that implements push notifications to the user's smartphone or head-mounted display.

[1403] Step 4:

[1404] The server constantly monitors the latest information using a method for collecting news and social media information about a specific subject in real time. The input is the name of the specific subject (e.g., artist name), and the output is the collected real-time data. Specifically, the server collects information at set intervals (e.g., every 5 minutes) and continuously performs API requests and web scraping.

[1405] Step 5:

[1406] The server periodically sends the latest information to the user's device using a method that notifies the collected information every 5 minutes. The input is the collected real-time data, and the output is a notification sent every 5 minutes. Specifically, the server uses APScheduler to schedule and notify the user of filtered information at regular intervals.

[1407] Step 6:

[1408] By receiving notifications, users can obtain the latest information about specific subjects in real time. The input is the notification sent from the server, and the output is the latest information received by the user. Specifically, notifications are displayed on the user's smartphone or head-mounted display, allowing the user to instantly check the latest information.

[1409] 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.

[1410] The present invention relates to a system that efficiently collects and analyzes the latest information about a specific subject (hereinafter referred to as "artist"), supports fan activities, recognizes user emotions, and provides services based on those emotions. This system includes information collection means, analysis means, notification means, purchase support means, generation means, strategy formulation means, and an emotion engine.

[1411] 1. Providing new information

[1412] Program processing

[1413] The server uses the artist's name as a key to collect information from public databases on the Internet, news sites, social networking services, and official websites. The information collected by the server is analyzed using natural language processing technology and filtered based on relevance and importance. The filtered information is then delivered to the user's device via push notification or email. Furthermore, an emotion engine analyzes the user's emotions and delivers the filtered results in a format appropriate to the emotion.

[1414] Specific examples

[1415] A user wants to track the latest information about a particular artist and enters the artist's name into the system. The server collects information about the artist from multiple sources on the Internet and filters out important news, articles, and social media posts. The emotion engine analyzes the user's emotions, determines which information is most relevant, and notifies the user.

[1416] 2. Support for creating original songs

[1417] Program processing

[1418] The server acquires the artist's song data and analyzes musical elements such as rhythm, melody, chords, and tempo. Based on the analysis results, it provides an original song creation tool that users can use to create original songs. The emotion engine analyzes the user's emotions and makes song creation suggestions.

[1419] Specific examples

[1420] If a user wants to create a song in the style of a certain artist, they specify the artist's musical style to the system. The server analyzes the artist's song data and extracts musical characteristics. The emotion engine analyzes the user's emotions when creating the song and suggests appropriate templates and tools to help create a song that is more suited to the user.

[1421] 3. Social media posting support

[1422] Program processing

[1423] The server retrieves the user's past social media posts and analyzes their content and engagement. The server uses natural language generation technology to generate text for new posts and presents it to the user. The emotion engine analyzes the user's current emotions and adjusts the post text to match those emotions. The user can then review the generated text, edit it, and post it.

[1424] Specific examples

[1425] If a user is thinking about posting their impressions of a concert on social media but is unsure how to write it, they can link their past social media posts to the system. The server analyzes past trends and generates text for a new post, and an emotion engine analyzes the user's current emotions and adjusts the text accordingly. The user can use that text as a reference when posting.

[1426] 4. Performance Analysis

[1427] Program processing

[1428] The server collects past live footage and audio, and analyzes performance trends, track lists, and audience reactions. Based on the analysis results, it suggests songs that are likely to be played at the next live show and effective cheering methods to users. The emotion engine analyzes the user's emotions and adjusts cheering methods and performance analysis results based on their emotions.

[1429] Specific examples

[1430] If a user wants to predict what songs will be played at the next live concert, they register the live concert information in the system. The server analyzes past performance data and creates a list of songs that are likely to be played at the next live concert. The emotion engine analyzes the user's emotions and suggests appropriate ways to cheer.

[1431] 5. Real-time tracking

[1432] Program processing

[1433] The server monitors artists' social media accounts and official websites, collecting new posts and news in real time. The collected information is organized and instantly sent to the user's device. The emotion engine analyzes the user's emotions, selecting important information and adjusting the content of notifications.

[1434] Specific examples

[1435] If a user wants to keep up with the latest news about their favorite artist, they can register the artist's social media account in the system. The server monitors the information in real time and notifies the user immediately when new posts or news are posted. The emotion engine analyzes the user's emotions, determines which information is most useful to the user, and adjusts the content of the notifications accordingly.

[1436] 6. Item Recommendations

[1437] Program processing

[1438] The server analyzes the user's purchasing history and selects items that match the user's preferences from a database of artist-related products. The selected items are then recommended to the user via push notification or email. The emotion engine analyzes the user's emotions and recommends the optimal items to increase their desire to purchase.

[1439] Specific examples

[1440] When a user wants to purchase new merchandise from an artist, they connect their past purchase history to the system. The server analyzes their preferences and recommends related items, and the emotion engine analyzes the user's emotions and suggests items that will increase their desire to purchase.

[1441] 7. Fan Art Generation

[1442] Program processing

[1443] The server collects image data of artists and analyzes their style and characteristics. Based on the analysis results, AI is used to generate fan art, which is then provided to the user in a downloadable format. An emotion engine analyzes the user's emotions and adjusts the style and content of the generated fan art.

[1444] Specific examples

[1445] When a user wants to create fan art of an artist, they provide an image of the artist to the system. The server analyzes the style and provides AI-generated fan art. The emotion engine analyzes the user's emotions and adjusts the style and content of the fan art to provide fan art that is more suited to the user.

[1446] 8. Develop an event strategy

[1447] Program processing

[1448] The server collects artist tour information and live event information. Based on the collected information, it formulates the optimal ticket purchasing strategy. The server analyzes the user's emotions using an emotion engine, adjusts the existing strategy, and provides it to the user. The server supports the purchasing process by notifying the user of information on the best time to purchase and how to select the best tickets.

[1449] Specific examples

[1450] If a user wants to buy tickets to an upcoming live event but doesn't know the best way to do so, they register the tour information in the system. The server analyzes the event information and formulates the optimal ticket purchasing strategy. The emotion engine analyzes the user's emotions, adjusts the strategy, provides the user with appropriate information, and assists the user in the purchasing process.

[1451] In this way, this system effectively manages and analyzes a wide variety of information, and provides a multifunctional service that supports fan activities while taking into account users' emotions. By using this system, users can improve the efficiency of their fan activities and enjoy a richer experience.

[1452] The processing flow will be explained below.

[1453] 1. Providing new information

[1454] Program processing

[1455] Step 1:

[1456] The server uses the name of a specific artist as a key to collect information from public databases, news sites, social networking services, and official websites on the Internet.

[1457] Step 2:

[1458] The server analyzes the collected information using natural language processing (NLP) techniques to evaluate its importance and relevance.

[1459] Step 3:

[1460] The server filters the information based on the evaluation results and removes unnecessary data.

[1461] Step 4:

[1462] The emotion engine analyzes the user's emotions and adjusts the filtered information to suit the user's current emotions.

[1463] Step 5:

[1464] The server sends the adjusted information to the user's device via push notification or email.

[1465] 2. Support for creating original songs

[1466] Program processing

[1467] Step 1:

[1468] The server acquires music data of the specified artist.

[1469] Step 2:

[1470] The server analyzes the music data and extracts musical features such as rhythm, melody, chords, and tempo.

[1471] Step 3:

[1472] The server generates a music composition tool based on the extracted features and provides it to the user's device.

[1473] Step 4:

[1474] The emotion engine analyzes the user's emotions and adjusts song-making suggestions based on the user's current emotions.

[1475] Step 5:

[1476] The user creates an original piece of music using the provided music creation tool.

[1477] 3. Social media posting support

[1478] Program processing

[1479] Step 1:

[1480] The server retrieves the user's past SNS posting data.

[1481] Step 2:

[1482] The server analyzes past posts' content, tone, and engagement.

[1483] Step 3:

[1484] The emotion engine analyzes the user's current emotions and predicts the content of the text based on past posting data and current emotions.

[1485] Step 4:

[1486] The server uses natural language generation (NLG) technology to generate text for new posts.

[1487] Step 5:

[1488] The server presents the generated text to the user's terminal.

[1489] Step 6:

[1490] The user checks the presented text, edits it, and posts it to a social networking site.

[1491] 4. Performance Analysis

[1492] Program processing

[1493] Step 1:

[1494] The server collects past live footage and audio data.

[1495] Step 2:

[1496] The server analyzes the collected data and extracts information about the songs being performed, audience reactions, and performance trends.

[1497] Step 3:

[1498] The emotion engine analyzes the user's emotions and adjusts the performance analysis results based on the user's current emotions.

[1499] Step 4:

[1500] The server predicts the likely song list and cheering methods for the next live show.

[1501] Step 5:

[1502] The server provides the prediction information to the user's terminal.

[1503] 5. Real-time tracking

[1504] Program processing

[1505] Step 1:

[1506] The server monitors the artist's social media accounts and official website.

[1507] Step 2:

[1508] The server collects new posts and news in real time.

[1509] Step 3:

[1510] The server organizes the collected information and selects information that is important to the user.

[1511] Step 4:

[1512] The emotion engine analyzes the user's emotions and adjusts the information it notifies based on the user's current emotions.

[1513] Step 5:

[1514] The server immediately notifies the user's terminal of the adjusted important information.

[1515] 6. Item Recommendations

[1516] Program processing

[1517] Step 1:

[1518] The server acquires the user's past purchase history.

[1519] Step 2:

[1520] The server analyzes the purchase history and understands the user's preferences.

[1521] Step 3:

[1522] The emotion engine analyzes user emotions and adjusts item recommendations based on preferences and emotions.

[1523] Step 4:

[1524] The server selects items that match the user's preferences from a database of artist-related products available on the market.

[1525] Step 5:

[1526] The server will then suggest the selected items to the user's device via push notification or email.

[1527] 7. Fan Art Generation

[1528] Program processing

[1529] Step 1:

[1530] The server collects image data of artists and analyzes their styles and characteristics.

[1531] Step 2:

[1532] The server uses AI to generate fan art based on the analysis results.

[1533] Step 3:

[1534] The emotion engine analyzes the user's emotions and adjusts the style and content of the generated fan art.

[1535] Step 4:

[1536] The server provides the generated fan art in a downloadable format to the user's device.

[1537] 8. Develop an event strategy

[1538] Program processing

[1539] Step 1:

[1540] The server collects information about artists' tours and live events.

[1541] Step 2:

[1542] Based on the event information collected by the server, the optimal ticket purchasing strategy is developed.

[1543] Step 3:

[1544] The emotion engine analyzes users' emotions and adjusts strategies based on their preferences when attending events.

[1545] Step 4:

[1546] The server provides the strategic information formulated by the server to the user's device to support the purchase process.

[1547] Step 5:

[1548] Based on the information provided by the user, the user purchases tickets at the optimal time and participates in the event.

[1549] Example 2

[1550] 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."

[1551] Many users need a system that efficiently collects and analyzes the latest information about a specific subject and supports fan activities. Additionally, recognizing users' emotions and providing appropriate information and services based on those emotions offers new value not found in conventional systems. However, current methods lack the accuracy of information collection and appropriate information filtering, and it is difficult to provide services that take users' emotions into account.

[1552] 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.

[1553] In this invention, the server includes an information collection means, an analysis means, and a notification means. This makes it possible to efficiently collect and analyze the latest information on a specific subject and provide information filtered based on importance to the user's terminal. Furthermore, by including an emotion analysis means, it is possible to provide appropriate information based on the user's emotions and more effectively support fan activities.

[1554] "Information gathering means" refers to means for gathering information from public databases, news sites, social networking services, and official websites on the Internet.

[1555] "Analysis means" refers to a means for analyzing collected information using natural language processing technology, evaluating its relevance and importance, and filtering it.

[1556] The "notification means" is a means for providing filtered information to a user's device via push notification or email.

[1557] The "purchase support means" is a means for recommending appropriate items and supporting the purchase process to assist users in purchasing artist-related products.

[1558] "Information generation means" means a means for generating new text or content for a user using a generative AI model.

[1559] "Strategy formulation tools" are tools for formulating strategies for taking optimal actions and decisions based on collected and analyzed information.

[1560] The "emotion analysis means" is a means for analyzing the user's emotions and adjusting the information provided and service content based on the analysis.

[1561] The present invention relates to a system that efficiently collects and analyzes the latest information about a specific subject (hereinafter referred to as "artist"), supports fan activities, recognizes user emotions, and provides services based on those emotions. This system includes information collection means, analysis means, notification means, purchase support means, information generation means, strategy formulation means, and emotion analysis means.

[1562] Information gathering methods

[1563] The server uses the artist's name as a key to collect information from public databases on the Internet, news sites, social networking services, and official websites. The server then uses scraping technology and APIs to obtain text data and stores it in a database. This allows data collected from a wide variety of sources to be managed centrally.

[1564] Analysis means

[1565] The server analyzes the collected information using natural language processing (NLP) technology. Specifically, it performs entity recognition, article summarization, sentiment analysis, etc., and scores the information for its relevance and importance. Based on the results of this analysis, it filters out information with high scores and excludes data with low scores, extracting only useful information.

[1566] Notification means

[1567] The server then provides the filtered information to the user's device via push notification or email. The notification method includes a custom notification function based on user settings, providing information at the optimal time based on the user's time and interests. Furthermore, an emotion analysis method is used to analyze the user's current emotions and adjust the notification content to suit the user's state, resulting in more user-friendly notifications.

[1568] Purchasing support methods

[1569] The server analyzes the user's purchasing history and selects items that match the user's preferences from a database of artist-related products. The selected items are then recommended to the user via push notification or email, and sentiment analysis techniques are used to suggest optimal items to increase purchasing motivation.

[1570] Information generation means

[1571] The server uses the generative AI model to generate new text and content for the user. For example, when generating text for a user to post on social media, the server analyzes the user's past posting data and engagement data to create an effective post. It also uses sentiment analysis to adjust the generated text to match the user's current emotions.

[1572] Example prompt sentence:

[1573] Describe how you would handle a system that helps users create original music in the style of a specific artist.

[1574] Strategy formulation tools

[1575] The server formulates strategies for optimal actions and decisions based on the collected and analyzed information. In particular, it formulates optimal ticket purchasing strategies based on artist tour information and live event information, and notifies users of the appropriate timing for purchase and how to select tickets. Emotion analysis takes into account the user's emotional state and adjusts the strategy to provide optimal support to the user.

[1576] Emotion analysis means

[1577] The server uses emotion analysis tools to analyze the user's emotions. This involves analyzing the user's social media posts, email content, and system action logs to understand the user's current emotional state. The analysis results are used in conjunction with other tools to adjust notification content and personalize information provision.

[1578] This system allows users to efficiently collect the latest information about specific artists in real time and receive filtered information based on analysis results. Furthermore, through sentiment analysis, it provides users with the information they need most at the optimal time, enhancing their fan activities.

[1579] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1580] Step 1: Gather information

[1581] The server uses the artist's name as a key to collect information from public databases, news sites, social networking services, and official websites on the Internet. Specifically, it uses scraping technology and APIs to obtain text data and stores it in a database. The input is the artist's name and the URL of the source of information, and the output is reviewable text data.

[1582] Step 2: Information analysis

[1583] The server analyzes the collected information using natural language processing (NLP) technology. Specifically, it performs entity recognition, article summarization, and sentiment analysis, and scores the relevance and importance of the information. The input is the text data collected in Step 1, and the output is the analyzed data with an importance score.

[1584] Step 3: Information filtering

[1585] The server filters the information based on the analysis results. Specifically, it keeps information with high scores and filters out data with low importance. The input is the analysis data generated in step 2, and the output is the filtered, useful information.

[1586] Step 4: Prepare for notification

[1587] The server prepares the filtered information for notification. Specifically, it formats it into a push notification or email format based on the user's settings. The input is the filtered information, and the output is the message data for notification.

[1588] Step 5: Sentiment analysis

[1589] The server analyzes the user's emotions. Specifically, it analyzes the user's social media posts and the system's action logs to understand the user's current emotional state. The input is the user's past data, and the output is data that represents the user's current emotional state.

[1590] Step 6: Send notification

[1591] The server sends the notification message data to the user's device. It reflects the emotion analysis data and adjusts the notification content according to the user's emotion. The input is the message data prepared in step 4 and the emotion analysis data generated in step 5, and the output is the notification sent to the user.

[1592] Step 7: User Verification

[1593] The user checks the notification through their device. Specifically, they receive a push notification or email on their device and view the content. The input is the notification data, and the output is the user's confirmation action.

[1594] Step 8: Gather feedback

[1595] The server collects user feedback, for example, by logging user reactions and actions to notifications. The input is the user action log, and the output is the feedback data.

[1596] In this way, by clearly indicating the specific operations and data flow at each step, it becomes easier to understand the processing of the entire system.

[1597] (Application example 2)

[1598] 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."

[1599] Conventional entertainment systems lack a means for users to obtain real-time updates about their favorite artists in autonomous vehicles, making it difficult to analyze users' emotions and provide appropriate information. Therefore, to improve the user experience, a comprehensive entertainment system that includes real-time information provision and emotion analysis is needed.

[1600] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an information collection means, an analysis means, a notification means, an emotion analysis means, an in-vehicle entertainment system, and a real-time information provision means. This enables a user in an autonomous vehicle to obtain the latest information about their favorite artist in real time and to provide optimal information and services based on the user's emotions.

[1601] "Information gathering means" refers to the means of gathering the latest information about a specific subject from public databases, news sites, social networking services, official websites, etc. on the Internet.

[1602] "Analysis means" refers to a means for evaluating the importance and relevance of collected information and for filtering it.

[1603] "Notification means" refers to a means for notifying the user of the analyzed information, and includes push notifications, emails, voice alerts, etc.

[1604] "Purchase support means" refers to means for supporting the process of users purchasing products and services related to their favorite artists.

[1605] The "generation means" is a means for generating new content or information based on a user's request.

[1606] "Strategy formulation means" is a means for formulating optimal action strategies based on collected and analyzed information.

[1607] "Emotion analysis means" is a means for analyzing a user's emotions and providing appropriate information and services based on the results.

[1608] An "in-vehicle entertainment system" is a system that provides entertainment content such as music, videos, and games for users to enjoy inside an autonomous vehicle.

[1609] The "real-time information providing means" is a means for instantly providing users with the latest information collected in real time.

[1610] This invention constitutes an entertainment system that allows users in self-driving vehicles to obtain the latest information about their favorite artists in real time and provide optimal content and services through emotion analysis.

[1611] The server is equipped with information collection means, analysis means, notification means, sentiment analysis means, an in-vehicle entertainment system, and real-time information provision means, improving the user experience and enabling users to enjoy important information about artists even while on the move.

[1612] Hardware and Software Description

[1613] Hardware:

[1614] Infotainment displays for autonomous vehicles

[1615] Network Module

[1616] Sensor and camera system (for analyzing user emotions)

[1617] software:

[1618] Python script

[1619] News API

[1620] Twitter API

[1621] smtplib (Python email library)

[1622] TextBlob (text analysis library)

[1623] Program processing explanation

[1624] The server uses News API and Twitter API to gather the latest information about the artist from public databases, news sites, social networking services, and official websites on the Internet. The collected information undergoes sentiment analysis using TextBlob, an analytical tool, and is filtered based on its importance and relevance. The filtered information is then sent in real time to the user's email address and the infotainment display in the autonomous vehicle via a notification tool.

[1625] In addition, as a means of emotion analysis, the vehicle uses sensors and camera systems inside the vehicle to analyze the user's facial expressions and voice, and provides information optimized for the user based on the results. As a means of providing real-time information, the vehicle is equipped with a mechanism to immediately notify the user of new data collected in real time.

[1626] Specific examples

[1627] While traveling in an autonomous vehicle, users may not want to miss the latest information on their favorite artists. In such cases, users register the artist's name in the system. The server collects information about the artist from multiple sources on the Internet in real time and performs sentiment analysis and filtering using TextBlob. Important and relevant information is immediately notified to the user and displayed on the vehicle's infotainment display. In addition, sensors and camera systems analyze the user's facial expressions and voice to provide optimal content based on the user's emotions.

[1628] Example prompts for generative AI models:

[1629] "Create an application that provides real-time updates about a favorite artist in an autonomous vehicle's entertainment system. Analyze user sentiment, filter news and social media posts, and notify the user of the appropriate information."

[1630] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1631] Step 1:

[1632] The server receives the name of the artist registered by the user in the system. The input is the artist name registered by the user, and it sends a request to the News API or Twitter API using this as a key. The output is news articles or tweets about the artist.

[1633] Step 2:

[1634] The server analyzes collected news articles and tweets using Python's TextBlob library. The collected text data is used as input, and sentiment analysis and importance / relevance evaluation are performed. The output is filtered positive information.

[1635] Step 3:

[1636] The server sends the filtered information to the user's email address or the infotainment display in the autonomous vehicle. The filtered information and the user's notification settings are input, and based on this, the information is sent in the form of a push notification or email. The output is the user receiving the latest information in real time.

[1637] Step 4:

[1638] The server uses the in-car sensors and camera system to analyze the user's facial expressions and voice to understand their emotional state. The input is the user's facial expression data and voice data, and emotion analysis is performed based on this. The output is the user's emotional state.

[1639] Step 5:

[1640] The server selects the most appropriate content based on the user's emotional state and sends the notification again. The input is the user's emotional state and filtered information, and based on this, the server selects the most appropriate content and notification content. The output is information optimized for the user's emotions.

[1641] Step 6:

[1642] The user views the information notified via the infotainment display in the autonomous vehicle or on their smartphone. The input is the notified information, and by checking it, the user can grasp the latest information about the artist in real time. The output is an update of the user's knowledge about the artist.

[1643] 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.

[1644] 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.

[1645] 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.

[1646] [Fourth embodiment]

[1647] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1648] 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.

[1649] 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).

[1650] 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.

[1651] 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.

[1652] 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).

[1653] 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.

[1654] 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.

[1655] 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.

[1656] 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.

[1657] 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.

[1658] 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.

[1659] 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."

[1660] The present invention relates to a system that efficiently collects and analyzes the latest information about a specific subject (hereinafter referred to as "artist") and supports fan activities. This system includes information collection means, analysis means, notification means, purchase support means, generation means, and strategy formulation means.

[1661] 1. Providing new information

[1662] Program processing

[1663] The server periodically collects new information from multiple sources, including public databases on the Internet, news sites, social networking services, and official websites, using the artist's name as a key. The information collected by the server is analyzed using natural language processing technology and filtered based on relevance and importance. The filtered information is then delivered to the user's device via push notification or email.

[1664] Specific examples

[1665] A user wants to keep track of the latest information about a particular artist, so they input the artist's name into the system. The server then collects information about the artist from multiple sources on the Internet, filters out important news, articles, and social media posts, and notifies the user's device.

[1666] 2. Support for creating original songs

[1667] Program processing

[1668] The server acquires the artist's song data and analyzes musical elements such as rhythm, melody, chords, tempo, etc. Based on the analysis results, it provides an original song creation tool that users can use to create original songs.

[1669] Specific examples

[1670] If a user wants to create a song in the style of a certain artist, they specify the artist's musical style to the system. The server analyzes the artist's song data and extracts musical characteristics. The user can then use the provided templates and tools to create a song in the artist's style.

[1671] 3. Social media posting support

[1672] Program processing

[1673] The server retrieves the user's past social media posts and analyzes their content and engagement. The server then uses natural language generation technology to generate text for new posts and presents it to the user. The user can then review the generated text, edit it, and post it.

[1674] Specific examples

[1675] If a user is thinking about posting their impressions of a concert on social media but is unsure of how to write it, they can link their past social media posts to the system. The server analyzes past trends, generates text for a new post, and presents it to the user. The user can use that text as a reference when posting.

[1676] 4. Performance Analysis

[1677] Program processing

[1678] The server collects past live performance footage and audio, analyzes performance trends, song lists, and audience reactions, and based on the analysis results, suggests songs that are likely to be played at the next live performance and suggests effective ways to cheer on the band.

[1679] Specific examples

[1680] If a user wants to predict what songs will be played at an upcoming live concert, they register the concert information in the system. The server analyzes past performance data and shares with the user a list of songs that are likely to be played at the next live concert.

[1681] 5. Real-time tracking

[1682] Program processing

[1683] The server monitors artists' social media accounts and official websites, collecting new posts and news in real time. The collected information is organized and instantly sent to the user's device.

[1684] Specific examples

[1685] If a user wants to keep up with the latest news about their favorite artist, they can register the artist's social media account in the system. The server monitors the account in real time, and users are immediately notified of any new posts or news.

[1686] 6. Item Recommendations

[1687] Program processing

[1688] The server analyzes the user's purchasing history and selects items that match the user's preferences from a database of artist-related products. The selected items are then suggested to the user via push notification or email.

[1689] Specific examples

[1690] When a user wants to purchase new merchandise from an artist, they can connect their past purchase history to the system. The server analyzes their preferences, recommends related items, and supports the user in making the purchase.

[1691] 7. Fan Art Generation

[1692] Program processing

[1693] The server collects image data of artists, analyzes their style and characteristics, and generates fan art based on the analysis results, which is then made available for users to download.

[1694] Specific examples

[1695] When a user wants to create fan art of an artist, they provide an image of the artist to the system, and the server analyzes the style and provides the user with AI-generated fan art.

[1696] 8. Develop an event strategy

[1697] Program processing

[1698] The server collects information about artists' tours and live events, formulates the optimal ticket purchasing strategy, and notifies users of the timing of purchases and how to select the best tickets.

[1699] Specific examples

[1700] If a user wants to buy tickets to an upcoming live event but doesn't know the best way to do so, they register the tour information in the system. The server analyzes the event information and suggests the best ticket purchasing strategy to the user.

[1701] In this way, this system effectively manages and analyzes a wide variety of information and provides a multifunctional service to support fan activities. By using this system, users can improve the efficiency of their fan activities and have a richer experience.

[1702] The processing flow will be explained below.

[1703] 1. Providing new information

[1704] Program processing

[1705] Step 1:

[1706] The server uses the name of a specific artist as a key to collect information from public databases, news sites, social networking services, and official websites on the Internet.

[1707] Step 2:

[1708] The server analyzes the collected information using natural language processing (NLP) techniques to evaluate its importance and relevance.

[1709] Step 3:

[1710] The server filters the information based on the evaluation results and removes unnecessary data.

[1711] Step 4:

[1712] The server sends the filtered information to the user's device via push notification or email.

[1713] 2. Support for creating original songs

[1714] Program processing

[1715] Step 1:

[1716] The server acquires music data of the specified artist.

[1717] Step 2:

[1718] The server analyzes the music data and extracts musical features such as rhythm, melody, chords, and tempo.

[1719] Step 3:

[1720] The server generates a music composition tool based on the extracted features and provides it to the user's terminal.

[1721] Step 4:

[1722] The user creates an original piece of music using the provided music creation tool.

[1723] 3. Social media posting support

[1724] Program processing

[1725] Step 1:

[1726] The server retrieves the user's past SNS posting data.

[1727] Step 2:

[1728] The server analyzes past posts' content, tone, and engagement.

[1729] Step 3:

[1730] The server uses natural language generation (NLG) technology to generate text for new posts.

[1731] Step 4:

[1732] The server presents the generated text to the user's terminal.

[1733] Step 5:

[1734] The user checks the presented text, edits it, and posts it to a social networking site.

[1735] 4. Performance Analysis

[1736] Program processing

[1737] Step 1:

[1738] The server collects past live footage and audio data.

[1739] Step 2:

[1740] The server analyzes the collected data and extracts information about the songs being performed, audience reactions, and performance trends.

[1741] Step 3:

[1742] Based on the analysis results, the server predicts the list of songs that are likely to be played at the next live concert and how to support the band.

[1743] Step 4:

[1744] The server provides the prediction information to the user's terminal.

[1745] 5. Real-time tracking

[1746] Program processing

[1747] Step 1:

[1748] The server monitors the artist's social media accounts and official website.

[1749] Step 2:

[1750] The server collects new posts and news in real time.

[1751] Step 3:

[1752] The server organizes the collected information and selects information that is important to the user.

[1753] Step 4:

[1754] The server immediately notifies the user's device of important information.

[1755] 6. Item Recommendations

[1756] Program processing

[1757] Step 1:

[1758] The server acquires the user's past purchase history.

[1759] Step 2:

[1760] The server analyzes the purchase history and understands the user's preferences.

[1761] Step 3:

[1762] The server selects items that match the user's preferences from a database of artist-related products available on the market.

[1763] Step 4:

[1764] The server will then suggest the selected items to the user's device via push notification or email.

[1765] 7. Fan Art Generation

[1766] Program processing

[1767] Step 1:

[1768] The server collects image data of artists and analyzes their styles and characteristics.

[1769] Step 2:

[1770] The server uses AI to generate fan art based on the analysis results.

[1771] Step 3:

[1772] The server provides the generated fan art in a downloadable format to the user's device.

[1773] 8. Develop an event strategy

[1774] Program processing

[1775] Step 1:

[1776] The server collects information about artists' tours and live events.

[1777] Step 2:

[1778] Based on the event information collected by the server, the optimal ticket purchasing strategy is developed.

[1779] Step 3:

[1780] The server provides the strategic information formulated by the server to the user's device to support the purchase process.

[1781] Step 4:

[1782] Based on the information provided by the user, the user purchases tickets at the optimal time and participates in the event.

[1783] Example 1

[1784] 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."

[1785] Conventional fan activity support systems are inefficient in collecting and analyzing the latest information on specific subjects, making it difficult for users to efficiently obtain information and improve the quality of their activities. Furthermore, they lack support for music creation and posting to social networking services, performance analysis, and real-time information tracking, making it difficult for users to centrally manage a wide range of activities. Analytical methods for properly evaluating the relevance and importance of information are also inadequate, creating a need for a method that provides only useful information to users.

[1786] 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.

[1787] In this invention, the server includes an information collection means, an analysis means, a notification means, a purchase support means, a generation means, a strategy formulation means, a music creation support means, a social network service posting support means, a performance analysis means, a real-time tracking means, an item recommendation means, and an artwork creation means, thereby enabling centralized and effective support for a wide range of fan activities, such as efficient collection and analysis of the latest information on a specific subject, timely notification to users, music creation support, social network service posting support, performance analysis, real-time information tracking, item recommendation, and fan art generation.

[1788] "Information gathering means" refers to the means of gathering the latest information on a specific subject from public databases, news sites, social networking services, and official websites on the Internet.

[1789] "Analysis means" refers to means for evaluating importance and relevance based on collected information and song data, data posted in the past on social networking services, and live performance data, and for filtering and analyzing the data.

[1790] "Notification means" refers to a means for sending filtered information to the user's device via push notification or email.

[1791] The "purchase support means" is a means for analyzing the user's purchase history and selecting and suggesting items that match the user's preferences from a database of artist-related products.

[1792] The "generation means" is a means for automatically generating new content and suggestions based on collected and analyzed data and providing them to users.

[1793] The "strategy formulation means" is a means for formulating an optimal ticket purchasing strategy based on artist tour information and live event information, and notifying the user of the strategy.

[1794] "Music composition support means" is a means for analyzing an artist's music data and providing a tool that enables a user to create original music based on the analysis results.

[1795] The "social network service posting support means" is a means for analyzing a user's past SNS posting data, automatically generating text for a new post, and providing it to the user.

[1796] "Performance analysis means" refers to a method of collecting past live performance footage and audio recordings, analyzing that data, and evaluating performance trends, song lists, and audience reactions.

[1797] "Real-time tracking means" refers to a means of monitoring an artist's social media accounts and official websites, collecting new posts and news in real time, and notifying users.

[1798] The "item recommendation means" is a means for analyzing the purchase history of a user and recommending highly relevant artist-related merchandise items.

[1799] The "artwork generation means" is a means for automatically generating fan art based on the artist's style and characteristics by analyzing the artist's image data and providing it to the user.

[1800] The present invention relates to a system for efficiently collecting and analyzing the latest information on a specific subject and supporting fan activities. The system includes an information collection means, an analysis means, a notification means, a purchasing support means, a creation means, a strategy formulation means, a music creation support means, a social network service posting support means, a performance analysis means, a real-time tracking means, an item recommendation means, and an art creation means.

[1801] Information gathering methods

[1802] The server uses information gathering tools to collect the latest information about the artist from public databases, news sites, social networking services, and official websites on the Internet, specifically using web scraping tools (e.g., Beautiful Soup, Scrapy) and APIs.

[1803] Example: A user wants to track the latest information about a particular artist and enters the artist's name into the system. The server collects information about the artist from multiple sources on the Internet, filters out important news, articles, and social media posts, and notifies the user's device.

[1804] Example prompt: "Please gather the latest information on the artist's name."

[1805] Analysis means

[1806] The server uses analytical tools to analyze the collected information, song data, past SNS posting data, and live performance data. Specifically, it uses text analysis tools (e.g., SpaCy, NLTK), music analysis tools (e.g., LibROSA, Essentia), and video analysis tools (e.g., OpenCV, Dlib).

[1807] Examples: Analyzing data collected by a server to evaluate importance and relevance and filter out noise on the Internet. Analyzing the content of news articles to extract important keywords and rank information based on importance and relevance.

[1808] Example prompt: "Analyze a news article about the artist's name."

[1809] Notification means

[1810] The server sends the filtered information to the user's device via push notification or email, using notification services such as Firebase or SendGrid.

[1811] Example: The server immediately sends filtered information to the user, allowing the user to grasp important information without missing it.

[1812] Example prompt: "Push important information to users."

[1813] Purchasing support methods

[1814] The server analyzes the user's purchase history and selects and suggests items that match the user's preferences from a database of artist-related products, using a purchase history analysis tool (e.g., Google Analytics, Tableau).

[1815] Example: If a user wants to buy new merchandise from an artist, the system analyzes their past purchase history and recommends related items.

[1816] Example prompt: "Recommend artist-related products based on the user's purchasing history."

[1817] generation means

[1818] The server uses a generating means to automatically generate new content and suggestions based on the collected and analyzed data and provide them to the user.

[1819] Example: The server analyzes the collected data and generates and provides useful articles and posts to users.

[1820] Example prompt: "Generate the latest news article about an artist."

[1821] Strategy formulation tools

[1822] This is a method for the server to create the optimal ticket purchasing strategy based on artist tour information and live event information and notify users. Event information acquisition tools (e.g., Eventbrite, Ticketmaster API) are used to collect this information.

[1823] Example: If a user wants to purchase tickets to an upcoming live event but isn't sure how best to do so, the server analyzes the event information and suggests the best ticket purchasing strategy to the user.

[1824] Example prompt: "Suggest a ticket purchasing strategy for the next live event."

[1825] Music creation support tools

[1826] The server retrieves the artist's music data and analyzes the rhythm, melody, chords, and tempo using music analysis software (e.g., Sonic Visualiser, MADM), and provides original music creation tools (e.g., Magix Music Maker, Ableton Live) based on the analysis results.

[1827] Example: Providing an interface that allows users to create original music based on the musical characteristics of artists analyzed by the server.

[1828] Example prompt: "Give me a tool to create music in the style of the artist."

[1829] Social networking service posting support tool

[1830] The server retrieves the user's past social media posts, analyzes the content and engagement of the posts, and uses social media data analysis tools (e.g., Hootsuite, Sprout Social) to generate text for new posts using natural language generation technology (e.g., GPT-3, BERT).

[1831] Example: If a user wants to post their impressions of a concert on social media but isn't sure how to write it, the server analyzes past trends and generates and provides new text for the post.

[1832] Example prompt: "Generate text to post on social media about your impressions of the concert."

[1833] Performance Analysis Tools

[1834] The server collects past live video and audio recordings and analyzes performance trends, track lists, and audience reactions using video analysis tools (e.g., OpenCV, FFmpeg) and audio analysis tools (e.g., LibROSA, Praat).

[1835] Example: A server provides a user with a list of songs that are likely to be played at an upcoming live show.

[1836] Example prompt: "Predict the song most likely to be played at the next live show."

[1837] Real-time tracking methods

[1838] The server monitors the artist's social media accounts and official website to collect new posts and news in real time using web scraping tools (e.g., Beautiful Soup, Scrapy) and APIs.

[1839] Example: The server monitors in real time and notifies users immediately when there is a new post or news.

[1840] Example prompt: "Please notify me of real-time updates on artist names."

[1841] Item recommendation method

[1842] The server analyzes the user's purchase history and selects items that match the user's preferences from a database of artist-related products. The analysis is performed using a purchase history analysis tool (e.g., Google Analytics, Tableau).

[1843] Example: The server analyzes the user's preferences and recommends related items to assist with purchasing.

[1844] Example prompt: "Recommend artist-related products based on the user's purchasing history."

[1845] Art creation means

[1846] The server collects the artist's image data and analyzes its style and characteristics using image analysis tools (e.g., TensorFlow, Keras). Based on the analysis results, fan art is generated and made available for users to download.

[1847] Example: If a user wants to create fan art of an artist, the server analyzes the style and serves the generated fan art to the user.

[1848] Example prompt: "Generate fan art of artist name."

[1849] This allows the system to effectively manage and analyze a wide range of information and provide multifunctional services to support fan activities, allowing users to improve the efficiency of their fan activities and enjoy a richer experience.

[1850] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1851] Providing new information

[1852] Step 1:

[1853] The server receives the artist name as input from the user, specifically, the server retrieves the artist name through a web interface.

[1854] Step 2:

[1855] The server collects data from public databases, news sites, social networking services, and official websites on the Internet using web scraping tools (e.g., Beautiful Soup, Scrapy) or APIs. The input is artist names, and the output is the collected, unparsed data.

[1856] Step 3:

[1857] The server analyzes the collected data using natural language processing techniques (e.g., SpaCy, NLTK) to evaluate its relevance and importance. The input is the collected data, and the output is the analyzed information.

[1858] Step 4:

[1859] The server filters the results of the analysis and extracts only the information that is deemed important to the user. The input is the analyzed information, and the output is the filtered information.

[1860] Step 5:

[1861] The server sends the filtered information to the user's device via push notification or email. It uses a notification service such as Firebase or SendGrid. The input is the filtered information, and the output is the notification sent to the user.

[1862] Original song creation support

[1863] Step 1:

[1864] The user inputs the artist's musical style into the system, and the server retrieves the artist's name through a web interface.

[1865] Step 2:

[1866] The server uses the music streaming service API (e.g., Spotify API, YouTube Data API) to obtain the artist's song data. The input is the artist name, and the output is the obtained song data.

[1867] Step 3:

[1868] The server uses a music analysis tool (e.g., LibROSA, Essentia) to analyze the rhythm, melody, chords, tempo, etc. of the song. The input is the song data, and the output is the analysis results.

[1869] Step 4:

[1870] The server provides users with original music creation tools (e.g., Magix Music Maker, Ableton Live). The input is the analysis results, and the output is the creation tools provided to users.

[1871] Step 5:

[1872] Users create original music using the provided tools. The input is the creation tool and the user's actions, and the output is a new original piece of music.

[1873] SNS posting support

[1874] Step 1:

[1875] The server connects to SNS APIs (e.g., Twitter API, Facebook Graph API) to retrieve users' past SNS posts. The input is user account information, and the output is the retrieved past post data.

[1876] Step 2:

[1877] The server analyzes the post content and engagement using a social media data analysis tool (e.g., Hootsuite, Sprout Social Analytics). The input is past post data, and the output is the analysis results.

[1878] Step 3:

[1879] The server generates text for new posts using natural language generation techniques (e.g., GPT-3, BERT). The input is the analysis result, and the output is the generated text.

[1880] Step 4:

[1881] The user checks and edits the generated text and posts it to the social networking site. The input is the generated text and the user's edits, and the output is the posted social networking site content.

[1882] Performance Analysis

[1883] Step 1:

[1884] The server uses the YouTube Data API and Spotify API to collect past live video and audio data. The input is live event information, and the output is the captured video and audio data.

[1885] Step 2:

[1886] The server analyzes the performance data using video analysis tools (e.g., OpenCV, Dlib) and audio analysis tools (e.g., LibROSA, Praat). The input is video and audio data, and the output is the analysis results.

[1887] Step 3:

[1888] The server uses machine learning models (e.g., LSTM, Random Forest) to predict the songs that are likely to be played at the next live show based on the analysis results. The input is the analysis results, and the output is the predicted song list.

[1889] Step 4:

[1890] The server proposes effective cheering methods to the user. The input is a predicted song list, and the output is a suggested cheering method.

[1891] Real-time tracking

[1892] Step 1:

[1893] The server sets up a web scraping tool (e.g., Beautiful Soup, Scrapy) or API to monitor artists' social media accounts and official websites. The input is the monitored account information, and the output is the collected real-time information.

[1894] Step 2:

[1895] The server analyzes and organizes the collected information in real time. The input is real-time information, and the output is organized information.

[1896] Step 3:

[1897] The server immediately sends a notification to the user's device. It uses a notification service such as Firebase or SendGrid. The input is organized information, and the output is the notification sent to the user.

[1898] Item Recommendations

[1899] Step 1:

[1900] The server obtains the user's purchase history. Specifically, it retrieves information from a database where purchase history is stored. The input is the user's account information, and the output is the obtained purchase history data.

[1901] Step 2:

[1902] The server analyzes the purchase history using a purchase history analysis tool (e.g., Google Analytics, Tableau). The input is the purchase history data, and the output is the analysis results.

[1903] Step 3:

[1904] The server selects items that match the user's preferences from a database of artist-related products. The input is the analysis results, and the output is a list of recommended items.

[1905] Step 4:

[1906] The server proposes a recommended item list to the user. The input is the item list, and the output is the item recommendations notified to the user.

[1907] Artwork Creation

[1908] Step 1:

[1909] The server collects image data of artists. Specifically, it retrieves images from the Internet using a web crawler or API. The input is the artist's name, and the output is the collected image data.

[1910] Step 2:

[1911] The server analyzes the image data using image analysis tools (e.g., TensorFlow, Keras). The analysis includes extracting styles and features. The input is the image data, and the output is the analysis results.

[1912] Step 3:

[1913] The server uses a generative AI model to generate fan art based on the analysis results. The input is the analysis results, and the output is the generated fan art.

[1914] Step 4:

[1915] The server prepares the generated fan art as a download resource for the user. The input is the generated fan art, and the output is a download link provided to the user.

[1916] (Application example 1)

[1917] 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."

[1918] The goal of this project is to solve the problem of fans finding it difficult to efficiently gather the latest information on specific topics and obtain it in real time. In particular, there is a lack of means to gather news and social media information in a timely manner and notify users every five minutes.

[1919] 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.

[1920] In this invention, the server includes an information collection means, an analysis means, a notification means, a purchase support means, a generation means, a strategy formulation means, a means for collecting news and SNS information related to a specific target in real time, and a means for notifying the collected information every five minutes, thereby enabling fans to receive the latest information related to the specific target in a timely manner.

[1921] "Information gathering means" refers to means of gathering information about a specific subject from public databases on the Internet, news sites, social networking services, official websites, etc.

[1922] The "analysis means" is a means for evaluating the importance and relevance of collected information and filtering it.

[1923] "Notification means" refers to a means of providing filtered information to a user's device via push notification or email.

[1924] "Purchase support means" refers to means for supporting a user's purchase.

[1925] "Generation means" refers to the means for creating new data or content.

[1926] "Strategy formulation tools" are means for creating optimal action plans based on collected and analyzed information.

[1927] "Means for collecting news and social media information about a specific subject in real time" refers to means for instantly collecting the latest news articles and posts on social networking services about a specific subject.

[1928] "Means for notifying collected information every 5 minutes" refers to means for notifying the user of the latest collected information every 5 minutes.

[1929] This invention relates to a system that efficiently collects, analyzes, and provides users with the latest information on a specific subject in real time. This system includes information collection means, analysis means, notification means, purchase support means, generation means, strategy formulation means, means for collecting news and SNS information on the specific subject in real time, and means for notifying users of the collected information every five minutes.

[1930] Program processing

[1931] The server executes a program in the following procedure to collect the latest information on a specific subject. First, it uses an information collection means to collect information on the specific subject from public databases on the Internet, news sites, social networking services, official websites, etc. Next, it uses an analysis means to analyze the collected information and filter it according to importance and relevance. Then, it uses a notification means to send the filtered information to the user's device every five minutes. This allows the user to receive the latest information on the specific subject in real time.

[1932] Hardware and software used

[1933] The hardware used includes a server, the user's smartphone or head-mounted display, and the software used is a Python program, the Twitter API, BeautifulSoup (a scraping library), APScheduler (a scheduling library), and SMTP (an email sending protocol).

[1934] Specific examples

[1935] As a concrete example, consider the case where a user wants to track the latest information about an artist named "Your Favorite Artist." In this system, all a user needs to do is enter the artist's name, and the server will monitor news sites and social media in real time, collecting data whenever new information is posted. The collected data is filtered using an analysis method to select important information. The filtered information is then sent to the user's smartphone every five minutes using a notification method, ensuring that the user always has the latest information at their fingertips.

[1936] Prompt Sentence Examples

[1937] An example of a prompt to input to a generative AI model would be:

[1938] "Please create a system that notifies me of the latest updates about my favorite artist. This system will use the Twitter API to collect the artist's latest tweets, scrape Google News to get related news, and send me an email with the collected information every 5 minutes."

[1939] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1940] Step 1:

[1941] The server uses information gathering tools to collect the latest information about a specific subject from public databases, news sites, social networking services, and official websites on the Internet. The input is the name of the target (e.g., artist name), and the output is the collected raw data. Specifically, the server performs web scraping or API requests to retrieve articles and posts related to the target.

[1942] Step 2:

[1943] The server analyzes the collected raw data using analytical methods. The input is the collected raw data, and the output is filtered information. Specifically, the server uses natural language processing technology to analyze the text data and filter it according to importance and relevance. For example, it scores news article headlines and social media posts and selects only those with high scores.

[1944] Step 3:

[1945] The server uses a notification method to send the filtered information to the user's device. The input is the filtered information, and the output is a notification displayed on the user's device. Specifically, the server uses the SMTP protocol to send emails or an API that implements push notifications to the user's smartphone or head-mounted display.

[1946] Step 4:

[1947] The server constantly monitors the latest information using a method for collecting news and social media information about a specific subject in real time. The input is the name of the specific subject (e.g., artist name), and the output is the collected real-time data. Specifically, the server collects information at set intervals (e.g., every 5 minutes) and continuously performs API requests and web scraping.

[1948] Step 5:

[1949] The server periodically sends the latest information to the user's device using a method that notifies the collected information every 5 minutes. The input is the collected real-time data, and the output is a notification sent every 5 minutes. Specifically, the server uses APScheduler to schedule and notify the user of filtered information at regular intervals.

[1950] Step 6:

[1951] By receiving notifications, users can obtain the latest information about specific subjects in real time. The input is the notification sent from the server, and the output is the latest information received by the user. Specifically, notifications are displayed on the user's smartphone or head-mounted display, allowing the user to instantly check the latest information.

[1952] 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.

[1953] The present invention relates to a system that efficiently collects and analyzes the latest information about a specific subject (hereinafter referred to as "artist"), supports fan activities, recognizes user emotions, and provides services based on those emotions. This system includes information collection means, analysis means, notification means, purchase support means, generation means, strategy formulation means, and an emotion engine.

[1954] 1. Providing new information

[1955] Program processing

[1956] The server uses the artist's name as a key to collect information from public databases on the Internet, news sites, social networking services, and official websites. The information collected by the server is analyzed using natural language processing technology and filtered based on relevance and importance. The filtered information is then delivered to the user's device via push notification or email. Furthermore, an emotion engine analyzes the user's emotions and delivers the filtered results in a format appropriate to the emotion.

[1957] Specific examples

[1958] A user wants to track the latest information about a particular artist and enters the artist's name into the system. The server collects information about the artist from multiple sources on the Internet and filters out important news, articles, and social media posts. The emotion engine analyzes the user's emotions, determines which information is most relevant, and notifies the user.

[1959] 2. Support for creating original songs

[1960] Program processing

[1961] The server acquires the artist's song data and analyzes musical elements such as rhythm, melody, chords, and tempo. Based on the analysis results, it provides an original song creation tool that users can use to create original songs. The emotion engine analyzes the user's emotions and makes song creation suggestions.

[1962] Specific examples

[1963] If a user wants to create a song in the style of a certain artist, they specify the artist's musical style to the system. The server analyzes the artist's song data and extracts musical characteristics. The emotion engine analyzes the user's emotions when creating the song and suggests appropriate templates and tools to help create a song that is more suited to the user.

[1964] 3. Social media posting support

[1965] Program processing

[1966] The server retrieves the user's past social media posts and analyzes their content and engagement. The server uses natural language generation technology to generate text for new posts and presents it to the user. The emotion engine analyzes the user's current emotions and adjusts the post text to match those emotions. The user can then review the generated text, edit it, and post it.

[1967] Specific examples

[1968] If a user is thinking about posting their impressions of a concert on social media but is unsure how to write it, they can link their past social media posts to the system. The server analyzes past trends and generates text for a new post, and an emotion engine analyzes the user's current emotions and adjusts the text accordingly. The user can use that text as a reference when posting.

[1969] 4. Performance Analysis

[1970] Program processing

[1971] The server collects past live footage and audio, and analyzes performance trends, track lists, and audience reactions. Based on the analysis results, it suggests songs that are likely to be played at the next live show and effective cheering methods to users. The emotion engine analyzes the user's emotions and adjusts cheering methods and performance analysis results based on their emotions.

[1972] Specific examples

[1973] If a user wants to predict what songs will be played at the next live concert, they register the live concert information in the system. The server analyzes past performance data and creates a list of songs that are likely to be played at the next live concert. The emotion engine analyzes the user's emotions and suggests appropriate ways to cheer.

[1974] 5. Real-time tracking

[1975] Program processing

[1976] The server monitors artists' social media accounts and official websites, collecting new posts and news in real time. The collected information is organized and instantly sent to the user's device. The emotion engine analyzes the user's emotions, selecting important information and adjusting the content of notifications.

[1977] Specific examples

[1978] If a user wants to keep up with the latest news about their favorite artist, they can register the artist's social media account in the system. The server monitors the information in real time and notifies the user immediately when new posts or news are posted. The emotion engine analyzes the user's emotions, determines which information is most useful to the user, and adjusts the content of the notifications accordingly.

[1979] 6. Item Recommendations

[1980] Program processing

[1981] The server analyzes the user's purchasing history and selects items that match the user's preferences from a database of artist-related products. The selected items are then recommended to the user via push notification or email. The emotion engine analyzes the user's emotions and recommends the optimal items to increase their desire to purchase.

[1982] Specific examples

[1983] When a user wants to purchase new merchandise from an artist, they connect their past purchase history to the system. The server analyzes their preferences and recommends related items, and the emotion engine analyzes the user's emotions and suggests items that will increase their desire to purchase.

[1984] 7. Fan Art Generation

[1985] Program processing

[1986] The server collects image data of artists and analyzes their style and characteristics. Based on the analysis results, AI is used to generate fan art, which is then provided to the user in a downloadable format. An emotion engine analyzes the user's emotions and adjusts the style and content of the generated fan art.

[1987] Specific examples

[1988] When a user wants to create fan art of an artist, they provide an image of the artist to the system. The server analyzes the style and provides AI-generated fan art. The emotion engine analyzes the user's emotions and adjusts the style and content of the fan art to provide fan art that is more suited to the user.

[1989] 8. Develop an event strategy

[1990] Program processing

[1991] The server collects artist tour information and live event information. Based on the collected information, it formulates the optimal ticket purchasing strategy. The server analyzes the user's emotions using an emotion engine, adjusts the existing strategy, and provides it to the user. The server supports the purchasing process by notifying the user of information on the best time to purchase and how to select the best tickets.

[1992] Specific examples

[1993] If a user wants to buy tickets to an upcoming live event but doesn't know the best way to do so, they register the tour information in the system. The server analyzes the event information and formulates the optimal ticket purchasing strategy. The emotion engine analyzes the user's emotions, adjusts the strategy, provides the user with appropriate information, and assists the user in the purchasing process.

[1994] In this way, this system effectively manages and analyzes a wide variety of information, and provides a multifunctional service that supports fan activities while taking into account users' emotions. By using this system, users can improve the efficiency of their fan activities and enjoy a richer experience.

[1995] The processing flow will be explained below.

[1996] 1. Providing new information

[1997] Program processing

[1998] Step 1:

[1999] The server uses the name of a specific artist as a key to collect information from public databases, news sites, social networking services, and official websites on the Internet.

[2000] Step 2:

[2001] The server analyzes the collected information using natural language processing (NLP) techniques to evaluate its importance and relevance.

[2002] Step 3:

[2003] The server filters the information based on the evaluation results and removes unnecessary data.

[2004] Step 4:

[2005] The emotion engine analyzes the user's emotions and adjusts the filtered information to suit the user's current emotions.

[2006] Step 5:

[2007] The server sends the adjusted information to the user's device via push notification or email.

[2008] 2. Support for creating original songs

[2009] Program processing

[2010] Step 1:

[2011] The server acquires music data of the specified artist.

[2012] Step 2:

[2013] The server analyzes the music data and extracts musical features such as rhythm, melody, chords, and tempo.

[2014] Step 3:

[2015] The server generates a music composition tool based on the extracted features and provides it to the user's device.

[2016] Step 4:

[2017] The emotion engine analyzes the user's emotions and adjusts song-making suggestions based on the user's current emotions.

[2018] Step 5:

[2019] The user creates an original piece of music using the provided music creation tool.

[2020] 3. Social media posting support

[2021] Program processing

[2022] Step 1:

[2023] The server retrieves the user's past SNS posting data.

[2024] Step 2:

[2025] The server analyzes past posts' content, tone, and engagement.

[2026] Step 3:

[2027] The emotion engine analyzes the user's current emotions and predicts the content of the text based on past posting data and current emotions.

[2028] Step 4:

[2029] The server uses natural language generation (NLG) technology to generate text for new posts.

[2030] Step 5:

[2031] The server presents the generated text to the user's terminal.

[2032] Step 6:

[2033] The user checks the presented text, edits it, and posts it to a social networking site.

[2034] 4. Performance Analysis

[2035] Program processing

[2036] Step 1:

[2037] The server collects past live footage and audio data.

[2038] Step 2:

[2039] The server analyzes the collected data and extracts information about the songs being performed, audience reactions, and performance trends.

[2040] Step 3:

[2041] The emotion engine analyzes the user's emotions and adjusts the performance analysis results based on the user's current emotions.

[2042] Step 4:

[2043] The server predicts the likely song list and cheering methods for the next live show.

[2044] Step 5:

[2045] The server provides the prediction information to the user's terminal.

[2046] 5. Real-time tracking

[2047] Program processing

[2048] Step 1:

[2049] The server monitors the artist's social media accounts and official website.

[2050] Step 2:

[2051] The server collects new posts and news in real time.

[2052] Step 3:

[2053] The server organizes the collected information and selects information that is important to the user.

[2054] Step 4:

[2055] The emotion engine analyzes the user's emotions and adjusts the information it notifies based on the user's current emotions.

[2056] Step 5:

[2057] The server immediately notifies the user's terminal of the adjusted important information.

[2058] 6. Item Recommendations

[2059] Program processing

[2060] Step 1:

[2061] The server acquires the user's past purchase history.

[2062] Step 2:

[2063] The server analyzes the purchase history and understands the user's preferences.

[2064] Step 3:

[2065] The emotion engine analyzes user emotions and adjusts item recommendations based on preferences and emotions.

[2066] Step 4:

[2067] The server selects items that match the user's preferences from a database of artist-related products available on the market.

[2068] Step 5:

[2069] The server will then suggest the selected items to the user's device via push notification or email.

[2070] 7. Fan Art Generation

[2071] Program processing

[2072] Step 1:

[2073] The server collects image data of artists and analyzes their styles and characteristics.

[2074] Step 2:

[2075] The server uses AI to generate fan art based on the analysis results.

[2076] Step 3:

[2077] The emotion engine analyzes the user's emotions and adjusts the style and content of the generated fan art.

[2078] Step 4:

[2079] The server provides the generated fan art in a downloadable format to the user's device.

[2080] 8. Develop an event strategy

[2081] Program processing

[2082] Step 1:

[2083] The server collects information about artists' tours and live events.

[2084] Step 2:

[2085] Based on the event information collected by the server, the optimal ticket purchasing strategy is developed.

[2086] Step 3:

[2087] The emotion engine analyzes users' emotions and adjusts strategies based on their preferences when attending events.

[2088] Step 4:

[2089] The server provides the strategic information formulated by the server to the user's device to support the purchase process.

[2090] Step 5:

[2091] Based on the information provided by the user, the user purchases tickets at the optimal time and participates in the event.

[2092] Example 2

[2093] 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."

[2094] Many users need a system that efficiently collects and analyzes the latest information about a specific subject and supports fan activities. Additionally, recognizing users' emotions and providing appropriate information and services based on those emotions offers new value not found in conventional systems. However, current methods lack the accuracy of information collection and appropriate information filtering, and it is difficult to provide services that take users' emotions into account.

[2095] 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.

[2096] In this invention, the server includes an information collection means, an analysis means, and a notification means. This makes it possible to efficiently collect and analyze the latest information on a specific subject and provide information filtered based on importance to the user's terminal. Furthermore, by including an emotion analysis means, it is possible to provide appropriate information based on the user's emotions and more effectively support fan activities.

[2097] "Information gathering means" refers to means for gathering information from public databases, news sites, social networking services, and official websites on the Internet.

[2098] "Analysis means" refers to a means for analyzing collected information using natural language processing technology, evaluating its relevance and importance, and filtering it.

[2099] The "notification means" is a means for providing filtered information to a user's device via push notification or email.

[2100] The "purchase support means" is a means for recommending appropriate items and supporting the purchase process to assist users in purchasing artist-related products.

[2101] "Information generation means" means a means for generating new text or content for a user using a generative AI model.

[2102] "Strategy formulation tools" are tools for formulating strategies for taking optimal actions and decisions based on collected and analyzed information.

[2103] The "emotion analysis means" is a means for analyzing the user's emotions and adjusting the information provided and service content based on the analysis.

[2104] The present invention relates to a system that efficiently collects and analyzes the latest information about a specific subject (hereinafter referred to as "artist"), supports fan activities, recognizes user emotions, and provides services based on those emotions. This system includes information collection means, analysis means, notification means, purchase support means, information generation means, strategy formulation means, and emotion analysis means.

[2105] Information gathering methods

[2106] The server uses the artist's name as a key to collect information from public databases on the Internet, news sites, social networking services, and official websites. The server then uses scraping technology and APIs to obtain text data and stores it in a database. This allows data collected from a wide variety of sources to be managed centrally.

[2107] Analysis means

[2108] The server analyzes the collected information using natural language processing (NLP) technology. Specifically, it performs entity recognition, article summarization, sentiment analysis, etc., and scores the information for its relevance and importance. Based on the results of this analysis, it filters out information with high scores and excludes data with low scores, extracting only useful information.

[2109] Notification means

[2110] The server then provides the filtered information to the user's device via push notification or email. The notification method includes a custom notification function based on user settings, providing information at the optimal time based on the user's time and interests. Furthermore, an emotion analysis method is used to analyze the user's current emotions and adjust the notification content to suit the user's state, resulting in more user-friendly notifications.

[2111] Purchasing support methods

[2112] The server analyzes the user's purchasing history and selects items that match the user's preferences from a database of artist-related products. The selected items are then recommended to the user via push notification or email, and sentiment analysis techniques are used to suggest optimal items to increase purchasing motivation.

[2113] Information generation means

[2114] The server uses the generative AI model to generate new text and content for the user. For example, when generating text for a user to post on social media, the server analyzes the user's past posting data and engagement data to create an effective post. It also uses sentiment analysis to adjust the generated text to match the user's current emotions.

[2115] Example prompt sentence:

[2116] Describe how you would handle a system that helps users create original music in the style of a specific artist.

[2117] Strategy formulation tools

[2118] The server formulates strategies for optimal actions and decisions based on the collected and analyzed information. In particular, it formulates optimal ticket purchasing strategies based on artist tour information and live event information, and notifies users of the appropriate timing for purchase and how to select tickets. Emotion analysis takes into account the user's emotional state and adjusts the strategy to provide optimal support to the user.

[2119] Emotion analysis means

[2120] The server uses emotion analysis tools to analyze the user's emotions. This involves analyzing the user's social media posts, email content, and system action logs to understand the user's current emotional state. The analysis results are used in conjunction with other tools to adjust notification content and personalize information provision.

[2121] This system allows users to efficiently collect the latest information about specific artists in real time and receive filtered information based on analysis results. Furthermore, through sentiment analysis, it provides users with the information they need most at the optimal time, enhancing their fan activities.

[2122] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2123] Step 1: Gather information

[2124] The server uses the artist's name as a key to collect information from public databases, news sites, social networking services, and official websites on the Internet. Specifically, it uses scraping technology and APIs to obtain text data and stores it in a database. The input is the artist's name and the URL of the source of information, and the output is reviewable text data.

[2125] Step 2: Information analysis

[2126] The server analyzes the collected information using natural language processing (NLP) technology. Specifically, it performs entity recognition, article summarization, and sentiment analysis, and scores the relevance and importance of the information. The input is the text data collected in Step 1, and the output is the analyzed data with an importance score.

[2127] Step 3: Information filtering

[2128] The server filters the information based on the analysis results. Specifically, it keeps information with high scores and filters out data with low importance. The input is the analysis data generated in step 2, and the output is the filtered, useful information.

[2129] Step 4: Prepare for notification

[2130] The server prepares the filtered information for notification. Specifically, it formats it into a push notification or email format based on the user's settings. The input is the filtered information, and the output is the message data for notification.

[2131] Step 5: Sentiment analysis

[2132] The server analyzes the user's emotions. Specifically, it analyzes the user's social media posts and the system's action logs to understand the user's current emotional state. The input is the user's past data, and the output is data that represents the user's current emotional state.

[2133] Step 6: Send notification

[2134] The server sends the notification message data to the user's device. It reflects the emotion analysis data and adjusts the notification content according to the user's emotion. The input is the message data prepared in step 4 and the emotion analysis data generated in step 5, and the output is the notification sent to the user.

[2135] Step 7: User Verification

[2136] The user checks the notification through their device. Specifically, they receive a push notification or email on their device and view the content. The input is the notification data, and the output is the user's confirmation action.

[2137] Step 8: Gather feedback

[2138] The server collects user feedback, for example, by logging user reactions and actions to notifications. The input is the user action log, and the output is the feedback data.

[2139] In this way, by clearly indicating the specific operations and data flow at each step, it becomes easier to understand the processing of the entire system.

[2140] (Application example 2)

[2141] 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."

[2142] Conventional entertainment systems lack a means for users to obtain real-time updates about their favorite artists in autonomous vehicles, making it difficult to analyze users' emotions and provide appropriate information. Therefore, to improve the user experience, a comprehensive entertainment system that includes real-time information provision and emotion analysis is needed.

[2143] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an information collection means, an analysis means, a notification means, an emotion analysis means, an in-vehicle entertainment system, and a real-time information provision means. This enables a user in an autonomous vehicle to obtain the latest information about their fa...

Claims

1. Information gathering means; Analysis means; Notification means; Purchasing assistance measures, generating means; Strategy formulation tools; A system including:

2. 2. The system according to claim 1, wherein the information gathering means is means for gathering the latest information on a specific subject from public databases, news sites, social networking services, and official websites on the Internet.

3. 2. The system according to claim 1, wherein the analyzing means is a means for evaluating importance and relevance based on the collected information and performing filtering.

4. The system according to claim 1 , wherein the notification means is a means for providing the filtered information to the user terminal by push notification or email.

5. 2. The system according to claim 1, wherein the purchasing support means is means for recommending related items based on the user's past purchasing history.

6. 2. The system of claim 1, wherein the generating means is a means for generating original content based on a specific subject style.

7. 2. The system according to claim 1, wherein the strategy formulation means is means for providing an optimal ticket purchasing strategy based on event information related to a specific target.

8. 2. The system according to claim 1, wherein the generating means is a means for analyzing musical characteristics of a specific object and supporting the creation of an original song.

9. 2. The system according to claim 1, wherein the analysis means is a means for analyzing performance data of a specific target and evaluating the trend thereof.

10. 2. The system according to claim 1, wherein the notification means is means for tracking real-time activity of a specific target and notifying the user terminal.

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