System

Abstract

A system is provided.SOLUTION: A system including web crawling means for collecting information related to specific keywords and competitor names from a web site, natural language processing means for analyzing the collected text data and extracting specific information such as new product releases and executive personnel changes, social media monitoring means for collecting competitor posts and follower count information from a social media platform, news alert means for receiving alerts when a news article or press release related to a competitor is published, and artificial intelligence chatbot means for collecting competitive information through user interaction.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] For companies to gain an advantage in market competition, it is important to quickly and accurately grasp the trends of their competitors and develop appropriate strategies based on that information. However, traditional methods require a great deal of time and effort to collect and analyze information, making it difficult to respond in real time. This can result in companies missing important trends of their competitors and being unable to develop appropriate strategies in a timely manner, resulting in a lack of competitiveness. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means: The present invention provides a system including: a web crawling means for collecting information related to specific keywords and competitor names from websites; a natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes; a social media monitoring means for collecting information on competitors' posts and follower numbers from social media platforms; a news alert means for receiving alerts when news articles or press releases related to competitors are issued; and an artificial intelligence chatbot means for collecting competitive information through user dialogue. This system enables companies to efficiently collect and analyze competitive information and use it in real time for strategy planning and product development.

[0006] "Web crawling methods" refer to technologies that automatically crawl websites on the Internet and collect information related to specific keywords or competitor names.

[0007] "Natural language processing means" refers to computer technology that analyzes collected text data and extracts specific information, such as new product announcements or executive personnel changes.

[0008] "Social media monitoring methods" refers to technologies used to collect and analyze information about competitors' posts and follower numbers from social media platforms.

[0009] "News Alert Tool" refers to a function that allows you to receive real-time alerts when news articles or press releases related to competitors are issued.

[0010] "Artificial intelligence chatbot means" refers to AI technology that collects competitive information through dialogue with users and provides relevant information in real time.

[0011] "Control Measures" refers to the technology that manages the entire system to integrate and operate the following measures: web crawling, natural language processing, social media monitoring, news alerts, and artificial intelligence chatbots based on keywords and competitor names set by users. [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] To implement the present invention, the following system configuration and program processing are required.

[0034] System Configuration

[0035] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, sends alerts, and manages the database. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set conflict information and check the results.

[0036] Program processing (natural language explanation)

[0037] 1. User Input

[0038] The user logs in to the system using a terminal and registers the names of competitors and related keywords on the management screen, completing the basic setup for collecting competitor information.

[0039] 2. Performing web crawling

[0040] The server periodically visits websites on the Internet to collect information related to registered keywords and competitor names, and the collected information is temporarily stored on the server.

[0041] 3. Natural Language Processing (NLP)

[0042] The server uses a natural language processing engine to analyze the text data collected by web crawling, and extracts useful competitive information (e.g., new product announcements, executive personnel changes, etc.). The extracted data is stored in a database.

[0043] 4. Social Media Monitoring

[0044] The server uses social media APIs to periodically collect and analyze information such as competitors' latest posts and follower counts. The analyzed data is also stored in a database.

[0045] 5. News Alerts

[0046] The server monitors the specified news feeds and generates alerts to notify the user when new news or press releases about competitors are published.

[0047] 6. Artificial Intelligence Chatbots

[0048] The server responds to user questions using a chatbot engine. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information.

[0049] Specific processing examples

[0050] For example, suppose a user wants to collect competitive information about a company called "ExampleCorp" and registers "ExampleCorp, new product, director personnel changes" as keywords in the system. In this case, the server operates as follows:

[0051] 1. The user enters a keyword from the device and sends it to the server.

[0052] 2. The server performs web crawling based on the registered keywords.

[0053] 3. The data collected by the server is analyzed using a natural language processing engine to extract relevant competitive information.

[0054] 4. The server collects and analyzes relevant information from the social media platform.

[0055] 5. The server monitors news feeds about competitors and generates alerts when new information is published.

[0056] 6. The user asks the chatbot, "Tell me about ExampleCorp's new product," and the server provides the appropriate information.

[0057] In this way, the system of the present invention can collect and analyze competitive information in real time and provide it to users.

[0058] The processing flow will be explained below.

[0059] Step 1:

[0060] A user logs into the system using a terminal, enters their authentication information (username and password), and if authentication is successful, accesses the main dashboard.

[0061] Step 2:

[0062] The user navigates to the admin page, selects the "Competitor Settings" option, enters the competitor name (e.g., ExampleCorp) and related keywords (e.g., new product, director personnel changes), and saves.

[0063] Step 3:

[0064] The device sends the entered competitor name and keywords to the server, which stores them in a database.

[0065] Step 4:

[0066] The server periodically launches the web crawling scheduler, which runs the web crawling tool at the specified interval (e.g., every 6 hours every day).

[0067] Step 5:

[0068] The server loads the list of websites to be collected and uses a web crawler to visit each site, retrieving text data from pages that match the specified competitor name or keywords.

[0069] Step 6:

[0070] The server temporarily stores the collected text data and launches a natural language processing engine to analyze the text and extract specific information (e.g., new product announcements, executive personnel changes).

[0071] Step 7:

[0072] The server stores the analysis results in a database, where they are organized and saved for later reference by the user.

[0073] Step 8:

[0074] The server uses social media APIs to monitor competitors' social media accounts, periodically collecting data on their latest posts and follower counts.

[0075] Step 9:

[0076] The server analyzes the collected social media data, extracts relevant information (e.g., marketing campaign responses, user comments) and stores it in a database.

[0077] Step 10:

[0078] The server monitors the specified news feed URL for new news articles and press releases related to competitors, and generates an alert when relevant information is published.

[0079] Step 11:

[0080] The server notifies the user of the generated alerts. The notifications are delivered to the user via email or internal system notifications.

[0081] Step 12:

[0082] A user launches the chatbot from a terminal and types a question about competitive information, such as "Tell me about ExampleCorp's new product."

[0083] Step 13:

[0084] The device sends the user's question to the server, which analyzes the question using a natural language processing engine and searches for related information in a database.

[0085] Step 14:

[0086] The server passes the search results to the chatbot, which generates an appropriate answer to the question, which is then sent to the device and displayed to the user.

[0087] Step 15:

[0088] The user selects the "Display Competitive Information Results" option from the administration screen. The device retrieves the latest analysis results from the server and displays them in a visualized format for the user.

[0089] Step 16:

[0090] The user can select the option to generate and download a competitive intelligence report if desired. The device will generate the report and provide a download link, such as in PDF format.

[0091] In this way, the system of the present invention quickly and efficiently collects and analyzes information on competitors through a series of processes and provides it to users.

[0092] Example 1

[0093] 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."

[0094] Collecting competitive information effectively and in real time is extremely important for understanding a company's marketing strategy and market trends. However, when information is collected manually, it takes a huge amount of time and effort, and analyzing the collected information is not easy. Furthermore, it is difficult to integrate multiple functions such as web crawling, social media monitoring, news alerts, and chatbots. This makes it difficult to understand competitor trends in a timely manner.

[0095] 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.

[0096] In this invention, the server includes an input means for a user to register specific keywords and competitor names using a terminal, a web crawling means for collecting information related to the specific keywords and competitor names from websites, a natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes, a social media monitoring means for collecting information on competitors' posts and follower numbers from social media platforms, a news alert means for generating alerts when news articles or press releases related to competitors are issued, and an AI chatbot means for providing competitor information through dialogue with users. This makes it possible to effectively collect, analyze, and comprehensively manage competitor information in real time.

[0097] "Input means" is a function that allows a user to register specific keywords and competitor names in the system using a terminal.

[0098] "Web crawling means" is a function that allows a server to crawl websites on the Internet and automatically collect information related to specific keywords and competitor names.

[0099] "Natural language processing means" is a function that analyzes collected text data and extracts specific information such as new product announcements and executive personnel changes. Specifically, it analyzes text using a natural language processing engine.

[0100] "Social media monitoring tools" are functions that collect and analyze information on competitors' posts and follower numbers from social media platforms.

[0101] The "news alert means" is a function that generates an alert and notifies the user when a news article or press release related to a competitor is issued.

[0102] The "artificial intelligence chatbot means" is a function that provides competitive information through dialogue with users. Specifically, it uses a chatbot engine to respond to user questions.

[0103] "Control Measures" refers to a function that integrates and operates web crawling, natural language processing, social media monitoring, news alerts, and AI chatbot functions based on keywords and competitor names set by the user.

[0104] MODE FOR CARRYING OUT THE INVENTION

[0105] To implement the present invention, the following system configuration and program processing are required.

[0106] System Configuration

[0107] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, generates alerts, and manages the database. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set conflict information and check the results.

[0108] Program processing (natural language explanation)

[0109] 1. User Input

[0110] A user logs in to the system using a terminal and registers competitor names and related keywords on the management screen. This operation includes entering keywords in a text field and clicking the "Register" button.

[0111] 2. Performing web crawling

[0112] The server launches a web crawling tool (e.g., Selenium or Scrapy) to collect information related to the registered keywords and competitor names from websites on the Internet. This data is temporarily stored in the server's storage. Specifically, the server searches for URLs that match the keywords and parses the HTML of those web pages to extract text data.

[0113] 3. Natural Language Processing (NLP)

[0114] The server passes the collected text data to a natural language processing engine (e.g., spaCy or NLTK) for analysis. The natural language processing engine tokenizes the text data and extracts important entities (e.g., company names, new product names, executive names, etc.). The extracted information is stored in a database. The server then divides the text data into sentences and performs entity identification for each sentence.

[0115] 4. Social Media Monitoring

[0116] The server prepares a social media API client (e.g., Twitter API client) and periodically calls the API to collect competitors' posts. The collected posts are analyzed, and important data (e.g., increases or decreases in the number of followers, rumors about new products, etc.) is extracted and stored in a database. The server parses the JSON-formatted data received from the API and extracts the necessary information.

[0117] 5. News Alerts

[0118] The server uses a news API (e.g., Google News API) to monitor news feeds and generates alerts when new news or press releases related to competitors are published. The generated alerts are notified to the user. Specifically, the server sets up regular checks of the feed and generates alerts when new entries are found.

[0119] 6. Artificial Intelligence Chatbots

[0120] The server launches a chatbot engine (e.g., ChatGPT or Dialogflow) and provides an interface for accepting user questions. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information. For example, if a user inputs "Tell me about ExampleCorp's new product," the server analyzes the question, retrieves information about the new product from the database, and responds.

[0121] Specific examples

[0122] For example, if a user wants to collect information about a certain company, he or she registers keywords such as "certain company, new product, executive personnel changes" in the system. In this case, the server operates as follows:

[0123] 1. The user enters a keyword from the device and sends it to the server.

[0124] 2. The server performs web crawling using Selenium based on the registered keywords.

[0125] 3. The data collected by the server is analyzed using spaCy to extract relevant competitive information.

[0126] 4. The server collects and analyzes relevant information from the Twitter API.

[0127] 5. The server monitors the news feed via the Google News API and generates an alert when new information is published.

[0128] 6. The user asks the chatbot, "Please tell me about a new product from a certain company," and the server provides the appropriate information.

[0129] In this way, the system of the present invention can collect and analyze competitive information in real time and provide it to users.

[0130] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0131] Step 1:

[0132] A user logs into the system using a terminal and registers the name of a competitor and related keywords on the management screen. The input for this operation is the "competitor name" and "keywords" entered by the user in the text field on the terminal. The output is this information sent to the server. Specifically, the user enters the keywords in the text field on the management screen and clicks the "Register" button.

[0133] Step 2:

[0134] The server performs web crawling based on registered keywords and competitor names. The input for this process is the "keywords" and "competitor names" registered by the user, and the output is the collected text data of websites. The server uses Selenium or Scrapy to automatically crawl related web pages on the Internet, parse the HTML data, and extract the text data.

[0135] Step 3:

[0136] The server passes the collected text data to a natural language processing engine for analysis. The input to this process is the "text data" collected in step 2, and the output is "extracted specific information (e.g., new product announcements, executive personnel changes, etc.)." Specifically, the server inputs the collected text data into spaCy or NLTK, which tokenizes the data and performs entity identification processing. Then, important information is extracted and stored in a database.

[0137] Step 4:

[0138] The server uses social media APIs to collect competitors' posts and follower counts. The inputs for this process are "competitor names" and "API clients," and the output is "collected social media data." The server periodically calls the Twitter API and Facebook API to receive relevant post and follower count data in JSON format. The server then analyzes the data and stores important information in a database.

[0139] Step 5:

[0140] The server monitors the news feed and generates alerts. The inputs for this process are the "news feed URL" and "keywords," and the output is an "alert notification." The server periodically checks for news articles and press releases related to the registered keywords using the Google News API, etc., and generates an alert to notify the user when new information is released.

[0141] Step 6:

[0142] When a user inputs a question to a chatbot using a terminal, the server provides appropriate information in response to the question. The input for this process is the user's "question" and the output is the "response." The server analyzes the question using a chatbot engine (e.g., ChatGPT or Dialogflow), searches for relevant information from a database, and generates a response. Specifically, if a user asks, "Please tell me about a new product from a certain company," the server retrieves information about the new product from the database and presents the answer through the chatbot.

[0143] (Application example 1)

[0144] 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."

[0145] Conventional competitive intelligence analysis systems only handle information such as competitor product announcements and executive personnel changes, and lack the functionality to collect and analyze information related to security risks, making it difficult for companies to respond quickly to security risks.

[0146] 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.

[0147] In this invention, the server includes a web crawling means for collecting information related to specific keywords and competitor names from websites, a natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes, a social media monitoring means for collecting information on competitors' posts and follower numbers from social media platforms, a news alert means for receiving alerts when news articles or press releases related to competitors are issued, an AI chatbot means for collecting competitor information through dialogue with users, and a cybersecurity monitoring means for collecting and analyzing information related to security risks. This enables the collection and analysis of not only information about competitors but also information about security risks, enabling companies to respond to security risks quickly and effectively.

[0148] "Web crawling" is a technique for automatically visiting websites on the Internet and collecting specific information.

[0149] "Natural language processing" is a technology that allows computers to understand and analyze human language and is used to extract specific information.

[0150] "Social media monitoring" is a technology that collects and analyzes information such as posts and follower numbers on social media platforms.

[0151] "News Alert" is a function that notifies users of the contents of specific news articles or press releases when they are published.

[0152] An "artificial intelligence chatbot" is software based on artificial intelligence that collects and provides information through dialogue with users.

[0153] "Information related to security risks" refers to information that may affect information security, such as cyber attacks, vulnerabilities, and phishing attacks.

[0154] "Cybersecurity monitoring" is a technology that collects and analyzes information on security risks related to specific keywords.

[0155] To implement the present invention, the following system configuration and program processing are required.

[0156] System Configuration

[0157] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, sends alerts, and manages the database. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set conflict information and check the results.

[0158] Hardware and software used

[0159] Server: Cloud-based server (e.g. AWS EC2)

[0160] Smartphone: iOS or Android device (app developed with React Native)

[0161] Database: PostgreSQL

[0162] Web crawler: Scrapy

[0163] Natural Language Processing (NLP): spaCy, NLTK

[0164] Social Media APIs: Twitter API, Facebook Graph API

[0165] Chatbot engine: Rasa

[0166] Program processing (natural language explanation)

[0167] server

[0168] The server receives the user's input and executes the following steps:

[0169] 1. Web crawling methods:

[0170] The server uses Scrapy to crawl websites related to registered keywords and competitor names and collect information.

[0171] The collected data is temporarily stored on the server.

[0172] 2. Natural Language Processing Tools:

[0173] The collected text data is analyzed using spaCy and NLTK to extract specific information such as new product announcements and executive personnel changes.

[0174] 3. Social Media Monitoring Methods:

[0175] The server uses the Twitter API and Facebook Graph API to periodically collect and analyze competitors' posts and follower counts.

[0176] 4. News Alert Methods:

[0177] Generate alerts to notify users when news articles or press releases related to competitors are published.

[0178] 5. Artificial Intelligence Chatbot Means:

[0179] Using Rasa, we collect competitive information and provide answers based on user questions.

[0180] 6. Cybersecurity Monitoring Measures:

[0181] It collects and analyzes security risk information related to specific keywords. For example, the server periodically checks for information about phishing attacks and malware and reports it to the user.

[0182] Terminal

[0183] The terminal acts as a user interface and provides the following functions:

[0184] Enter keywords and competitor names

[0185] Viewing analysis results and reports

[0186] Security risk alert notifications

[0187] User

[0188] The user operates the terminal and performs the following operations.

[0189] Registering keywords and competitor names

[0190] Checking the analysis results

[0191] Use the chatbot to ask for more information

[0192] Examples of concrete examples and prompts

[0193] As a concrete example, if a user sets the keywords "new product release phishing attack", the server operates as follows:

[0194] 1. Web crawling: When a specific company announces a new product release, we collect information about related phishing attacks.

[0195] 2. Natural Language Processing: Analyzes collected data and extracts useful information.

[0196] 3. Social media monitoring: Analyze the company's new product posts and related security risks.

[0197] 4. News Alerts: Notify users if a security risk related to a new release is detected.

[0198] 5. Chatbot: Type "What are the security risks of a new product release?" and get real-time details.

[0199] Example prompt sentence:

[0200] "What are the latest phishing attacks related to new product releases?"

[0201] "Show me the analysis results for a specific company's new product releases."

[0202] In this way, the system of the present invention can collect and analyze competitive information and security risks in real time and provide them to users.

[0203] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0204] Step 1:

[0205] The user operates the terminal, inputs and registers specific keywords and competitor names, and the input information is sent to the server. For example, if a user registers keywords such as "new product release phishing attack," this is sent to the server.

[0206] Step 2:

[0207] The server performs web crawling based on the registered keywords and competitor names. Specifically, the server uses Scrapy to crawl specific websites and collect relevant information. The input is the keywords and competitor names, and the output is the collected web data.

[0208] Step 3:

[0209] The server analyzes the collected web data using a natural language processing (NLP) engine. Specifically, the server uses spaCy or NLTK to analyze the text data and extract specific information, such as new product announcements or executive personnel changes. The input is the collected web data, and the output is the data from which the specific information has been extracted.

[0210] Step 4:

[0211] The server monitors the social media activities of competitors. Specifically, the server uses the Twitter API and Facebook Graph API to collect and analyze competitors' posts and follower counts. The input is social media account information, and the output is analyzed social media activity data.

[0212] Step 5:

[0213] The server monitors news articles and press releases related to competitors and generates alerts. When new news related to a specific keyword is published, the server generates an alert and notifies the user. The input is the news feed information and the output is the generated alert.

[0214] Step 6:

[0215] The server performs security risk analysis based on the collected information. Specifically, the server uses its cybersecurity monitoring function to periodically check for information about phishing attacks and malware and provide it to the user. The input is data related to competitors and security risks, and the output is a report on security risks.

[0216] Step 7:

[0217] A user can use the chatbot to request information from their device. For example, if the user types, "Please tell me the latest phishing attack information regarding new product releases," the server uses Rasa to search the relevant database and provide the appropriate information. The input is the user's query, and the output is the corresponding response.

[0218] In this way, the present invention realizes a system that collects and analyzes information step by step and provides the user with necessary competitive information and security risk information.

[0219] 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.

[0220] The present invention is a system that allows companies to quickly and efficiently collect and analyze information on their competitors and use it to formulate their own strategies and develop products. The present invention includes web crawling means, natural language processing means, social media monitoring means, news alert means, and artificial intelligence chatbot means, as well as an emotion recognition engine that recognizes user emotions. Specific embodiments of the present invention and the processing of the program are described below.

[0221] System Configuration

[0222] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, generates alerts, manages the database, and recognizes emotions. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set competitive information, check the results, and interact with the chatbot.

[0223] Program processing (natural language explanation)

[0224] 1. User Input

[0225] The user logs in to the system using a terminal and registers the names of competitors and related keywords on the management screen, completing the basic setup for collecting competitor information.

[0226] 2. Performing web crawling

[0227] The server periodically visits websites on the Internet to collect information related to registered keywords and competitor names, and the collected information is temporarily stored on the server.

[0228] 3. Natural Language Processing (NLP)

[0229] The server uses a natural language processing engine to analyze the text data collected by web crawling, and extracts useful competitive information (e.g., new product announcements, executive personnel changes, etc.). The extracted data is stored in a database.

[0230] 4. Social Media Monitoring

[0231] The server uses social media APIs to periodically collect and analyze information such as competitors' latest posts and follower counts. The analyzed data is also stored in a database.

[0232] 5. News Alerts

[0233] The server monitors the specified news feed URL and generates alerts when new news or press releases related to competitors are published, and notifies the user of the alerts.

[0234] 6. Artificial Intelligence Chatbots

[0235] The server responds to user questions using a chatbot engine. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information.

[0236] 7. Emotion Recognition Engine

[0237] The server uses an emotion recognition engine to recognize emotions from the user's dialogue and behavior. The emotion data is stored in a database and the system's behavior is adjusted based on the user's emotions.

[0238] Specific processing examples

[0239] For example, if a user wants to collect competitive information about a company called "ExampleCorp" and registers "ExampleCorp, new product, director personnel changes" as keywords in the system, the server operates as follows.

[0240] 1. The user enters a keyword from the device and sends it to the server.

[0241] 2. The server performs web crawling based on the registered keywords.

[0242] 3. The data collected by the server is analyzed using a natural language processing engine to extract relevant competitive information.

[0243] 4. The server collects and analyzes relevant information from the social media platform.

[0244] 5. The server monitors news feeds about competitors and generates alerts when new information is published.

[0245] 6. The user asks the chatbot, "Tell me about ExampleCorp's new product," and the server provides the appropriate information.

[0246] 7. The server recognizes emotions from the user's questions and actions to the chatbot and adjusts the response content based on the emotional data.

[0247] The system of the present invention not only efficiently collects and analyzes competitive information, but also, by combining it with an emotion recognition engine, is able to flexibly respond to the user's emotions, thereby contributing to an improved user experience.

[0248] The processing flow will be explained below.

[0249] Step 1:

[0250] A user logs into the system using a terminal, enters their authentication information (username and password), and if authentication is successful, accesses the main dashboard.

[0251] Step 2:

[0252] The user navigates to the admin page, selects the "Competitor Settings" option, enters the competitor name (e.g., ExampleCorp) and related keywords (e.g., new product, director personnel changes), and saves.

[0253] Step 3:

[0254] The device sends the entered competitor name and keywords to the server, which stores them in a database.

[0255] Step 4:

[0256] The server periodically launches the web crawling scheduler, which runs the web crawling tool at the specified interval (e.g., every 6 hours every day).

[0257] Step 5:

[0258] The server loads the list of websites to be collected and uses a web crawler to visit each site, retrieving text data from pages that match the specified competitor name or keywords.

[0259] Step 6:

[0260] The server temporarily stores the collected text data and launches a natural language processing engine to analyze the text and extract specific information (e.g., new product announcements, executive personnel changes).

[0261] Step 7:

[0262] The server stores the analysis results in a database, where they are organized and saved for later reference by the user.

[0263] Step 8:

[0264] The server uses social media APIs to monitor competitors' social media accounts, periodically collecting data on their latest posts and follower counts.

[0265] Step 9:

[0266] The server analyzes the collected social media data, extracts relevant information (e.g., marketing campaign responses, user comments) and stores it in a database.

[0267] Step 10:

[0268] The server monitors the specified news feed URL for new news articles and press releases related to competitors, and generates an alert when relevant information is published.

[0269] Step 11:

[0270] The server notifies the user of the generated alerts. The notifications are delivered to the user via email or internal system notifications.

[0271] Step 12:

[0272] A user launches the chatbot from a terminal and types a question about competitive information, such as "Tell me about ExampleCorp's new product."

[0273] Step 13:

[0274] The device sends the user's question to the server, which analyzes the question using a natural language processing engine and searches for related information in a database.

[0275] Step 14:

[0276] The server passes the search results to the chatbot, which generates an appropriate answer to the question, which is then sent to the device and displayed to the user.

[0277] Step 15:

[0278] The server activates an emotion recognition engine to determine the user's emotions through user questions and dialogue, and the emotion data is stored in a database.

[0279] Step 16:

[0280] The server takes into account the user's emotional data and adjusts the chatbot's responses, for example, providing more detailed information or offering assistance if the user expresses dissatisfaction.

[0281] Step 17:

[0282] The user selects the "Display Competitive Information Results" option from the administration screen. The device retrieves the latest analysis results from the server and displays them in a visualized format for the user.

[0283] Step 18:

[0284] The user can select the option to generate and download a competitive intelligence report if desired. The device will generate the report and provide a download link, such as in PDF format.

[0285] In this way, the system of the present invention quickly and efficiently collects and analyzes information on competitors through a series of processes and provides it to users.

[0286] Example 2

[0287] 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."

[0288] It is extremely important for companies to quickly and efficiently collect and analyze information about their competitors and use it to formulate their own strategies and develop products. However, current methods require time to collect and analyze information, making it difficult to make quick decisions. Furthermore, the collected information contains a lot of noise, making it difficult to extract useful information. Furthermore, there is a need for flexible systems that respond based on user sentiment, but current systems are unable to do so. The purpose of this invention is to solve these problems and enable companies to efficiently collect and analyze competitive information and make quick decisions.

[0289] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: information collection means for collecting information related to specific keywords and competitor names from websites; natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes; social media analysis means for collecting information on competitor posts and follower counts from social media platforms; notification means for generating alerts and notifying users when news articles or press releases related to competitors are published; interactive agent means for providing competitive information through dialogue with the user; and emotion recognition means for recognizing user emotions and adjusting system operation. This enables companies to efficiently collect and analyze competitive information and make quick decisions. Furthermore, flexible responses based on user emotions can also be realized.

[0290] "Information Gathering Tools" are tools or software used to automatically gather information related to specific keywords and competitor names from websites.

[0291] "Natural language processing means" refers to the technology and software used to analyze collected text data and extract useful information.

[0292] "Social media analytics tools" refer to technologies and software used to collect and analyze competitors' posts and follower numbers from social media platforms.

[0293] "Notification means" refers to a system or function that generates an alert and notifies users when a news article or press release related to a competitor is issued.

[0294] "Interactive agent means" refers to chatbot technology that uses artificial intelligence to provide competitive information through dialogue with users.

[0295] "Emotion recognition means" refers to the technology and software for recognizing emotions from user interactions and operations and adjusting the system's behavior.

[0296] This invention is a system that allows companies to quickly and efficiently collect and analyze information on their competitors and use it to formulate their own strategies and develop products. The system mainly consists of a server, a terminal, and a user. The server collects information, analyzes it, generates notifications, manages the database, and recognizes emotions, while the terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set competitive information, check the results, and interact with the chatbot.

[0297] Hardware and software used

[0298] server

[0299] 1. Information collection method: The server uses a web crawling tool such as "Scrapy" to automatically crawl websites on the Internet and collect information related to specific keywords and competitor names. The collected data is temporarily stored in a database such as "MongoDB."

[0300] 2. Natural language processing: The server uses tools like "spaCy" and "NLTK" to analyze the collected text data and extract useful information, such as "new product announcements" and "executive personnel changes," and stores this information in a database.

[0301] 3. Social media analysis: The server uses the Twitter API and Facebook Graph API to periodically collect and analyze information such as competitors' latest posts and follower numbers. The analyzed data is stored in a database.

[0302] 4. Notification Method: The server uses the Google News API and RSS feeds to monitor news articles and press releases related to competitors, and when new information is released, it generates an alert and notifies the user's device.

[0303] 5. Conversational Agent: The server uses chatbot engines such as Dialogflow and Rasa to respond to user questions. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information.

[0304] 6. Emotion Recognition: The server uses emotion recognition engines such as IBM Watson Tone Analyzer and Microsoft Azure Emotion API to recognize emotions from the user's interactions and actions. The recognized emotion data is stored in a database and the system's behavior is adjusted based on the user's emotions.

[0305] Terminal

[0306] 1. Accepting user input: The terminal provides an interface for accepting input from the user. For example, the user can register competitor names and related keywords on the management screen on the browser.

[0307] 2. Displaying Results: The device displays the analyzed data and alerts to the user, including the collected competitive information and analysis results.

[0308] 3. Report generation: The terminal generates a report based on the collected and analyzed data and provides it to the user.

[0309] Examples of concrete examples and prompts

[0310] For example, if a user wants to collect the latest information about "Competitor A," they can input keywords such as "new product announcement" and "management change" into the system. The server then performs web crawling, analyzes the collected data using a natural language processing engine, and extracts useful information. Using social media analysis tools, the server collects and analyzes "Competitor A's" latest posts and changes in the number of followers. It also monitors news articles and press releases related to "Competitor A" and notifies the user when new information is released. Furthermore, the user can use a chatbot to input questions such as "Tell me about Competitor A's new product," and the chatbot will search the database and provide relevant information. The server recognizes the user's emotions from their interactions and actions and adjusts the response accordingly.

[0311] Prompt Sentence Examples

[0312] "Collect the latest competitive information about competitor A."

[0313] "Please tell me about competitor A's new product."

[0314] "Check out competitor A's social media activity."

[0315] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0316] Step 1: User Input

[0317] The user logs into the system using a terminal and registers the name of the competitor and related keywords on the management screen. For example, they enter keywords such as "Competitor A," "New product announcement," and "Changes in management." When this input is sent to the server, the conditions for collecting competitive information are set and the basic setup is complete.

[0318] Input: Competitor name (Competitor A), related keywords (new product announcement, management changes)

[0319] Output: Basic setup for competitive intelligence gathering completed

[0320] Step 2: Perform a web crawl

[0321] The server uses Scrapy to crawl websites on the Internet based on set keywords. For example, it automatically collects blogs and news articles related to competitor A. The collected information is temporarily stored in MongoDB.

[0322] Input: Competitor name, related keywords

[0323] Output: Collected information (raw)

[0324] Step 3: Natural Language Processing (NLP)

[0325] The server uses "spaCy" or "NLTK" to analyze the collected text data and extract useful information. For example, specific information such as "Competitor A has announced a new product" or "The director has been transferred" is identified and stored in a database.

[0326] Input: Collected text data

[0327] Output: Extracted useful information (e.g., new product launches, executive personnel changes)

[0328] Step 4: Social Media Monitoring

[0329] The server uses the Twitter API and Facebook Graph API to periodically collect the latest posts and changes in the number of followers of competitor A. The collected data is analyzed, and specific information such as "Competitor A's new tweets" and "increased followers" is stored in a database.

[0330] Input: Competitor's social media account information

[0331] Output: Parsed social media data

[0332] Step 5: Generate a news alert

[0333] The server uses the Google News API and RSS feeds to monitor news articles and press releases related to competitor A. For example, if news comes out that competitor A has announced a new product, an alert is immediately generated and the user is notified.

[0334] Input: News feed URL

[0335] Output: Generated alert notification

[0336] Step 6: Artificial Intelligence Chatbots

[0337] A user accesses the chatbot using a device and inputs a question such as, "Please tell me about Competitor A's new product." The server uses Dialogflow to analyze the question, searches the database, and provides relevant information. It then returns a specific answer to the user, such as, "Competitor A has announced a new smartphone."

[0338] Input: User question

[0339] Output: Chatbot response

[0340] Step 7: Emotion Recognition

[0341] The server uses IBM Watson Tone Analyzer to recognize emotions from the user's dialogue and actions. For example, if the user is emotionally charged, the server adjusts the dialogue accordingly. This emotional data is stored in a database.

[0342] Input: User interaction content, operation information

[0343] Output: Emotion recognition results, adjusted dialogue content

[0344] (Application example 2)

[0345] 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."

[0346] Modern companies need to quickly and efficiently collect and analyze information about their competitors, but they lack the appropriate systems to do so. There is also a need for integrated support tools that enable store managers to collect and analyze competitive information and utilize it in store operations. Furthermore, there is a lack of systems that recognize user emotions and adjust interactions. There is a need to resolve these issues and support corporate strategy planning, product development, and efficient store operations.

[0347] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0348] In this invention, the server includes a web crawling means for collecting information related to specific keywords and competitor names from websites, a natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes, a social media monitoring means for collecting information on competitors' posts and follower numbers from social media platforms, a news alert means for receiving alerts when news articles or press releases related to competitors are issued, an AI chatbot means for collecting competitor information through dialogue with users, an emotion recognition means for recognizing user emotions and adjusting the content of the dialogue based on the emotions, and a smart store management means for allowing store managers to collect and analyze competitor information and use it in store operations. This enables companies to efficiently collect and analyze competitor information and effectively use it in store operations.

[0349] "Web crawling" is a technique for automatically collecting information from websites.

[0350] "Natural language processing" is a technology that uses computers to analyze, understand, and generate human language.

[0351] "Social media monitoring" is a technique for monitoring and collecting activity on social media.

[0352] "News Alert" is a technology that notifies you when news articles or press releases related to specified keywords are published.

[0353] An "artificial intelligence chatbot" is a system that provides and collects information through dialogue with users.

[0354] "Emotion recognition" is a technology that estimates and recognizes a user's emotions from their words, actions, and facial expressions.

[0355] "Smart Store Management" is an integrated support system that allows store managers to collect and analyze competitive information and utilize it in store operations.

[0356] This invention is a system that allows companies to quickly and efficiently collect and analyze information on their competitors and use it to formulate their own strategies and develop products. This system incorporates web crawling, natural language processing, social media monitoring, news alerts, AI chatbots, emotion recognition, and smart store management. We will explain the details of each method and how the entire system works.

[0357] Hardware and Software

[0358] The system consists of a server, user terminals, and a network. The hardware used includes regular desktop PCs, smartphones, and servers. The software uses the following technologies:

[0359] BeautifulSoup: Used to extract information from web pages.

[0360] SpaCy: Used for natural language processing.

[0361] Tweepy: Used to collect data from social media (Twitter).

[0362] Transformers (Hugging Face): Used for emotion recognition and chatbots.

[0363] NewsAPI: Used to collect news articles.

[0364] System Features

[0365] Web crawling

[0366] The server crawls websites based on registered keywords using BeautifulSoup and collects related information, which is then temporarily stored on the server in text format.

[0367] Natural Language Processing

[0368] The collected text data is analyzed on the server using SpaCy to extract useful information such as new product announcements and executive personnel changes, and the most relevant data is then stored in a database.

[0369] Social Media Monitoring

[0370] The server uses Tweepy to collect and analyze data on competitors' latest posts and follower numbers from social media APIs (such as Twitter), and the analysis data is stored in its own database.

[0371] News Alerts

[0372] The server uses the NewsAPI to alert users when news articles or press releases related to specific keywords are published, via email or in-app notifications.

[0373] Artificial Intelligence Chatbot

[0374] The server uses a chatbot engine based on Transformers to respond to user questions. For example, if a user asks, "Tell me about a new product from a competitor's company," the chatbot will search the database and provide relevant information.

[0375] emotion recognition

[0376] The server uses Transformers' emotion recognition engine to analyze emotions from user interactions, allowing it to tailor the chatbot's responses based on the user's emotional state.

[0377] Smart store management

[0378] Store managers can use this system to collect competitive information and develop store management strategies based on the analysis results, helping them maintain an advantage over their competitors.

[0379] Specific examples

[0380] For example, if a user asks "What is the latest information on a new product from a competitor's name?" the system will do the following:

[0381] Perform web crawling and collect relevant information.

[0382] Analyze and extract collected text data using natural language processing.

[0383] Collect the latest information on social media through social media monitoring.

[0384] News alerts detect new news articles and notify you accordingly.

[0385] An artificial intelligence chatbot responds to questions and provides relevant information from a database.

[0386] Emotion recognition generates responses based on the user's emotions.

[0387] Prompt Sentence Examples

[0388] "Please give me the latest information on new products from competitors' names."

[0389] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0390] Step 1:

[0391] A user logs into the system using a terminal and registers keywords such as "competitor company name, new product, executive personnel changes" on the administration screen.

[0392] Input: Keywords entered by the user on the device

[0393] Data processing: The server sets the basic settings for information collection based on this keyword.

[0394] Output: The set keywords are registered in the system.

[0395] Step 2:

[0396] The server periodically crawls websites on the Internet using BeautifulSoup and collects information related to registered keywords.

[0397] Input: Registered keyword

[0398] Data processing: Extracting text data from website HTML

[0399] Output: The collected text data is temporarily stored on the server.

[0400] Step 3:

[0401] The text data collected by the server is analyzed using SpaCy to extract useful information (e.g., new product announcements, executive personnel changes, etc.).

[0402] Input: Collected text data

[0403] Data processing: Extracting useful information through natural language processing

[0404] Output: The extracted information is registered in the database.

[0405] Step 4:

[0406] The server uses Tweepy to collect and analyze competitors' latest posts and follower counts from social media APIs.

[0407] Input: Registered keyword

[0408] Data processing: Analyzing data obtained from social media APIs

[0409] Output: The parsed information is registered in the database

[0410] Step 5:

[0411] The server uses the NewsAPI to monitor news articles and press releases related to competitors and generate alerts when new information is released.

[0412] Input: Specific keywords

[0413] Data processing: Monitor news feeds and generate notifications when new information is published.

[0414] Output: A notification is sent to the user's device

[0415] Step 6:

[0416] The user inputs a question to the chatbot through the terminal, such as "Please tell me about a new product from a competitor's company."

[0417] Input: User question (prompt)

[0418] Data processing: The server uses the chatbot engine to search the database and extract relevant information.

[0419] Output: The extracted information is provided to the user

[0420] Step 7:

[0421] The server uses Transformers to recognize emotions from the user's dialogue and adjust the dialogue content.

[0422] Input: User interaction

[0423] Data processing: Analyze emotions with an emotion recognition engine and tailor responses accordingly

[0424] Output: An appropriate response is generated according to the user's emotions.

[0425] Step 8:

[0426] Store managers use this system to collect and analyze competitive information and develop strategies for store operations.

[0427] Input: Collected and analyzed competitive information

[0428] Data processing: Formulate operational strategies based on results

[0429] Output: A new strategy for store operations is implemented.

[0430] The above processing steps enable business and store managers to quickly and efficiently collect and analyze competitive information and use it to develop appropriate business strategies.

[0431] 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.

[0432] 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.

[0433] 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.

[0434] [Second embodiment]

[0435] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0436] 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.

[0437] 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).

[0438] 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.

[0439] 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.

[0440] 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).

[0441] 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.

[0442] 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.

[0443] 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.

[0444] 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.

[0445] 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.

[0446] 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."

[0447] To implement the present invention, the following system configuration and program processing are required.

[0448] System Configuration

[0449] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, sends alerts, and manages the database. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set conflict information and check the results.

[0450] Program processing (natural language explanation)

[0451] 1. User Input

[0452] The user logs in to the system using a terminal and registers the names of competitors and related keywords on the management screen, completing the basic setup for collecting competitor information.

[0453] 2. Performing web crawling

[0454] The server periodically visits websites on the Internet to collect information related to registered keywords and competitor names, and the collected information is temporarily stored on the server.

[0455] 3. Natural Language Processing (NLP)

[0456] The server uses a natural language processing engine to analyze the text data collected by web crawling, and extracts useful competitive information (e.g., new product announcements, executive personnel changes, etc.). The extracted data is stored in a database.

[0457] 4. Social Media Monitoring

[0458] The server uses social media APIs to periodically collect and analyze information such as competitors' latest posts and follower counts. The analyzed data is also stored in a database.

[0459] 5. News Alerts

[0460] The server monitors the specified news feeds and generates alerts to notify the user when new news or press releases about competitors are published.

[0461] 6. Artificial Intelligence Chatbots

[0462] The server responds to user questions using a chatbot engine. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information.

[0463] Specific processing examples

[0464] For example, suppose a user wants to collect competitive information about a company called "ExampleCorp" and registers "ExampleCorp, new product, director personnel changes" as keywords in the system. In this case, the server operates as follows:

[0465] 1. The user enters a keyword from the device and sends it to the server.

[0466] 2. The server performs web crawling based on the registered keywords.

[0467] 3. The data collected by the server is analyzed using a natural language processing engine to extract relevant competitive information.

[0468] 4. The server collects and analyzes relevant information from the social media platform.

[0469] 5. The server monitors news feeds about competitors and generates alerts when new information is published.

[0470] 6. The user asks the chatbot, "Tell me about ExampleCorp's new product," and the server provides the appropriate information.

[0471] In this way, the system of the present invention can collect and analyze competitive information in real time and provide it to users.

[0472] The processing flow will be explained below.

[0473] Step 1:

[0474] A user logs into the system using a terminal, enters their authentication information (username and password), and if authentication is successful, accesses the main dashboard.

[0475] Step 2:

[0476] The user navigates to the admin page, selects the "Competitor Settings" option, enters the competitor name (e.g., ExampleCorp) and related keywords (e.g., new product, director personnel changes), and saves.

[0477] Step 3:

[0478] The device sends the entered competitor name and keywords to the server, which stores them in a database.

[0479] Step 4:

[0480] The server periodically launches the web crawling scheduler, which runs the web crawling tool at the specified interval (e.g., every 6 hours every day).

[0481] Step 5:

[0482] The server loads the list of websites to be collected and uses a web crawler to visit each site, retrieving text data from pages that match the specified competitor name or keywords.

[0483] Step 6:

[0484] The server temporarily stores the collected text data and launches a natural language processing engine to analyze the text and extract specific information (e.g., new product announcements, executive personnel changes).

[0485] Step 7:

[0486] The server stores the analysis results in a database, where they are organized and saved for later reference by the user.

[0487] Step 8:

[0488] The server uses social media APIs to monitor competitors' social media accounts, periodically collecting data on their latest posts and follower counts.

[0489] Step 9:

[0490] The server analyzes the collected social media data, extracts relevant information (e.g., marketing campaign responses, user comments) and stores it in a database.

[0491] Step 10:

[0492] The server monitors the specified news feed URL for new news articles and press releases related to competitors, and generates an alert when relevant information is published.

[0493] Step 11:

[0494] The server notifies the user of the generated alerts. The notifications are delivered to the user via email or internal system notifications.

[0495] Step 12:

[0496] A user launches the chatbot from a terminal and types a question about competitive information, such as "Tell me about ExampleCorp's new product."

[0497] Step 13:

[0498] The device sends the user's question to the server, which analyzes the question using a natural language processing engine and searches for related information in a database.

[0499] Step 14:

[0500] The server passes the search results to the chatbot, which generates an appropriate answer to the question, which is then sent to the device and displayed to the user.

[0501] Step 15:

[0502] The user selects the "Display Competitive Information Results" option from the administration screen. The device retrieves the latest analysis results from the server and displays them in a visualized format for the user.

[0503] Step 16:

[0504] The user can select the option to generate and download a competitive intelligence report if desired. The device will generate the report and provide a download link, such as in PDF format.

[0505] In this way, the system of the present invention quickly and efficiently collects and analyzes information on competitors through a series of processes and provides it to users.

[0506] Example 1

[0507] 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."

[0508] Collecting competitive information effectively and in real time is extremely important for understanding a company's marketing strategy and market trends. However, when information is collected manually, it takes a huge amount of time and effort, and analyzing the collected information is not easy. Furthermore, it is difficult to integrate multiple functions such as web crawling, social media monitoring, news alerts, and chatbots. This makes it difficult to understand competitor trends in a timely manner.

[0509] 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.

[0510] In this invention, the server includes an input means for a user to register specific keywords and competitor names using a terminal, a web crawling means for collecting information related to the specific keywords and competitor names from websites, a natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes, a social media monitoring means for collecting information on competitors' posts and follower numbers from social media platforms, a news alert means for generating alerts when news articles or press releases related to competitors are issued, and an AI chatbot means for providing competitor information through dialogue with users. This makes it possible to effectively collect, analyze, and comprehensively manage competitor information in real time.

[0511] "Input means" is a function that allows a user to register specific keywords and competitor names in the system using a terminal.

[0512] "Web crawling means" is a function that allows a server to crawl websites on the Internet and automatically collect information related to specific keywords and competitor names.

[0513] "Natural language processing means" is a function that analyzes collected text data and extracts specific information such as new product announcements and executive personnel changes. Specifically, it analyzes text using a natural language processing engine.

[0514] "Social media monitoring tools" are functions that collect and analyze information on competitors' posts and follower numbers from social media platforms.

[0515] The "news alert means" is a function that generates an alert and notifies the user when a news article or press release related to a competitor is issued.

[0516] The "artificial intelligence chatbot means" is a function that provides competitive information through dialogue with users. Specifically, it uses a chatbot engine to respond to user questions.

[0517] "Control Measures" refers to a function that integrates and operates web crawling, natural language processing, social media monitoring, news alerts, and AI chatbot functions based on keywords and competitor names set by the user.

[0518] MODE FOR CARRYING OUT THE INVENTION

[0519] To implement the present invention, the following system configuration and program processing are required.

[0520] System Configuration

[0521] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, generates alerts, and manages the database. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set conflict information and check the results.

[0522] Program processing (natural language explanation)

[0523] 1. User Input

[0524] A user logs in to the system using a terminal and registers competitor names and related keywords on the management screen. This operation includes entering keywords in a text field and clicking the "Register" button.

[0525] 2. Performing web crawling

[0526] The server launches a web crawling tool (e.g., Selenium or Scrapy) to collect information related to the registered keywords and competitor names from websites on the Internet. This data is temporarily stored in the server's storage. Specifically, the server searches for URLs that match the keywords and parses the HTML of those web pages to extract text data.

[0527] 3. Natural Language Processing (NLP)

[0528] The server passes the collected text data to a natural language processing engine (e.g., spaCy or NLTK) for analysis. The natural language processing engine tokenizes the text data and extracts important entities (e.g., company names, new product names, executive names, etc.). The extracted information is stored in a database. The server then divides the text data into sentences and performs entity identification for each sentence.

[0529] 4. Social Media Monitoring

[0530] The server prepares a social media API client (e.g., Twitter API client) and periodically calls the API to collect competitors' posts. The collected posts are analyzed, and important data (e.g., increases or decreases in the number of followers, rumors about new products, etc.) is extracted and stored in a database. The server parses the JSON-formatted data received from the API and extracts the necessary information.

[0531] 5. News Alerts

[0532] The server uses a news API (e.g., Google News API) to monitor news feeds and generates alerts when new news or press releases related to competitors are published. The generated alerts are notified to the user. Specifically, the server sets up regular checks of the feed and generates alerts when new entries are found.

[0533] 6. Artificial Intelligence Chatbots

[0534] The server launches a chatbot engine (e.g., ChatGPT or Dialogflow) and provides an interface for accepting user questions. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information. For example, if a user inputs "Tell me about ExampleCorp's new product," the server analyzes the question, retrieves information about the new product from the database, and responds.

[0535] Specific examples

[0536] For example, if a user wants to collect information about a certain company, he or she registers keywords such as "certain company, new product, executive personnel changes" in the system. In this case, the server operates as follows:

[0537] 1. The user enters a keyword from the device and sends it to the server.

[0538] 2. The server performs web crawling using Selenium based on the registered keywords.

[0539] 3. The data collected by the server is analyzed using spaCy to extract relevant competitive information.

[0540] 4. The server collects and analyzes relevant information from the Twitter API.

[0541] 5. The server monitors the news feed via the Google News API and generates an alert when new information is published.

[0542] 6. The user asks the chatbot, "Please tell me about a new product from a certain company," and the server provides the appropriate information.

[0543] In this way, the system of the present invention can collect and analyze competitive information in real time and provide it to users.

[0544] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0545] Step 1:

[0546] A user logs into the system using a terminal and registers the name of a competitor and related keywords on the management screen. The input for this operation is the "competitor name" and "keywords" entered by the user in the text field on the terminal. The output is this information sent to the server. Specifically, the user enters the keywords in the text field on the management screen and clicks the "Register" button.

[0547] Step 2:

[0548] The server performs web crawling based on registered keywords and competitor names. The input for this process is the "keywords" and "competitor names" registered by the user, and the output is the collected text data of websites. The server uses Selenium or Scrapy to automatically crawl related web pages on the Internet, parse the HTML data, and extract the text data.

[0549] Step 3:

[0550] The server passes the collected text data to a natural language processing engine for analysis. The input to this process is the "text data" collected in step 2, and the output is "extracted specific information (e.g., new product announcements, executive personnel changes, etc.)." Specifically, the server inputs the collected text data into spaCy or NLTK, which tokenizes the data and performs entity identification processing. Then, important information is extracted and stored in a database.

[0551] Step 4:

[0552] The server uses social media APIs to collect competitors' posts and follower counts. The inputs for this process are "competitor names" and "API clients," and the output is "collected social media data." The server periodically calls the Twitter API and Facebook API to receive relevant post and follower count data in JSON format. The server then analyzes the data and stores important information in a database.

[0553] Step 5:

[0554] The server monitors the news feed and generates alerts. The inputs for this process are the "news feed URL" and "keywords," and the output is an "alert notification." The server periodically checks for news articles and press releases related to the registered keywords using the Google News API, etc., and generates an alert to notify the user when new information is released.

[0555] Step 6:

[0556] When a user inputs a question to a chatbot using a terminal, the server provides appropriate information in response to the question. The input for this process is the user's "question" and the output is the "response." The server analyzes the question using a chatbot engine (e.g., ChatGPT or Dialogflow), searches for relevant information from a database, and generates a response. Specifically, if a user asks, "Please tell me about a new product from a certain company," the server retrieves information about the new product from the database and presents the answer through the chatbot.

[0557] (Application example 1)

[0558] 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."

[0559] Conventional competitive intelligence analysis systems only handle information such as competitor product announcements and executive personnel changes, and lack the functionality to collect and analyze information related to security risks, making it difficult for companies to respond quickly to security risks.

[0560] 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.

[0561] In this invention, the server includes a web crawling means for collecting information related to specific keywords and competitor names from websites, a natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes, a social media monitoring means for collecting information on competitors' posts and follower numbers from social media platforms, a news alert means for receiving alerts when news articles or press releases related to competitors are issued, an AI chatbot means for collecting competitor information through dialogue with users, and a cybersecurity monitoring means for collecting and analyzing information related to security risks. This enables the collection and analysis of not only information about competitors but also information about security risks, enabling companies to respond to security risks quickly and effectively.

[0562] "Web crawling" is a technique for automatically visiting websites on the Internet and collecting specific information.

[0563] "Natural language processing" is a technology that allows computers to understand and analyze human language and is used to extract specific information.

[0564] "Social media monitoring" is a technology that collects and analyzes information such as posts and follower numbers on social media platforms.

[0565] "News Alert" is a function that notifies users of the contents of specific news articles or press releases when they are published.

[0566] An "artificial intelligence chatbot" is software based on artificial intelligence that collects and provides information through dialogue with users.

[0567] "Information related to security risks" refers to information that may affect information security, such as cyber attacks, vulnerabilities, and phishing attacks.

[0568] "Cybersecurity monitoring" is a technology that collects and analyzes information on security risks related to specific keywords.

[0569] To implement the present invention, the following system configuration and program processing are required.

[0570] System Configuration

[0571] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, sends alerts, and manages the database. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set conflict information and check the results.

[0572] Hardware and software used

[0573] Server: Cloud-based server (e.g. AWS EC2)

[0574] Smartphone: iOS or Android device (app developed with React Native)

[0575] Database: PostgreSQL

[0576] Web crawler: Scrapy

[0577] Natural Language Processing (NLP): spaCy, NLTK

[0578] Social Media APIs: Twitter API, Facebook Graph API

[0579] Chatbot engine: Rasa

[0580] Program processing (natural language explanation)

[0581] server

[0582] The server receives the user's input and executes the following steps:

[0583] 1. Web crawling methods:

[0584] The server uses Scrapy to crawl websites related to registered keywords and competitor names and collect information.

[0585] The collected data is temporarily stored on the server.

[0586] 2. Natural Language Processing Tools:

[0587] The collected text data is analyzed using spaCy and NLTK to extract specific information such as new product announcements and executive personnel changes.

[0588] 3. Social Media Monitoring Methods:

[0589] The server uses the Twitter API and Facebook Graph API to periodically collect and analyze competitors' posts and follower counts.

[0590] 4. News Alert Methods:

[0591] Generate alerts to notify users when news articles or press releases related to competitors are published.

[0592] 5. Artificial Intelligence Chatbot Means:

[0593] Using Rasa, we collect competitive information and provide answers based on user questions.

[0594] 6. Cybersecurity Monitoring Measures:

[0595] It collects and analyzes security risk information related to specific keywords. For example, the server periodically checks for information about phishing attacks and malware and reports it to the user.

[0596] Terminal

[0597] The terminal acts as a user interface and provides the following functions:

[0598] Enter keywords and competitor names

[0599] Viewing analysis results and reports

[0600] Security risk alert notifications

[0601] User

[0602] The user operates the terminal and performs the following operations.

[0603] Registering keywords and competitor names

[0604] Checking the analysis results

[0605] Use the chatbot to ask for more information

[0606] Examples of concrete examples and prompts

[0607] As a concrete example, if a user sets the keywords "new product release phishing attack", the server operates as follows:

[0608] 1. Web crawling: When a specific company announces a new product release, we collect information about related phishing attacks.

[0609] 2. Natural Language Processing: Analyzes collected data and extracts useful information.

[0610] 3. Social media monitoring: Analyze the company's new product posts and related security risks.

[0611] 4. News Alerts: Notify users if a security risk related to a new release is detected.

[0612] 5. Chatbot: Type "What are the security risks of a new product release?" and get real-time details.

[0613] Example prompt sentence:

[0614] "What are the latest phishing attacks related to new product releases?"

[0615] "Show me the analysis results for a specific company's new product releases."

[0616] In this way, the system of the present invention can collect and analyze competitive information and security risks in real time and provide them to users.

[0617] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0618] Step 1:

[0619] The user operates the terminal, inputs and registers specific keywords and competitor names, and the input information is sent to the server. For example, if a user registers keywords such as "new product release phishing attack," this is sent to the server.

[0620] Step 2:

[0621] The server performs web crawling based on the registered keywords and competitor names. Specifically, the server uses Scrapy to crawl specific websites and collect relevant information. The input is the keywords and competitor names, and the output is the collected web data.

[0622] Step 3:

[0623] The server analyzes the collected web data using a natural language processing (NLP) engine. Specifically, the server uses spaCy or NLTK to analyze the text data and extract specific information, such as new product announcements or executive personnel changes. The input is the collected web data, and the output is the data from which the specific information has been extracted.

[0624] Step 4:

[0625] The server monitors the social media activities of competitors. Specifically, the server uses the Twitter API and Facebook Graph API to collect and analyze competitors' posts and follower counts. The input is social media account information, and the output is analyzed social media activity data.

[0626] Step 5:

[0627] The server monitors news articles and press releases related to competitors and generates alerts. When new news related to a specific keyword is published, the server generates an alert and notifies the user. The input is the news feed information and the output is the generated alert.

[0628] Step 6:

[0629] The server performs security risk analysis based on the collected information. Specifically, the server uses its cybersecurity monitoring function to periodically check for information about phishing attacks and malware and provide it to the user. The input is data related to competitors and security risks, and the output is a report on security risks.

[0630] Step 7:

[0631] A user can use the chatbot to request information from their device. For example, if the user types, "Please tell me the latest phishing attack information regarding new product releases," the server uses Rasa to search the relevant database and provide the appropriate information. The input is the user's query, and the output is the corresponding response.

[0632] In this way, the present invention realizes a system that collects and analyzes information step by step and provides the user with necessary competitive information and security risk information.

[0633] 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.

[0634] The present invention is a system that allows companies to quickly and efficiently collect and analyze information on their competitors and use it to formulate their own strategies and develop products. The present invention includes web crawling means, natural language processing means, social media monitoring means, news alert means, and artificial intelligence chatbot means, as well as an emotion recognition engine that recognizes user emotions. Specific embodiments of the present invention and the processing of the program are described below.

[0635] System Configuration

[0636] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, generates alerts, manages the database, and recognizes emotions. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set competitive information, check the results, and interact with the chatbot.

[0637] Program processing (natural language explanation)

[0638] 1. User Input

[0639] The user logs in to the system using a terminal and registers the names of competitors and related keywords on the management screen, completing the basic setup for collecting competitor information.

[0640] 2. Performing web crawling

[0641] The server periodically visits websites on the Internet to collect information related to registered keywords and competitor names, and the collected information is temporarily stored on the server.

[0642] 3. Natural Language Processing (NLP)

[0643] The server uses a natural language processing engine to analyze the text data collected by web crawling, and extracts useful competitive information (e.g., new product announcements, executive personnel changes, etc.). The extracted data is stored in a database.

[0644] 4. Social Media Monitoring

[0645] The server uses social media APIs to periodically collect and analyze information such as competitors' latest posts and follower counts. The analyzed data is also stored in a database.

[0646] 5. News Alerts

[0647] The server monitors the specified news feed URL and generates alerts when new news or press releases related to competitors are published, and notifies the user of the alerts.

[0648] 6. Artificial Intelligence Chatbots

[0649] The server responds to user questions using a chatbot engine. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information.

[0650] 7. Emotion Recognition Engine

[0651] The server uses an emotion recognition engine to recognize emotions from the user's dialogue and behavior. The emotion data is stored in a database and the system's behavior is adjusted based on the user's emotions.

[0652] Specific processing examples

[0653] For example, if a user wants to collect competitive information about a company called "ExampleCorp" and registers "ExampleCorp, new product, director personnel changes" as keywords in the system, the server operates as follows.

[0654] 1. The user enters a keyword from the device and sends it to the server.

[0655] 2. The server performs web crawling based on the registered keywords.

[0656] 3. The data collected by the server is analyzed using a natural language processing engine to extract relevant competitive information.

[0657] 4. The server collects and analyzes relevant information from the social media platform.

[0658] 5. The server monitors news feeds about competitors and generates alerts when new information is published.

[0659] 6. The user asks the chatbot, "Tell me about ExampleCorp's new product," and the server provides the appropriate information.

[0660] 7. The server recognizes emotions from the user's questions and actions to the chatbot and adjusts the response content based on the emotional data.

[0661] The system of the present invention not only efficiently collects and analyzes competitive information, but also, by combining it with an emotion recognition engine, is able to flexibly respond to the user's emotions, thereby contributing to an improved user experience.

[0662] The processing flow will be explained below.

[0663] Step 1:

[0664] A user logs into the system using a terminal, enters their authentication information (username and password), and if authentication is successful, accesses the main dashboard.

[0665] Step 2:

[0666] The user navigates to the admin page, selects the "Competitor Settings" option, enters the competitor name (e.g., ExampleCorp) and related keywords (e.g., new product, director personnel changes), and saves.

[0667] Step 3:

[0668] The device sends the entered competitor name and keywords to the server, which stores them in a database.

[0669] Step 4:

[0670] The server periodically launches the web crawling scheduler, which runs the web crawling tool at the specified interval (e.g., every 6 hours every day).

[0671] Step 5:

[0672] The server loads the list of websites to be collected and uses a web crawler to visit each site, retrieving text data from pages that match the specified competitor name or keywords.

[0673] Step 6:

[0674] The server temporarily stores the collected text data and launches a natural language processing engine to analyze the text and extract specific information (e.g., new product announcements, executive personnel changes).

[0675] Step 7:

[0676] The server stores the analysis results in a database, where they are organized and saved for later reference by the user.

[0677] Step 8:

[0678] The server uses social media APIs to monitor competitors' social media accounts, periodically collecting data on their latest posts and follower counts.

[0679] Step 9:

[0680] The server analyzes the collected social media data, extracts relevant information (e.g., marketing campaign responses, user comments) and stores it in a database.

[0681] Step 10:

[0682] The server monitors the specified news feed URL for new news articles and press releases related to competitors, and generates an alert when relevant information is published.

[0683] Step 11:

[0684] The server notifies the user of the generated alerts. The notifications are delivered to the user via email or internal system notifications.

[0685] Step 12:

[0686] A user launches the chatbot from a terminal and types a question about competitive information, such as "Tell me about ExampleCorp's new product."

[0687] Step 13:

[0688] The device sends the user's question to the server, which analyzes the question using a natural language processing engine and searches for related information in a database.

[0689] Step 14:

[0690] The server passes the search results to the chatbot, which generates an appropriate answer to the question, which is then sent to the device and displayed to the user.

[0691] Step 15:

[0692] The server activates an emotion recognition engine to determine the user's emotions through user questions and dialogue, and the emotion data is stored in a database.

[0693] Step 16:

[0694] The server takes into account the user's emotional data and adjusts the chatbot's responses, for example, providing more detailed information or offering assistance if the user expresses dissatisfaction.

[0695] Step 17:

[0696] The user selects the "Display Competitive Information Results" option from the administration screen. The device retrieves the latest analysis results from the server and displays them in a visualized format for the user.

[0697] Step 18:

[0698] The user can select the option to generate and download a competitive intelligence report if desired. The device will generate the report and provide a download link, such as in PDF format.

[0699] In this way, the system of the present invention quickly and efficiently collects and analyzes information on competitors through a series of processes and provides it to users.

[0700] Example 2

[0701] 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."

[0702] It is extremely important for companies to quickly and efficiently collect and analyze information about their competitors and use it to formulate their own strategies and develop products. However, current methods require time to collect and analyze information, making it difficult to make quick decisions. Furthermore, the collected information contains a lot of noise, making it difficult to extract useful information. Furthermore, there is a need for flexible systems that respond based on user sentiment, but current systems are unable to do so. The purpose of this invention is to solve these problems and enable companies to efficiently collect and analyze competitive information and make quick decisions.

[0703] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: information collection means for collecting information related to specific keywords and competitor names from websites; natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes; social media analysis means for collecting information on competitor posts and follower counts from social media platforms; notification means for generating alerts and notifying users when news articles or press releases related to competitors are published; interactive agent means for providing competitive information through dialogue with the user; and emotion recognition means for recognizing user emotions and adjusting system operation. This enables companies to efficiently collect and analyze competitive information and make quick decisions. Furthermore, flexible responses based on user emotions can also be realized.

[0704] "Information Gathering Tools" are tools or software used to automatically gather information related to specific keywords and competitor names from websites.

[0705] "Natural language processing means" refers to the technology and software used to analyze collected text data and extract useful information.

[0706] "Social media analytics tools" refer to technologies and software used to collect and analyze competitors' posts and follower numbers from social media platforms.

[0707] "Notification means" refers to a system or function that generates an alert and notifies users when a news article or press release related to a competitor is issued.

[0708] "Interactive agent means" refers to chatbot technology that uses artificial intelligence to provide competitive information through dialogue with users.

[0709] "Emotion recognition means" refers to the technology and software for recognizing emotions from user interactions and operations and adjusting the system's behavior.

[0710] This invention is a system that allows companies to quickly and efficiently collect and analyze information on their competitors and use it to formulate their own strategies and develop products. The system mainly consists of a server, a terminal, and a user. The server collects information, analyzes it, generates notifications, manages the database, and recognizes emotions, while the terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set competitive information, check the results, and interact with the chatbot.

[0711] Hardware and software used

[0712] server

[0713] 1. Information collection method: The server uses a web crawling tool such as "Scrapy" to automatically crawl websites on the Internet and collect information related to specific keywords and competitor names. The collected data is temporarily stored in a database such as "MongoDB."

[0714] 2. Natural language processing: The server uses tools like "spaCy" and "NLTK" to analyze the collected text data and extract useful information, such as "new product announcements" and "executive personnel changes," and stores this information in a database.

[0715] 3. Social media analysis: The server uses the Twitter API and Facebook Graph API to periodically collect and analyze information such as competitors' latest posts and follower numbers. The analyzed data is stored in a database.

[0716] 4. Notification Method: The server uses the Google News API and RSS feeds to monitor news articles and press releases related to competitors, and when new information is released, it generates an alert and notifies the user's device.

[0717] 5. Conversational Agent: The server uses chatbot engines such as Dialogflow and Rasa to respond to user questions. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information.

[0718] 6. Emotion Recognition: The server uses emotion recognition engines such as IBM Watson Tone Analyzer and Microsoft Azure Emotion API to recognize emotions from the user's interactions and actions. The recognized emotion data is stored in a database and the system's behavior is adjusted based on the user's emotions.

[0719] Terminal

[0720] 1. Accepting user input: The terminal provides an interface for accepting input from the user. For example, the user can register competitor names and related keywords on the management screen on the browser.

[0721] 2. Displaying Results: The device displays the analyzed data and alerts to the user, including the collected competitive information and analysis results.

[0722] 3. Report generation: The terminal generates a report based on the collected and analyzed data and provides it to the user.

[0723] Examples of concrete examples and prompts

[0724] For example, if a user wants to collect the latest information about "Competitor A," they can input keywords such as "new product announcement" and "management change" into the system. The server then performs web crawling, analyzes the collected data using a natural language processing engine, and extracts useful information. Using social media analysis tools, the server collects and analyzes "Competitor A's" latest posts and changes in the number of followers. It also monitors news articles and press releases related to "Competitor A" and notifies the user when new information is released. Furthermore, the user can use a chatbot to input questions such as "Tell me about Competitor A's new product," and the chatbot will search the database and provide relevant information. The server recognizes the user's emotions from their interactions and actions and adjusts the response accordingly.

[0725] Prompt Sentence Examples

[0726] "Collect the latest competitive information about competitor A."

[0727] "Please tell me about competitor A's new product."

[0728] "Check out competitor A's social media activity."

[0729] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0730] Step 1: User Input

[0731] The user logs into the system using a terminal and registers the name of the competitor and related keywords on the management screen. For example, they enter keywords such as "Competitor A," "New product announcement," and "Changes in management." When this input is sent to the server, the conditions for collecting competitive information are set and the basic setup is complete.

[0732] Input: Competitor name (Competitor A), related keywords (new product announcement, management changes)

[0733] Output: Basic setup for competitive intelligence gathering completed

[0734] Step 2: Perform a web crawl

[0735] The server uses Scrapy to crawl websites on the Internet based on set keywords. For example, it automatically collects blogs and news articles related to competitor A. The collected information is temporarily stored in MongoDB.

[0736] Input: Competitor name, related keywords

[0737] Output: Collected information (raw)

[0738] Step 3: Natural Language Processing (NLP)

[0739] The server uses "spaCy" or "NLTK" to analyze the collected text data and extract useful information. For example, specific information such as "Competitor A has announced a new product" or "The director has been transferred" is identified and stored in a database.

[0740] Input: Collected text data

[0741] Output: Extracted useful information (e.g., new product launches, executive personnel changes)

[0742] Step 4: Social Media Monitoring

[0743] The server uses the Twitter API and Facebook Graph API to periodically collect the latest posts and changes in the number of followers of competitor A. The collected data is analyzed, and specific information such as "Competitor A's new tweets" and "increased followers" is stored in a database.

[0744] Input: Competitor's social media account information

[0745] Output: Parsed social media data

[0746] Step 5: Generate a news alert

[0747] The server uses the Google News API and RSS feeds to monitor news articles and press releases related to competitor A. For example, if news comes out that competitor A has announced a new product, an alert is immediately generated and the user is notified.

[0748] Input: News feed URL

[0749] Output: Generated alert notification

[0750] Step 6: Artificial Intelligence Chatbots

[0751] A user accesses the chatbot using a device and inputs a question such as, "Please tell me about Competitor A's new product." The server uses Dialogflow to analyze the question, searches the database, and provides relevant information. It then returns a specific answer to the user, such as, "Competitor A has announced a new smartphone."

[0752] Input: User question

[0753] Output: Chatbot response

[0754] Step 7: Emotion Recognition

[0755] The server uses IBM Watson Tone Analyzer to recognize emotions from the user's dialogue and actions. For example, if the user is emotionally charged, the server adjusts the dialogue accordingly. This emotional data is stored in a database.

[0756] Input: User interaction content, operation information

[0757] Output: Emotion recognition results, adjusted dialogue content

[0758] (Application example 2)

[0759] 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."

[0760] Modern companies need to quickly and efficiently collect and analyze information about their competitors, but they lack the appropriate systems to do so. There is also a need for integrated support tools that enable store managers to collect and analyze competitive information and utilize it in store operations. Furthermore, there is a lack of systems that recognize user emotions and adjust interactions. There is a need to resolve these issues and support corporate strategy planning, product development, and efficient store operations.

[0761] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0762] In this invention, the server includes a web crawling means for collecting information related to specific keywords and competitor names from websites, a natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes, a social media monitoring means for collecting information on competitors' posts and follower numbers from social media platforms, a news alert means for receiving alerts when news articles or press releases related to competitors are issued, an AI chatbot means for collecting competitor information through dialogue with users, an emotion recognition means for recognizing user emotions and adjusting the content of the dialogue based on the emotions, and a smart store management means for allowing store managers to collect and analyze competitor information and use it in store operations. This enables companies to efficiently collect and analyze competitor information and effectively use it in store operations.

[0763] "Web crawling" is a technique for automatically collecting information from websites.

[0764] "Natural language processing" is a technology that uses computers to analyze, understand, and generate human language.

[0765] "Social media monitoring" is a technique for monitoring and collecting activity on social media.

[0766] "News Alert" is a technology that notifies you when news articles or press releases related to specified keywords are published.

[0767] An "artificial intelligence chatbot" is a system that provides and collects information through dialogue with users.

[0768] "Emotion recognition" is a technology that estimates and recognizes a user's emotions from their words, actions, and facial expressions.

[0769] "Smart Store Management" is an integrated support system that allows store managers to collect and analyze competitive information and utilize it in store operations.

[0770] This invention is a system that allows companies to quickly and efficiently collect and analyze information on their competitors and use it to formulate their own strategies and develop products. This system incorporates web crawling, natural language processing, social media monitoring, news alerts, AI chatbots, emotion recognition, and smart store management. We will explain the details of each method and how the entire system works.

[0771] Hardware and Software

[0772] The system consists of a server, user terminals, and a network. The hardware used includes regular desktop PCs, smartphones, and servers. The software uses the following technologies:

[0773] BeautifulSoup: Used to extract information from web pages.

[0774] SpaCy: Used for natural language processing.

[0775] Tweepy: Used to collect data from social media (Twitter).

[0776] Transformers (Hugging Face): Used for emotion recognition and chatbots.

[0777] NewsAPI: Used to collect news articles.

[0778] System Features

[0779] Web crawling

[0780] The server crawls websites based on registered keywords using BeautifulSoup and collects related information, which is then temporarily stored on the server in text format.

[0781] Natural Language Processing

[0782] The collected text data is analyzed on the server using SpaCy to extract useful information such as new product announcements and executive personnel changes, and the most relevant data is then stored in a database.

[0783] Social Media Monitoring

[0784] The server uses Tweepy to collect and analyze data on competitors' latest posts and follower numbers from social media APIs (such as Twitter), and the analysis data is stored in its own database.

[0785] News Alerts

[0786] The server uses the NewsAPI to alert users when news articles or press releases related to specific keywords are published, via email or in-app notifications.

[0787] Artificial Intelligence Chatbot

[0788] The server uses a chatbot engine based on Transformers to respond to user questions. For example, if a user asks, "Tell me about a new product from a competitor's company," the chatbot will search the database and provide relevant information.

[0789] emotion recognition

[0790] The server uses Transformers' emotion recognition engine to analyze emotions from user interactions, allowing it to tailor the chatbot's responses based on the user's emotional state.

[0791] Smart store management

[0792] Store managers can use this system to collect competitive information and develop store management strategies based on the analysis results, helping them maintain an advantage over their competitors.

[0793] Specific examples

[0794] For example, if a user asks "What is the latest information on a new product from a competitor's name?" the system will do the following:

[0795] Perform web crawling and collect relevant information.

[0796] Analyze and extract collected text data using natural language processing.

[0797] Collect the latest information on social media through social media monitoring.

[0798] News alerts detect new news articles and notify you accordingly.

[0799] An artificial intelligence chatbot responds to questions and provides relevant information from a database.

[0800] Emotion recognition generates responses based on the user's emotions.

[0801] Prompt Sentence Examples

[0802] "Please give me the latest information on new products from competitors' names."

[0803] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0804] Step 1:

[0805] A user logs into the system using a terminal and registers keywords such as "competitor company name, new product, executive personnel changes" on the administration screen.

[0806] Input: Keywords entered by the user on the device

[0807] Data processing: The server sets the basic settings for information collection based on this keyword.

[0808] Output: The set keywords are registered in the system.

[0809] Step 2:

[0810] The server periodically crawls websites on the Internet using BeautifulSoup and collects information related to registered keywords.

[0811] Input: Registered keyword

[0812] Data processing: Extracting text data from website HTML

[0813] Output: The collected text data is temporarily stored on the server.

[0814] Step 3:

[0815] The text data collected by the server is analyzed using SpaCy to extract useful information (e.g., new product announcements, executive personnel changes, etc.).

[0816] Input: Collected text data

[0817] Data processing: Extracting useful information through natural language processing

[0818] Output: The extracted information is registered in the database.

[0819] Step 4:

[0820] The server uses Tweepy to collect and analyze competitors' latest posts and follower counts from social media APIs.

[0821] Input: Registered keyword

[0822] Data processing: Analyzing data obtained from social media APIs

[0823] Output: The parsed information is registered in the database

[0824] Step 5:

[0825] The server uses the NewsAPI to monitor news articles and press releases related to competitors and generate alerts when new information is released.

[0826] Input: Specific keywords

[0827] Data processing: Monitor news feeds and generate notifications when new information is published.

[0828] Output: A notification is sent to the user's device

[0829] Step 6:

[0830] The user inputs a question to the chatbot through the terminal, such as "Please tell me about a new product from a competitor's company."

[0831] Input: User question (prompt)

[0832] Data processing: The server uses the chatbot engine to search the database and extract relevant information.

[0833] Output: The extracted information is provided to the user

[0834] Step 7:

[0835] The server uses Transformers to recognize emotions from the user's dialogue and adjust the dialogue content.

[0836] Input: User interaction

[0837] Data processing: Analyze emotions with an emotion recognition engine and tailor responses accordingly

[0838] Output: An appropriate response is generated according to the user's emotions.

[0839] Step 8:

[0840] Store managers use this system to collect and analyze competitive information and develop strategies for store operations.

[0841] Input: Collected and analyzed competitive information

[0842] Data processing: Formulate operational strategies based on results

[0843] Output: A new strategy for store operations is implemented.

[0844] The above processing steps enable business and store managers to quickly and efficiently collect and analyze competitive information and use it to develop appropriate business strategies.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] [Third embodiment]

[0849] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0850] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0851] 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).

[0852] 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.

[0853] 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.

[0854] 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).

[0855] 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.

[0856] 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.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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."

[0861] To implement the present invention, the following system configuration and program processing are required.

[0862] System Configuration

[0863] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, sends alerts, and manages the database. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set conflict information and check the results.

[0864] Program processing (natural language explanation)

[0865] 1. User Input

[0866] The user logs in to the system using a terminal and registers the names of competitors and related keywords on the management screen, completing the basic setup for collecting competitor information.

[0867] 2. Performing web crawling

[0868] The server periodically visits websites on the Internet to collect information related to registered keywords and competitor names, and the collected information is temporarily stored on the server.

[0869] 3. Natural Language Processing (NLP)

[0870] The server uses a natural language processing engine to analyze the text data collected by web crawling, and extracts useful competitive information (e.g., new product announcements, executive personnel changes, etc.). The extracted data is stored in a database.

[0871] 4. Social Media Monitoring

[0872] The server uses social media APIs to periodically collect and analyze information such as competitors' latest posts and follower counts. The analyzed data is also stored in a database.

[0873] 5. News Alerts

[0874] The server monitors the specified news feeds and generates alerts to notify the user when new news or press releases about competitors are published.

[0875] 6. Artificial Intelligence Chatbots

[0876] The server responds to user questions using a chatbot engine. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information.

[0877] Specific processing examples

[0878] For example, suppose a user wants to collect competitive information about a company called "ExampleCorp" and registers "ExampleCorp, new product, director personnel changes" as keywords in the system. In this case, the server operates as follows:

[0879] 1. The user enters a keyword from the device and sends it to the server.

[0880] 2. The server performs web crawling based on the registered keywords.

[0881] 3. The data collected by the server is analyzed using a natural language processing engine to extract relevant competitive information.

[0882] 4. The server collects and analyzes relevant information from the social media platform.

[0883] 5. The server monitors news feeds about competitors and generates alerts when new information is published.

[0884] 6. The user asks the chatbot, "Tell me about ExampleCorp's new product," and the server provides the appropriate information.

[0885] In this way, the system of the present invention can collect and analyze competitive information in real time and provide it to users.

[0886] The processing flow will be explained below.

[0887] Step 1:

[0888] A user logs into the system using a terminal, enters their authentication information (username and password), and if authentication is successful, accesses the main dashboard.

[0889] Step 2:

[0890] The user navigates to the admin page, selects the "Competitor Settings" option, enters the competitor name (e.g., ExampleCorp) and related keywords (e.g., new product, director personnel changes), and saves.

[0891] Step 3:

[0892] The device sends the entered competitor name and keywords to the server, which stores them in a database.

[0893] Step 4:

[0894] The server periodically launches the web crawling scheduler, which runs the web crawling tool at the specified interval (e.g., every 6 hours every day).

[0895] Step 5:

[0896] The server loads the list of websites to be collected and uses a web crawler to visit each site, retrieving text data from pages that match the specified competitor name or keywords.

[0897] Step 6:

[0898] The server temporarily stores the collected text data and launches a natural language processing engine to analyze the text and extract specific information (e.g., new product announcements, executive personnel changes).

[0899] Step 7:

[0900] The server stores the analysis results in a database, where they are organized and saved for later reference by the user.

[0901] Step 8:

[0902] The server uses social media APIs to monitor competitors' social media accounts, periodically collecting data on their latest posts and follower counts.

[0903] Step 9:

[0904] The server analyzes the collected social media data, extracts relevant information (e.g., marketing campaign responses, user comments) and stores it in a database.

[0905] Step 10:

[0906] The server monitors the specified news feed URL for new news articles and press releases related to competitors, and generates an alert when relevant information is published.

[0907] Step 11:

[0908] The server notifies the user of the generated alerts. The notifications are delivered to the user via email or internal system notifications.

[0909] Step 12:

[0910] A user launches the chatbot from a terminal and types a question about competitive information, such as "Tell me about ExampleCorp's new product."

[0911] Step 13:

[0912] The device sends the user's question to the server, which analyzes the question using a natural language processing engine and searches for related information in a database.

[0913] Step 14:

[0914] The server passes the search results to the chatbot, which generates an appropriate answer to the question, which is then sent to the device and displayed to the user.

[0915] Step 15:

[0916] The user selects the "Display Competitive Information Results" option from the administration screen. The device retrieves the latest analysis results from the server and displays them in a visualized format for the user.

[0917] Step 16:

[0918] The user can select the option to generate and download a competitive intelligence report if desired. The device will generate the report and provide a download link, such as in PDF format.

[0919] In this way, the system of the present invention quickly and efficiently collects and analyzes information on competitors through a series of processes and provides it to users.

[0920] Example 1

[0921] 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."

[0922] Collecting competitive information effectively and in real time is extremely important for understanding a company's marketing strategy and market trends. However, when information is collected manually, it takes a huge amount of time and effort, and analyzing the collected information is not easy. Furthermore, it is difficult to integrate multiple functions such as web crawling, social media monitoring, news alerts, and chatbots. This makes it difficult to understand competitor trends in a timely manner.

[0923] 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.

[0924] In this invention, the server includes an input means for a user to register specific keywords and competitor names using a terminal, a web crawling means for collecting information related to the specific keywords and competitor names from websites, a natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes, a social media monitoring means for collecting information on competitors' posts and follower numbers from social media platforms, a news alert means for generating alerts when news articles or press releases related to competitors are issued, and an AI chatbot means for providing competitor information through dialogue with users. This makes it possible to effectively collect, analyze, and comprehensively manage competitor information in real time.

[0925] "Input means" is a function that allows a user to register specific keywords and competitor names in the system using a terminal.

[0926] "Web crawling means" is a function that allows a server to crawl websites on the Internet and automatically collect information related to specific keywords and competitor names.

[0927] "Natural language processing means" is a function that analyzes collected text data and extracts specific information such as new product announcements and executive personnel changes. Specifically, it analyzes text using a natural language processing engine.

[0928] "Social media monitoring tools" are functions that collect and analyze information on competitors' posts and follower numbers from social media platforms.

[0929] The "news alert means" is a function that generates an alert and notifies the user when a news article or press release related to a competitor is issued.

[0930] The "artificial intelligence chatbot means" is a function that provides competitive information through dialogue with users. Specifically, it uses a chatbot engine to respond to user questions.

[0931] "Control Measures" refers to a function that integrates and operates web crawling, natural language processing, social media monitoring, news alerts, and AI chatbot functions based on keywords and competitor names set by the user.

[0932] MODE FOR CARRYING OUT THE INVENTION

[0933] To implement the present invention, the following system configuration and program processing are required.

[0934] System Configuration

[0935] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, generates alerts, and manages the database. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set conflict information and check the results.

[0936] Program processing (natural language explanation)

[0937] 1. User Input

[0938] A user logs in to the system using a terminal and registers competitor names and related keywords on the management screen. This operation includes entering keywords in a text field and clicking the "Register" button.

[0939] 2. Performing web crawling

[0940] The server launches a web crawling tool (e.g., Selenium or Scrapy) to collect information related to the registered keywords and competitor names from websites on the Internet. This data is temporarily stored in the server's storage. Specifically, the server searches for URLs that match the keywords and parses the HTML of those web pages to extract text data.

[0941] 3. Natural Language Processing (NLP)

[0942] The server passes the collected text data to a natural language processing engine (e.g., spaCy or NLTK) for analysis. The natural language processing engine tokenizes the text data and extracts important entities (e.g., company names, new product names, executive names, etc.). The extracted information is stored in a database. The server then divides the text data into sentences and performs entity identification for each sentence.

[0943] 4. Social Media Monitoring

[0944] The server prepares a social media API client (e.g., Twitter API client) and periodically calls the API to collect competitors' posts. The collected posts are analyzed, and important data (e.g., increases or decreases in the number of followers, rumors about new products, etc.) is extracted and stored in a database. The server parses the JSON-formatted data received from the API and extracts the necessary information.

[0945] 5. News Alerts

[0946] The server uses a news API (e.g., Google News API) to monitor news feeds and generates alerts when new news or press releases related to competitors are published. The generated alerts are notified to the user. Specifically, the server sets up regular checks of the feed and generates alerts when new entries are found.

[0947] 6. Artificial Intelligence Chatbots

[0948] The server launches a chatbot engine (e.g., ChatGPT or Dialogflow) and provides an interface for accepting user questions. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information. For example, if a user inputs "Tell me about ExampleCorp's new product," the server analyzes the question, retrieves information about the new product from the database, and responds.

[0949] Specific examples

[0950] For example, if a user wants to collect information about a certain company, he or she registers keywords such as "certain company, new product, executive personnel changes" in the system. In this case, the server operates as follows:

[0951] 1. The user enters a keyword from the device and sends it to the server.

[0952] 2. The server performs web crawling using Selenium based on the registered keywords.

[0953] 3. The data collected by the server is analyzed using spaCy to extract relevant competitive information.

[0954] 4. The server collects and analyzes relevant information from the Twitter API.

[0955] 5. The server monitors the news feed via the Google News API and generates an alert when new information is published.

[0956] 6. The user asks the chatbot, "Please tell me about a new product from a certain company," and the server provides the appropriate information.

[0957] In this way, the system of the present invention can collect and analyze competitive information in real time and provide it to users.

[0958] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0959] Step 1:

[0960] A user logs into the system using a terminal and registers the name of a competitor and related keywords on the management screen. The input for this operation is the "competitor name" and "keywords" entered by the user in the text field on the terminal. The output is this information sent to the server. Specifically, the user enters the keywords in the text field on the management screen and clicks the "Register" button.

[0961] Step 2:

[0962] The server performs web crawling based on registered keywords and competitor names. The input for this process is the "keywords" and "competitor names" registered by the user, and the output is the collected text data of websites. The server uses Selenium or Scrapy to automatically crawl related web pages on the Internet, parse the HTML data, and extract the text data.

[0963] Step 3:

[0964] The server passes the collected text data to a natural language processing engine for analysis. The input to this process is the "text data" collected in step 2, and the output is "extracted specific information (e.g., new product announcements, executive personnel changes, etc.)." Specifically, the server inputs the collected text data into spaCy or NLTK, which tokenizes the data and performs entity identification processing. Then, important information is extracted and stored in a database.

[0965] Step 4:

[0966] The server uses social media APIs to collect competitors' posts and follower counts. The inputs for this process are "competitor names" and "API clients," and the output is "collected social media data." The server periodically calls the Twitter API and Facebook API to receive relevant post and follower count data in JSON format. The server then analyzes the data and stores important information in a database.

[0967] Step 5:

[0968] The server monitors the news feed and generates alerts. The inputs for this process are the "news feed URL" and "keywords," and the output is an "alert notification." The server periodically checks for news articles and press releases related to the registered keywords using the Google News API, etc., and generates an alert to notify the user when new information is released.

[0969] Step 6:

[0970] When a user inputs a question to a chatbot using a terminal, the server provides appropriate information in response to the question. The input for this process is the user's "question" and the output is the "response." The server analyzes the question using a chatbot engine (e.g., ChatGPT or Dialogflow), searches for relevant information from a database, and generates a response. Specifically, if a user asks, "Please tell me about a new product from a certain company," the server retrieves information about the new product from the database and presents the answer through the chatbot.

[0971] (Application example 1)

[0972] 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."

[0973] Conventional competitive intelligence analysis systems only handle information such as competitor product announcements and executive personnel changes, and lack the functionality to collect and analyze information related to security risks, making it difficult for companies to respond quickly to security risks.

[0974] 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.

[0975] In this invention, the server includes a web crawling means for collecting information related to specific keywords and competitor names from websites, a natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes, a social media monitoring means for collecting information on competitors' posts and follower numbers from social media platforms, a news alert means for receiving alerts when news articles or press releases related to competitors are issued, an AI chatbot means for collecting competitor information through dialogue with users, and a cybersecurity monitoring means for collecting and analyzing information related to security risks. This enables the collection and analysis of not only information about competitors but also information about security risks, enabling companies to respond to security risks quickly and effectively.

[0976] "Web crawling" is a technique for automatically visiting websites on the Internet and collecting specific information.

[0977] "Natural language processing" is a technology that allows computers to understand and analyze human language and is used to extract specific information.

[0978] "Social media monitoring" is a technology that collects and analyzes information such as posts and follower numbers on social media platforms.

[0979] "News Alert" is a function that notifies users of the contents of specific news articles or press releases when they are published.

[0980] An "artificial intelligence chatbot" is software based on artificial intelligence that collects and provides information through dialogue with users.

[0981] "Information related to security risks" refers to information that may affect information security, such as cyber attacks, vulnerabilities, and phishing attacks.

[0982] "Cybersecurity monitoring" is a technology that collects and analyzes information on security risks related to specific keywords.

[0983] To implement the present invention, the following system configuration and program processing are required.

[0984] System Configuration

[0985] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, sends alerts, and manages the database. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set conflict information and check the results.

[0986] Hardware and software used

[0987] Server: Cloud-based server (e.g. AWS EC2)

[0988] Smartphone: iOS or Android device (app developed with React Native)

[0989] Database: PostgreSQL

[0990] Web crawler: Scrapy

[0991] Natural Language Processing (NLP): spaCy, NLTK

[0992] Social Media APIs: Twitter API, Facebook Graph API

[0993] Chatbot engine: Rasa

[0994] Program processing (natural language explanation)

[0995] server

[0996] The server receives the user's input and executes the following steps:

[0997] 1. Web crawling methods:

[0998] The server uses Scrapy to crawl websites related to registered keywords and competitor names and collect information.

[0999] The collected data is temporarily stored on the server.

[1000] 2. Natural Language Processing Tools:

[1001] The collected text data is analyzed using spaCy and NLTK to extract specific information such as new product announcements and executive personnel changes.

[1002] 3. Social Media Monitoring Methods:

[1003] The server uses the Twitter API and Facebook Graph API to periodically collect and analyze competitors' posts and follower counts.

[1004] 4. News Alert Methods:

[1005] Generate alerts to notify users when news articles or press releases related to competitors are published.

[1006] 5. Artificial Intelligence Chatbot Means:

[1007] Using Rasa, we collect competitive information and provide answers based on user questions.

[1008] 6. Cybersecurity Monitoring Measures:

[1009] It collects and analyzes security risk information related to specific keywords. For example, the server periodically checks for information about phishing attacks and malware and reports it to the user.

[1010] Terminal

[1011] The terminal acts as a user interface and provides the following functions:

[1012] Enter keywords and competitor names

[1013] Viewing analysis results and reports

[1014] Security risk alert notifications

[1015] User

[1016] The user operates the terminal and performs the following operations.

[1017] Registering keywords and competitor names

[1018] Checking the analysis results

[1019] Use the chatbot to ask for more information

[1020] Examples of concrete examples and prompts

[1021] As a concrete example, if a user sets the keywords "new product release phishing attack", the server operates as follows:

[1022] 1. Web crawling: When a specific company announces a new product release, we collect information about related phishing attacks.

[1023] 2. Natural Language Processing: Analyzes collected data and extracts useful information.

[1024] 3. Social media monitoring: Analyze the company's new product posts and related security risks.

[1025] 4. News Alerts: Notify users if a security risk related to a new release is detected.

[1026] 5. Chatbot: Type "What are the security risks of a new product release?" and get real-time details.

[1027] Example prompt sentence:

[1028] "What are the latest phishing attacks related to new product releases?"

[1029] "Show me the analysis results for a specific company's new product releases."

[1030] In this way, the system of the present invention can collect and analyze competitive information and security risks in real time and provide them to users.

[1031] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1032] Step 1:

[1033] The user operates the terminal, inputs and registers specific keywords and competitor names, and the input information is sent to the server. For example, if a user registers keywords such as "new product release phishing attack," this is sent to the server.

[1034] Step 2:

[1035] The server performs web crawling based on the registered keywords and competitor names. Specifically, the server uses Scrapy to crawl specific websites and collect relevant information. The input is the keywords and competitor names, and the output is the collected web data.

[1036] Step 3:

[1037] The server analyzes the collected web data using a natural language processing (NLP) engine. Specifically, the server uses spaCy or NLTK to analyze the text data and extract specific information, such as new product announcements or executive personnel changes. The input is the collected web data, and the output is the data from which the specific information has been extracted.

[1038] Step 4:

[1039] The server monitors the social media activities of competitors. Specifically, the server uses the Twitter API and Facebook Graph API to collect and analyze competitors' posts and follower counts. The input is social media account information, and the output is analyzed social media activity data.

[1040] Step 5:

[1041] The server monitors news articles and press releases related to competitors and generates alerts. When new news related to a specific keyword is published, the server generates an alert and notifies the user. The input is the news feed information and the output is the generated alert.

[1042] Step 6:

[1043] The server performs security risk analysis based on the collected information. Specifically, the server uses its cybersecurity monitoring function to periodically check for information about phishing attacks and malware and provide it to the user. The input is data related to competitors and security risks, and the output is a report on security risks.

[1044] Step 7:

[1045] A user can use the chatbot to request information from their device. For example, if the user types, "Please tell me the latest phishing attack information regarding new product releases," the server uses Rasa to search the relevant database and provide the appropriate information. The input is the user's query, and the output is the corresponding response.

[1046] In this way, the present invention realizes a system that collects and analyzes information step by step and provides the user with necessary competitive information and security risk information.

[1047] 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.

[1048] The present invention is a system that allows companies to quickly and efficiently collect and analyze information on their competitors and use it to formulate their own strategies and develop products. The present invention includes web crawling means, natural language processing means, social media monitoring means, news alert means, and artificial intelligence chatbot means, as well as an emotion recognition engine that recognizes user emotions. Specific embodiments of the present invention and the processing of the program are described below.

[1049] System Configuration

[1050] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, generates alerts, manages the database, and recognizes emotions. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set competitive information, check the results, and interact with the chatbot.

[1051] Program processing (natural language explanation)

[1052] 1. User Input

[1053] The user logs in to the system using a terminal and registers the names of competitors and related keywords on the management screen, completing the basic setup for collecting competitor information.

[1054] 2. Performing web crawling

[1055] The server periodically visits websites on the Internet to collect information related to registered keywords and competitor names, and the collected information is temporarily stored on the server.

[1056] 3. Natural Language Processing (NLP)

[1057] The server uses a natural language processing engine to analyze the text data collected by web crawling, and extracts useful competitive information (e.g., new product announcements, executive personnel changes, etc.). The extracted data is stored in a database.

[1058] 4. Social Media Monitoring

[1059] The server uses social media APIs to periodically collect and analyze information such as competitors' latest posts and follower counts. The analyzed data is also stored in a database.

[1060] 5. News Alerts

[1061] The server monitors the specified news feed URL and generates alerts when new news or press releases related to competitors are published, and notifies the user of the alerts.

[1062] 6. Artificial Intelligence Chatbots

[1063] The server responds to user questions using a chatbot engine. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information.

[1064] 7. Emotion Recognition Engine

[1065] The server uses an emotion recognition engine to recognize emotions from the user's dialogue and behavior. The emotion data is stored in a database and the system's behavior is adjusted based on the user's emotions.

[1066] Specific processing examples

[1067] For example, if a user wants to collect competitive information about a company called "ExampleCorp" and registers "ExampleCorp, new product, director personnel changes" as keywords in the system, the server operates as follows.

[1068] 1. The user enters a keyword from the device and sends it to the server.

[1069] 2. The server performs web crawling based on the registered keywords.

[1070] 3. The data collected by the server is analyzed using a natural language processing engine to extract relevant competitive information.

[1071] 4. The server collects and analyzes relevant information from the social media platform.

[1072] 5. The server monitors news feeds about competitors and generates alerts when new information is published.

[1073] 6. The user asks the chatbot, "Tell me about ExampleCorp's new product," and the server provides the appropriate information.

[1074] 7. The server recognizes emotions from the user's questions and actions to the chatbot and adjusts the response content based on the emotional data.

[1075] The system of the present invention not only efficiently collects and analyzes competitive information, but also, by combining it with an emotion recognition engine, is able to flexibly respond to the user's emotions, thereby contributing to an improved user experience.

[1076] The processing flow will be explained below.

[1077] Step 1:

[1078] A user logs into the system using a terminal, enters their authentication information (username and password), and if authentication is successful, accesses the main dashboard.

[1079] Step 2:

[1080] The user navigates to the admin page, selects the "Competitor Settings" option, enters the competitor name (e.g., ExampleCorp) and related keywords (e.g., new product, director personnel changes), and saves.

[1081] Step 3:

[1082] The device sends the entered competitor name and keywords to the server, which stores them in a database.

[1083] Step 4:

[1084] The server periodically launches the web crawling scheduler, which runs the web crawling tool at the specified interval (e.g., every 6 hours every day).

[1085] Step 5:

[1086] The server loads the list of websites to be collected and uses a web crawler to visit each site, retrieving text data from pages that match the specified competitor name or keywords.

[1087] Step 6:

[1088] The server temporarily stores the collected text data and launches a natural language processing engine to analyze the text and extract specific information (e.g., new product announcements, executive personnel changes).

[1089] Step 7:

[1090] The server stores the analysis results in a database, where they are organized and saved for later reference by the user.

[1091] Step 8:

[1092] The server uses social media APIs to monitor competitors' social media accounts, periodically collecting data on their latest posts and follower counts.

[1093] Step 9:

[1094] The server analyzes the collected social media data, extracts relevant information (e.g., marketing campaign responses, user comments) and stores it in a database.

[1095] Step 10:

[1096] The server monitors the specified news feed URL for new news articles and press releases related to competitors, and generates an alert when relevant information is published.

[1097] Step 11:

[1098] The server notifies the user of the generated alerts. The notifications are delivered to the user via email or internal system notifications.

[1099] Step 12:

[1100] A user launches the chatbot from a terminal and types a question about competitive information, such as "Tell me about ExampleCorp's new product."

[1101] Step 13:

[1102] The device sends the user's question to the server, which analyzes the question using a natural language processing engine and searches for related information in a database.

[1103] Step 14:

[1104] The server passes the search results to the chatbot, which generates an appropriate answer to the question, which is then sent to the device and displayed to the user.

[1105] Step 15:

[1106] The server activates an emotion recognition engine to determine the user's emotions through user questions and dialogue, and the emotion data is stored in a database.

[1107] Step 16:

[1108] The server takes into account the user's emotional data and adjusts the chatbot's responses, for example, providing more detailed information or offering assistance if the user expresses dissatisfaction.

[1109] Step 17:

[1110] The user selects the "Display Competitive Information Results" option from the administration screen. The device retrieves the latest analysis results from the server and displays them in a visualized format for the user.

[1111] Step 18:

[1112] The user can select the option to generate and download a competitive intelligence report if desired. The device will generate the report and provide a download link, such as in PDF format.

[1113] In this way, the system of the present invention quickly and efficiently collects and analyzes information on competitors through a series of processes and provides it to users.

[1114] Example 2

[1115] 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."

[1116] It is extremely important for companies to quickly and efficiently collect and analyze information about their competitors and use it to formulate their own strategies and develop products. However, current methods require time to collect and analyze information, making it difficult to make quick decisions. Furthermore, the collected information contains a lot of noise, making it difficult to extract useful information. Furthermore, there is a need for flexible systems that respond based on user sentiment, but current systems are unable to do so. The purpose of this invention is to solve these problems and enable companies to efficiently collect and analyze competitive information and make quick decisions.

[1117] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: information collection means for collecting information related to specific keywords and competitor names from websites; natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes; social media analysis means for collecting information on competitor posts and follower counts from social media platforms; notification means for generating alerts and notifying users when news articles or press releases related to competitors are published; interactive agent means for providing competitive information through dialogue with the user; and emotion recognition means for recognizing user emotions and adjusting system operation. This enables companies to efficiently collect and analyze competitive information and make quick decisions. Furthermore, flexible responses based on user emotions can also be realized.

[1118] "Information Gathering Tools" are tools or software used to automatically gather information related to specific keywords and competitor names from websites.

[1119] "Natural language processing means" refers to the technology and software used to analyze collected text data and extract useful information.

[1120] "Social media analytics tools" refer to technologies and software used to collect and analyze competitors' posts and follower numbers from social media platforms.

[1121] "Notification means" refers to a system or function that generates an alert and notifies users when a news article or press release related to a competitor is issued.

[1122] "Interactive agent means" refers to chatbot technology that uses artificial intelligence to provide competitive information through dialogue with users.

[1123] "Emotion recognition means" refers to the technology and software for recognizing emotions from user interactions and operations and adjusting the system's behavior.

[1124] This invention is a system that allows companies to quickly and efficiently collect and analyze information on their competitors and use it to formulate their own strategies and develop products. The system mainly consists of a server, a terminal, and a user. The server collects information, analyzes it, generates notifications, manages the database, and recognizes emotions, while the terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set competitive information, check the results, and interact with the chatbot.

[1125] Hardware and software used

[1126] server

[1127] 1. Information collection method: The server uses a web crawling tool such as "Scrapy" to automatically crawl websites on the Internet and collect information related to specific keywords and competitor names. The collected data is temporarily stored in a database such as "MongoDB."

[1128] 2. Natural language processing: The server uses tools like "spaCy" and "NLTK" to analyze the collected text data and extract useful information, such as "new product announcements" and "executive personnel changes," and stores this information in a database.

[1129] 3. Social media analysis: The server uses the Twitter API and Facebook Graph API to periodically collect and analyze information such as competitors' latest posts and follower numbers. The analyzed data is stored in a database.

[1130] 4. Notification Method: The server uses the Google News API and RSS feeds to monitor news articles and press releases related to competitors, and when new information is released, it generates an alert and notifies the user's device.

[1131] 5. Conversational Agent: The server uses chatbot engines such as Dialogflow and Rasa to respond to user questions. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information.

[1132] 6. Emotion Recognition: The server uses emotion recognition engines such as IBM Watson Tone Analyzer and Microsoft Azure Emotion API to recognize emotions from the user's interactions and actions. The recognized emotion data is stored in a database and the system's behavior is adjusted based on the user's emotions.

[1133] Terminal

[1134] 1. Accepting user input: The terminal provides an interface for accepting input from the user. For example, the user can register competitor names and related keywords on the management screen on the browser.

[1135] 2. Displaying Results: The device displays the analyzed data and alerts to the user, including the collected competitive information and analysis results.

[1136] 3. Report generation: The terminal generates a report based on the collected and analyzed data and provides it to the user.

[1137] Examples of concrete examples and prompts

[1138] For example, if a user wants to collect the latest information about "Competitor A," they can input keywords such as "new product announcement" and "management change" into the system. The server then performs web crawling, analyzes the collected data using a natural language processing engine, and extracts useful information. Using social media analysis tools, the server collects and analyzes "Competitor A's" latest posts and changes in the number of followers. It also monitors news articles and press releases related to "Competitor A" and notifies the user when new information is released. Furthermore, the user can use a chatbot to input questions such as "Tell me about Competitor A's new product," and the chatbot will search the database and provide relevant information. The server recognizes the user's emotions from their interactions and actions and adjusts the response accordingly.

[1139] Prompt Sentence Examples

[1140] "Collect the latest competitive information about competitor A."

[1141] "Please tell me about competitor A's new product."

[1142] "Check out competitor A's social media activity."

[1143] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1144] Step 1: User Input

[1145] The user logs into the system using a terminal and registers the name of the competitor and related keywords on the management screen. For example, they enter keywords such as "Competitor A," "New product announcement," and "Changes in management." When this input is sent to the server, the conditions for collecting competitive information are set and the basic setup is complete.

[1146] Input: Competitor name (Competitor A), related keywords (new product announcement, management changes)

[1147] Output: Basic setup for competitive intelligence gathering completed

[1148] Step 2: Perform a web crawl

[1149] The server uses Scrapy to crawl websites on the Internet based on set keywords. For example, it automatically collects blogs and news articles related to competitor A. The collected information is temporarily stored in MongoDB.

[1150] Input: Competitor name, related keywords

[1151] Output: Collected information (raw)

[1152] Step 3: Natural Language Processing (NLP)

[1153] The server uses "spaCy" or "NLTK" to analyze the collected text data and extract useful information. For example, specific information such as "Competitor A has announced a new product" or "The director has been transferred" is identified and stored in a database.

[1154] Input: Collected text data

[1155] Output: Extracted useful information (e.g., new product launches, executive personnel changes)

[1156] Step 4: Social Media Monitoring

[1157] The server uses the Twitter API and Facebook Graph API to periodically collect the latest posts and changes in the number of followers of competitor A. The collected data is analyzed, and specific information such as "Competitor A's new tweets" and "increased followers" is stored in a database.

[1158] Input: Competitor's social media account information

[1159] Output: Parsed social media data

[1160] Step 5: Generate a news alert

[1161] The server uses the Google News API and RSS feeds to monitor news articles and press releases related to competitor A. For example, if news comes out that competitor A has announced a new product, an alert is immediately generated and the user is notified.

[1162] Input: News feed URL

[1163] Output: Generated alert notification

[1164] Step 6: Artificial Intelligence Chatbots

[1165] A user accesses the chatbot using a device and inputs a question such as, "Please tell me about Competitor A's new product." The server uses Dialogflow to analyze the question, searches the database, and provides relevant information. It then returns a specific answer to the user, such as, "Competitor A has announced a new smartphone."

[1166] Input: User question

[1167] Output: Chatbot response

[1168] Step 7: Emotion Recognition

[1169] The server uses IBM Watson Tone Analyzer to recognize emotions from the user's dialogue and actions. For example, if the user is emotionally charged, the server adjusts the dialogue accordingly. This emotional data is stored in a database.

[1170] Input: User interaction content, operation information

[1171] Output: Emotion recognition results, adjusted dialogue content

[1172] (Application example 2)

[1173] 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."

[1174] Modern companies need to quickly and efficiently collect and analyze information about their competitors, but they lack the appropriate systems to do so. There is also a need for integrated support tools that enable store managers to collect and analyze competitive information and utilize it in store operations. Furthermore, there is a lack of systems that recognize user emotions and adjust interactions. There is a need to resolve these issues and support corporate strategy planning, product development, and efficient store operations.

[1175] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1176] In this invention, the server includes a web crawling means for collecting information related to specific keywords and competitor names from websites, a natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes, a social media monitoring means for collecting information on competitors' posts and follower numbers from social media platforms, a news alert means for receiving alerts when news articles or press releases related to competitors are issued, an AI chatbot means for collecting competitor information through dialogue with users, an emotion recognition means for recognizing user emotions and adjusting the content of the dialogue based on the emotions, and a smart store management means for allowing store managers to collect and analyze competitor information and use it in store operations. This enables companies to efficiently collect and analyze competitor information and effectively use it in store operations.

[1177] "Web crawling" is a technique for automatically collecting information from websites.

[1178] "Natural language processing" is a technology that uses computers to analyze, understand, and generate human language.

[1179] "Social media monitoring" is a technique for monitoring and collecting activity on social media.

[1180] "News Alert" is a technology that notifies you when news articles or press releases related to specified keywords are published.

[1181] An "artificial intelligence chatbot" is a system that provides and collects information through dialogue with users.

[1182] "Emotion recognition" is a technology that estimates and recognizes a user's emotions from their words, actions, and facial expressions.

[1183] "Smart Store Management" is an integrated support system that allows store managers to collect and analyze competitive information and utilize it in store operations.

[1184] This invention is a system that allows companies to quickly and efficiently collect and analyze information on their competitors and use it to formulate their own strategies and develop products. This system incorporates web crawling, natural language processing, social media monitoring, news alerts, AI chatbots, emotion recognition, and smart store management. We will explain the details of each method and how the entire system works.

[1185] Hardware and Software

[1186] The system consists of a server, user terminals, and a network. The hardware used includes regular desktop PCs, smartphones, and servers. The software uses the following technologies:

[1187] BeautifulSoup: Used to extract information from web pages.

[1188] SpaCy: Used for natural language processing.

[1189] Tweepy: Used to collect data from social media (Twitter).

[1190] Transformers (Hugging Face): Used for emotion recognition and chatbots.

[1191] NewsAPI: Used to collect news articles.

[1192] System Features

[1193] Web crawling

[1194] The server crawls websites based on registered keywords using BeautifulSoup and collects related information, which is then temporarily stored on the server in text format.

[1195] Natural Language Processing

[1196] The collected text data is analyzed on the server using SpaCy to extract useful information such as new product announcements and executive personnel changes, and the most relevant data is then stored in a database.

[1197] Social Media Monitoring

[1198] The server uses Tweepy to collect and analyze data on competitors' latest posts and follower numbers from social media APIs (such as Twitter), and the analysis data is stored in its own database.

[1199] News Alerts

[1200] The server uses the NewsAPI to alert users when news articles or press releases related to specific keywords are published, via email or in-app notifications.

[1201] Artificial Intelligence Chatbot

[1202] The server uses a chatbot engine based on Transformers to respond to user questions. For example, if a user asks, "Tell me about a new product from a competitor's company," the chatbot will search the database and provide relevant information.

[1203] emotion recognition

[1204] The server uses Transformers' emotion recognition engine to analyze emotions from user interactions, allowing it to tailor the chatbot's responses based on the user's emotional state.

[1205] Smart store management

[1206] Store managers can use this system to collect competitive information and develop store management strategies based on the analysis results, helping them maintain an advantage over their competitors.

[1207] Specific examples

[1208] For example, if a user asks "What is the latest information on a new product from a competitor's name?" the system will do the following:

[1209] Perform web crawling and collect relevant information.

[1210] Analyze and extract collected text data using natural language processing.

[1211] Collect the latest information on social media through social media monitoring.

[1212] News alerts detect new news articles and notify you accordingly.

[1213] An artificial intelligence chatbot responds to questions and provides relevant information from a database.

[1214] Emotion recognition generates responses based on the user's emotions.

[1215] Prompt Sentence Examples

[1216] "Please give me the latest information on new products from competitors' names."

[1217] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1218] Step 1:

[1219] A user logs into the system using a terminal and registers keywords such as "competitor company name, new product, executive personnel changes" on the administration screen.

[1220] Input: Keywords entered by the user on the device

[1221] Data processing: The server sets the basic settings for information collection based on this keyword.

[1222] Output: The set keywords are registered in the system.

[1223] Step 2:

[1224] The server periodically crawls websites on the Internet using BeautifulSoup and collects information related to registered keywords.

[1225] Input: Registered keyword

[1226] Data processing: Extracting text data from website HTML

[1227] Output: The collected text data is temporarily stored on the server.

[1228] Step 3:

[1229] The text data collected by the server is analyzed using SpaCy to extract useful information (e.g., new product announcements, executive personnel changes, etc.).

[1230] Input: Collected text data

[1231] Data processing: Extracting useful information through natural language processing

[1232] Output: The extracted information is registered in the database.

[1233] Step 4:

[1234] The server uses Tweepy to collect and analyze competitors' latest posts and follower counts from social media APIs.

[1235] Input: Registered keyword

[1236] Data processing: Analyzing data obtained from social media APIs

[1237] Output: The parsed information is registered in the database

[1238] Step 5:

[1239] The server uses the NewsAPI to monitor news articles and press releases related to competitors and generate alerts when new information is released.

[1240] Input: Specific keywords

[1241] Data processing: Monitor news feeds and generate notifications when new information is published.

[1242] Output: A notification is sent to the user's device

[1243] Step 6:

[1244] The user inputs a question to the chatbot through the terminal, such as "Please tell me about a new product from a competitor's company."

[1245] Input: User question (prompt)

[1246] Data processing: The server uses the chatbot engine to search the database and extract relevant information.

[1247] Output: The extracted information is provided to the user

[1248] Step 7:

[1249] The server uses Transformers to recognize emotions from the user's dialogue and adjust the dialogue content.

[1250] Input: User interaction

[1251] Data processing: Analyze emotions with an emotion recognition engine and tailor responses accordingly

[1252] Output: An appropriate response is generated according to the user's emotions.

[1253] Step 8:

[1254] Store managers use this system to collect and analyze competitive information and develop strategies for store operations.

[1255] Input: Collected and analyzed competitive information

[1256] Data processing: Formulate operational strategies based on results

[1257] Output: A new strategy for store operations is implemented.

[1258] The above processing steps enable business and store managers to quickly and efficiently collect and analyze competitive information and use it to develop appropriate business strategies.

[1259] 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.

[1260] 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.

[1261] 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.

[1262] [Fourth embodiment]

[1263] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1264] 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.

[1265] 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).

[1266] 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.

[1267] 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.

[1268] 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).

[1269] 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.

[1270] 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.

[1271] 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.

[1272] 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.

[1273] 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.

[1274] 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.

[1275] 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."

[1276] To implement the present invention, the following system configuration and program processing are required.

[1277] System Configuration

[1278] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, sends alerts, and manages the database. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set conflict information and check the results.

[1279] Program processing (natural language explanation)

[1280] 1. User Input

[1281] The user logs in to the system using a terminal and registers the names of competitors and related keywords on the management screen, completing the basic setup for collecting competitor information.

[1282] 2. Performing web crawling

[1283] The server periodically visits websites on the Internet to collect information related to registered keywords and competitor names, and the collected information is temporarily stored on the server.

[1284] 3. Natural Language Processing (NLP)

[1285] The server uses a natural language processing engine to analyze the text data collected by web crawling, and extracts useful competitive information (e.g., new product announcements, executive personnel changes, etc.). The extracted data is stored in a database.

[1286] 4. Social Media Monitoring

[1287] The server uses social media APIs to periodically collect and analyze information such as competitors' latest posts and follower counts. The analyzed data is also stored in a database.

[1288] 5. News Alerts

[1289] The server monitors the specified news feeds and generates alerts to notify the user when new news or press releases about competitors are published.

[1290] 6. Artificial Intelligence Chatbots

[1291] The server responds to user questions using a chatbot engine. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information.

[1292] Specific processing examples

[1293] For example, suppose a user wants to collect competitive information about a company called "ExampleCorp" and registers "ExampleCorp, new product, director personnel changes" as keywords in the system. In this case, the server operates as follows:

[1294] 1. The user enters a keyword from the device and sends it to the server.

[1295] 2. The server performs web crawling based on the registered keywords.

[1296] 3. The data collected by the server is analyzed using a natural language processing engine to extract relevant competitive information.

[1297] 4. The server collects and analyzes relevant information from the social media platform.

[1298] 5. The server monitors news feeds about competitors and generates alerts when new information is published.

[1299] 6. The user asks the chatbot, "Tell me about ExampleCorp's new product," and the server provides the appropriate information.

[1300] In this way, the system of the present invention can collect and analyze competitive information in real time and provide it to users.

[1301] The processing flow will be explained below.

[1302] Step 1:

[1303] A user logs into the system using a terminal, enters their authentication information (username and password), and if authentication is successful, accesses the main dashboard.

[1304] Step 2:

[1305] The user navigates to the admin page, selects the "Competitor Settings" option, enters the competitor name (e.g., ExampleCorp) and related keywords (e.g., new product, director personnel changes), and saves.

[1306] Step 3:

[1307] The device sends the entered competitor name and keywords to the server, which stores them in a database.

[1308] Step 4:

[1309] The server periodically launches the web crawling scheduler, which runs the web crawling tool at the specified interval (e.g., every 6 hours every day).

[1310] Step 5:

[1311] The server loads the list of websites to be collected and uses a web crawler to visit each site, retrieving text data from pages that match the specified competitor name or keywords.

[1312] Step 6:

[1313] The server temporarily stores the collected text data and launches a natural language processing engine to analyze the text and extract specific information (e.g., new product announcements, executive personnel changes).

[1314] Step 7:

[1315] The server stores the analysis results in a database, where they are organized and saved for later reference by the user.

[1316] Step 8:

[1317] The server uses social media APIs to monitor competitors' social media accounts, periodically collecting data on their latest posts and follower counts.

[1318] Step 9:

[1319] The server analyzes the collected social media data, extracts relevant information (e.g., marketing campaign responses, user comments) and stores it in a database.

[1320] Step 10:

[1321] The server monitors the specified news feed URL for new news articles and press releases related to competitors, and generates an alert when relevant information is published.

[1322] Step 11:

[1323] The server notifies the user of the generated alerts. The notifications are delivered to the user via email or internal system notifications.

[1324] Step 12:

[1325] A user launches the chatbot from a terminal and types a question about competitive information, such as "Tell me about ExampleCorp's new product."

[1326] Step 13:

[1327] The device sends the user's question to the server, which analyzes the question using a natural language processing engine and searches for related information in a database.

[1328] Step 14:

[1329] The server passes the search results to the chatbot, which generates an appropriate answer to the question, which is then sent to the device and displayed to the user.

[1330] Step 15:

[1331] The user selects the "Display Competitive Information Results" option from the administration screen. The device retrieves the latest analysis results from the server and displays them in a visualized format for the user.

[1332] Step 16:

[1333] The user can select the option to generate and download a competitive intelligence report if desired. The device will generate the report and provide a download link, such as in PDF format.

[1334] In this way, the system of the present invention quickly and efficiently collects and analyzes information on competitors through a series of processes and provides it to users.

[1335] Example 1

[1336] 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."

[1337] Collecting competitive information effectively and in real time is extremely important for understanding a company's marketing strategy and market trends. However, when information is collected manually, it takes a huge amount of time and effort, and analyzing the collected information is not easy. Furthermore, it is difficult to integrate multiple functions such as web crawling, social media monitoring, news alerts, and chatbots. This makes it difficult to understand competitor trends in a timely manner.

[1338] 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.

[1339] In this invention, the server includes an input means for a user to register specific keywords and competitor names using a terminal, a web crawling means for collecting information related to the specific keywords and competitor names from websites, a natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes, a social media monitoring means for collecting information on competitors' posts and follower numbers from social media platforms, a news alert means for generating alerts when news articles or press releases related to competitors are issued, and an AI chatbot means for providing competitor information through dialogue with users. This makes it possible to effectively collect, analyze, and comprehensively manage competitor information in real time.

[1340] "Input means" is a function that allows a user to register specific keywords and competitor names in the system using a terminal.

[1341] "Web crawling means" is a function that allows a server to crawl websites on the Internet and automatically collect information related to specific keywords and competitor names.

[1342] "Natural language processing means" is a function that analyzes collected text data and extracts specific information such as new product announcements and executive personnel changes. Specifically, it analyzes text using a natural language processing engine.

[1343] "Social media monitoring tools" are functions that collect and analyze information on competitors' posts and follower numbers from social media platforms.

[1344] The "news alert means" is a function that generates an alert and notifies the user when a news article or press release related to a competitor is issued.

[1345] The "artificial intelligence chatbot means" is a function that provides competitive information through dialogue with users. Specifically, it uses a chatbot engine to respond to user questions.

[1346] "Control Measures" refers to a function that integrates and operates web crawling, natural language processing, social media monitoring, news alerts, and AI chatbot functions based on keywords and competitor names set by the user.

[1347] MODE FOR CARRYING OUT THE INVENTION

[1348] To implement the present invention, the following system configuration and program processing are required.

[1349] System Configuration

[1350] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, generates alerts, and manages the database. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set conflict information and check the results.

[1351] Program processing (natural language explanation)

[1352] 1. User Input

[1353] A user logs in to the system using a terminal and registers competitor names and related keywords on the management screen. This operation includes entering keywords in a text field and clicking the "Register" button.

[1354] 2. Performing web crawling

[1355] The server launches a web crawling tool (e.g., Selenium or Scrapy) to collect information related to the registered keywords and competitor names from websites on the Internet. This data is temporarily stored in the server's storage. Specifically, the server searches for URLs that match the keywords and parses the HTML of those web pages to extract text data.

[1356] 3. Natural Language Processing (NLP)

[1357] The server passes the collected text data to a natural language processing engine (e.g., spaCy or NLTK) for analysis. The natural language processing engine tokenizes the text data and extracts important entities (e.g., company names, new product names, executive names, etc.). The extracted information is stored in a database. The server then divides the text data into sentences and performs entity identification for each sentence.

[1358] 4. Social Media Monitoring

[1359] The server prepares a social media API client (e.g., Twitter API client) and periodically calls the API to collect competitors' posts. The collected posts are analyzed, and important data (e.g., increases or decreases in the number of followers, rumors about new products, etc.) is extracted and stored in a database. The server parses the JSON-formatted data received from the API and extracts the necessary information.

[1360] 5. News Alerts

[1361] The server uses a news API (e.g., Google News API) to monitor news feeds and generates alerts when new news or press releases related to competitors are published. The generated alerts are notified to the user. Specifically, the server sets up regular checks of the feed and generates alerts when new entries are found.

[1362] 6. Artificial Intelligence Chatbots

[1363] The server launches a chatbot engine (e.g., ChatGPT or Dialogflow) and provides an interface for accepting user questions. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information. For example, if a user inputs "Tell me about ExampleCorp's new product," the server analyzes the question, retrieves information about the new product from the database, and responds.

[1364] Specific examples

[1365] For example, if a user wants to collect information about a certain company, he or she registers keywords such as "certain company, new product, executive personnel changes" in the system. In this case, the server operates as follows:

[1366] 1. The user enters a keyword from the device and sends it to the server.

[1367] 2. The server performs web crawling using Selenium based on the registered keywords.

[1368] 3. The data collected by the server is analyzed using spaCy to extract relevant competitive information.

[1369] 4. The server collects and analyzes relevant information from the Twitter API.

[1370] 5. The server monitors the news feed via the Google News API and generates an alert when new information is published.

[1371] 6. The user asks the chatbot, "Please tell me about a new product from a certain company," and the server provides the appropriate information.

[1372] In this way, the system of the present invention can collect and analyze competitive information in real time and provide it to users.

[1373] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1374] Step 1:

[1375] A user logs into the system using a terminal and registers the name of a competitor and related keywords on the management screen. The input for this operation is the "competitor name" and "keywords" entered by the user in the text field on the terminal. The output is this information sent to the server. Specifically, the user enters the keywords in the text field on the management screen and clicks the "Register" button.

[1376] Step 2:

[1377] The server performs web crawling based on registered keywords and competitor names. The input for this process is the "keywords" and "competitor names" registered by the user, and the output is the collected text data of websites. The server uses Selenium or Scrapy to automatically crawl related web pages on the Internet, parse the HTML data, and extract the text data.

[1378] Step 3:

[1379] The server passes the collected text data to a natural language processing engine for analysis. The input to this process is the "text data" collected in step 2, and the output is "extracted specific information (e.g., new product announcements, executive personnel changes, etc.)." Specifically, the server inputs the collected text data into spaCy or NLTK, which tokenizes the data and performs entity identification processing. Then, important information is extracted and stored in a database.

[1380] Step 4:

[1381] The server uses social media APIs to collect competitors' posts and follower counts. The inputs for this process are "competitor names" and "API clients," and the output is "collected social media data." The server periodically calls the Twitter API and Facebook API to receive relevant post and follower count data in JSON format. The server then analyzes the data and stores important information in a database.

[1382] Step 5:

[1383] The server monitors the news feed and generates alerts. The inputs for this process are the "news feed URL" and "keywords," and the output is an "alert notification." The server periodically checks for news articles and press releases related to the registered keywords using the Google News API, etc., and generates an alert to notify the user when new information is released.

[1384] Step 6:

[1385] When a user inputs a question to a chatbot using a terminal, the server provides appropriate information in response to the question. The input for this process is the user's "question" and the output is the "response." The server analyzes the question using a chatbot engine (e.g., ChatGPT or Dialogflow), searches for relevant information from a database, and generates a response. Specifically, if a user asks, "Please tell me about a new product from a certain company," the server retrieves information about the new product from the database and presents the answer through the chatbot.

[1386] (Application example 1)

[1387] 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."

[1388] Conventional competitive intelligence analysis systems only handle information such as competitor product announcements and executive personnel changes, and lack the functionality to collect and analyze information related to security risks, making it difficult for companies to respond quickly to security risks.

[1389] 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.

[1390] In this invention, the server includes a web crawling means for collecting information related to specific keywords and competitor names from websites, a natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes, a social media monitoring means for collecting information on competitors' posts and follower numbers from social media platforms, a news alert means for receiving alerts when news articles or press releases related to competitors are issued, an AI chatbot means for collecting competitor information through dialogue with users, and a cybersecurity monitoring means for collecting and analyzing information related to security risks. This enables the collection and analysis of not only information about competitors but also information about security risks, enabling companies to respond to security risks quickly and effectively.

[1391] "Web crawling" is a technique for automatically visiting websites on the Internet and collecting specific information.

[1392] "Natural language processing" is a technology that allows computers to understand and analyze human language and is used to extract specific information.

[1393] "Social media monitoring" is a technology that collects and analyzes information such as posts and follower numbers on social media platforms.

[1394] "News Alert" is a function that notifies users of the contents of specific news articles or press releases when they are published.

[1395] An "artificial intelligence chatbot" is software based on artificial intelligence that collects and provides information through dialogue with users.

[1396] "Information related to security risks" refers to information that may affect information security, such as cyber attacks, vulnerabilities, and phishing attacks.

[1397] "Cybersecurity monitoring" is a technology that collects and analyzes information on security risks related to specific keywords.

[1398] To implement the present invention, the following system configuration and program processing are required.

[1399] System Configuration

[1400] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, sends alerts, and manages the database. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set conflict information and check the results.

[1401] Hardware and software used

[1402] Server: Cloud-based server (e.g. AWS EC2)

[1403] Smartphone: iOS or Android device (app developed with React Native)

[1404] Database: PostgreSQL

[1405] Web crawler: Scrapy

[1406] Natural Language Processing (NLP): spaCy, NLTK

[1407] Social Media APIs: Twitter API, Facebook Graph API

[1408] Chatbot engine: Rasa

[1409] Program processing (natural language explanation)

[1410] server

[1411] The server receives the user's input and executes the following steps:

[1412] 1. Web crawling methods:

[1413] The server uses Scrapy to crawl websites related to registered keywords and competitor names and collect information.

[1414] The collected data is temporarily stored on the server.

[1415] 2. Natural Language Processing Tools:

[1416] The collected text data is analyzed using spaCy and NLTK to extract specific information such as new product announcements and executive personnel changes.

[1417] 3. Social Media Monitoring Methods:

[1418] The server uses the Twitter API and Facebook Graph API to periodically collect and analyze competitors' posts and follower counts.

[1419] 4. News Alert Methods:

[1420] Generate alerts to notify users when news articles or press releases related to competitors are published.

[1421] 5. Artificial Intelligence Chatbot Means:

[1422] Using Rasa, we collect competitive information and provide answers based on user questions.

[1423] 6. Cybersecurity Monitoring Measures:

[1424] It collects and analyzes security risk information related to specific keywords. For example, the server periodically checks for information about phishing attacks and malware and reports it to the user.

[1425] Terminal

[1426] The terminal acts as a user interface and provides the following functions:

[1427] Enter keywords and competitor names

[1428] Viewing analysis results and reports

[1429] Security risk alert notifications

[1430] User

[1431] The user operates the terminal and performs the following operations.

[1432] Registering keywords and competitor names

[1433] Checking the analysis results

[1434] Use the chatbot to ask for more information

[1435] Examples of concrete examples and prompts

[1436] As a concrete example, if a user sets the keywords "new product release phishing attack", the server operates as follows:

[1437] 1. Web crawling: When a specific company announces a new product release, we collect information about related phishing attacks.

[1438] 2. Natural Language Processing: Analyzes collected data and extracts useful information.

[1439] 3. Social media monitoring: Analyze the company's new product posts and related security risks.

[1440] 4. News Alerts: Notify users if a security risk related to a new release is detected.

[1441] 5. Chatbot: Type "What are the security risks of a new product release?" and get real-time details.

[1442] Example prompt sentence:

[1443] "What are the latest phishing attacks related to new product releases?"

[1444] "Show me the analysis results for a specific company's new product releases."

[1445] In this way, the system of the present invention can collect and analyze competitive information and security risks in real time and provide them to users.

[1446] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1447] Step 1:

[1448] The user operates the terminal, inputs and registers specific keywords and competitor names, and the input information is sent to the server. For example, if a user registers keywords such as "new product release phishing attack," this is sent to the server.

[1449] Step 2:

[1450] The server performs web crawling based on the registered keywords and competitor names. Specifically, the server uses Scrapy to crawl specific websites and collect relevant information. The input is the keywords and competitor names, and the output is the collected web data.

[1451] Step 3:

[1452] The server analyzes the collected web data using a natural language processing (NLP) engine. Specifically, the server uses spaCy or NLTK to analyze the text data and extract specific information, such as new product announcements or executive personnel changes. The input is the collected web data, and the output is the data from which the specific information has been extracted.

[1453] Step 4:

[1454] The server monitors the social media activities of competitors. Specifically, the server uses the Twitter API and Facebook Graph API to collect and analyze competitors' posts and follower counts. The input is social media account information, and the output is analyzed social media activity data.

[1455] Step 5:

[1456] The server monitors news articles and press releases related to competitors and generates alerts. When new news related to a specific keyword is published, the server generates an alert and notifies the user. The input is the news feed information and the output is the generated alert.

[1457] Step 6:

[1458] The server performs security risk analysis based on the collected information. Specifically, the server uses its cybersecurity monitoring function to periodically check for information about phishing attacks and malware and provide it to the user. The input is data related to competitors and security risks, and the output is a report on security risks.

[1459] Step 7:

[1460] A user can use the chatbot to request information from their device. For example, if the user types, "Please tell me the latest phishing attack information regarding new product releases," the server uses Rasa to search the relevant database and provide the appropriate information. The input is the user's query, and the output is the corresponding response.

[1461] In this way, the present invention realizes a system that collects and analyzes information step by step and provides the user with necessary competitive information and security risk information.

[1462] 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.

[1463] The present invention is a system that allows companies to quickly and efficiently collect and analyze information on their competitors and use it to formulate their own strategies and develop products. The present invention includes web crawling means, natural language processing means, social media monitoring means, news alert means, and artificial intelligence chatbot means, as well as an emotion recognition engine that recognizes user emotions. Specific embodiments of the present invention and the processing of the program are described below.

[1464] System Configuration

[1465] The system of the present invention consists of a server, a terminal, and a user. The server collects information, analyzes it, generates alerts, manages the database, and recognizes emotions. The terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set competitive information, check the results, and interact with the chatbot.

[1466] Program processing (natural language explanation)

[1467] 1. User Input

[1468] The user logs in to the system using a terminal and registers the names of competitors and related keywords on the management screen, completing the basic setup for collecting competitor information.

[1469] 2. Performing web crawling

[1470] The server periodically visits websites on the Internet to collect information related to registered keywords and competitor names, and the collected information is temporarily stored on the server.

[1471] 3. Natural Language Processing (NLP)

[1472] The server uses a natural language processing engine to analyze the text data collected by web crawling, and extracts useful competitive information (e.g., new product announcements, executive personnel changes, etc.). The extracted data is stored in a database.

[1473] 4. Social Media Monitoring

[1474] The server uses social media APIs to periodically collect and analyze information such as competitors' latest posts and follower counts. The analyzed data is also stored in a database.

[1475] 5. News Alerts

[1476] The server monitors the specified news feed URL and generates alerts when new news or press releases related to competitors are published, and notifies the user of the alerts.

[1477] 6. Artificial Intelligence Chatbots

[1478] The server responds to user questions using a chatbot engine. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information.

[1479] 7. Emotion Recognition Engine

[1480] The server uses an emotion recognition engine to recognize emotions from the user's dialogue and behavior. The emotion data is stored in a database and the system's behavior is adjusted based on the user's emotions.

[1481] Specific processing examples

[1482] For example, if a user wants to collect competitive information about a company called "ExampleCorp" and registers "ExampleCorp, new product, director personnel changes" as keywords in the system, the server operates as follows.

[1483] 1. The user enters a keyword from the device and sends it to the server.

[1484] 2. The server performs web crawling based on the registered keywords.

[1485] 3. The data collected by the server is analyzed using a natural language processing engine to extract relevant competitive information.

[1486] 4. The server collects and analyzes relevant information from the social media platform.

[1487] 5. The server monitors news feeds about competitors and generates alerts when new information is published.

[1488] 6. The user asks the chatbot, "Tell me about ExampleCorp's new product," and the server provides the appropriate information.

[1489] 7. The server recognizes emotions from the user's questions and actions to the chatbot and adjusts the response content based on the emotional data.

[1490] The system of the present invention not only efficiently collects and analyzes competitive information, but also, by combining it with an emotion recognition engine, is able to flexibly respond to the user's emotions, thereby contributing to an improved user experience.

[1491] The processing flow will be explained below.

[1492] Step 1:

[1493] A user logs into the system using a terminal, enters their authentication information (username and password), and if authentication is successful, accesses the main dashboard.

[1494] Step 2:

[1495] The user navigates to the admin page, selects the "Competitor Settings" option, enters the competitor name (e.g., ExampleCorp) and related keywords (e.g., new product, director personnel changes), and saves.

[1496] Step 3:

[1497] The device sends the entered competitor name and keywords to the server, which stores them in a database.

[1498] Step 4:

[1499] The server periodically launches the web crawling scheduler, which runs the web crawling tool at the specified interval (e.g., every 6 hours every day).

[1500] Step 5:

[1501] The server loads the list of websites to be collected and uses a web crawler to visit each site, retrieving text data from pages that match the specified competitor name or keywords.

[1502] Step 6:

[1503] The server temporarily stores the collected text data and launches a natural language processing engine to analyze the text and extract specific information (e.g., new product announcements, executive personnel changes).

[1504] Step 7:

[1505] The server stores the analysis results in a database, where they are organized and saved for later reference by the user.

[1506] Step 8:

[1507] The server uses social media APIs to monitor competitors' social media accounts, periodically collecting data on their latest posts and follower counts.

[1508] Step 9:

[1509] The server analyzes the collected social media data, extracts relevant information (e.g., marketing campaign responses, user comments) and stores it in a database.

[1510] Step 10:

[1511] The server monitors the specified news feed URL for new news articles and press releases related to competitors, and generates an alert when relevant information is published.

[1512] Step 11:

[1513] The server notifies the user of the generated alerts. The notifications are delivered to the user via email or internal system notifications.

[1514] Step 12:

[1515] A user launches the chatbot from a terminal and types a question about competitive information, such as "Tell me about ExampleCorp's new product."

[1516] Step 13:

[1517] The device sends the user's question to the server, which analyzes the question using a natural language processing engine and searches for related information in a database.

[1518] Step 14:

[1519] The server passes the search results to the chatbot, which generates an appropriate answer to the question, which is then sent to the device and displayed to the user.

[1520] Step 15:

[1521] The server activates an emotion recognition engine to determine the user's emotions through user questions and dialogue, and the emotion data is stored in a database.

[1522] Step 16:

[1523] The server takes into account the user's emotional data and adjusts the chatbot's responses, for example, providing more detailed information or offering assistance if the user expresses dissatisfaction.

[1524] Step 17:

[1525] The user selects the "Display Competitive Information Results" option from the administration screen. The device retrieves the latest analysis results from the server and displays them in a visualized format for the user.

[1526] Step 18:

[1527] The user can select the option to generate and download a competitive intelligence report if desired. The device will generate the report and provide a download link, such as in PDF format.

[1528] In this way, the system of the present invention quickly and efficiently collects and analyzes information on competitors through a series of processes and provides it to users.

[1529] Example 2

[1530] 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."

[1531] It is extremely important for companies to quickly and efficiently collect and analyze information about their competitors and use it to formulate their own strategies and develop products. However, current methods require time to collect and analyze information, making it difficult to make quick decisions. Furthermore, the collected information contains a lot of noise, making it difficult to extract useful information. Furthermore, there is a need for flexible systems that respond based on user sentiment, but current systems are unable to do so. The purpose of this invention is to solve these problems and enable companies to efficiently collect and analyze competitive information and make quick decisions.

[1532] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: information collection means for collecting information related to specific keywords and competitor names from websites; natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes; social media analysis means for collecting information on competitor posts and follower counts from social media platforms; notification means for generating alerts and notifying users when news articles or press releases related to competitors are published; interactive agent means for providing competitive information through dialogue with the user; and emotion recognition means for recognizing user emotions and adjusting system operation. This enables companies to efficiently collect and analyze competitive information and make quick decisions. Furthermore, flexible responses based on user emotions can also be realized.

[1533] "Information Gathering Tools" are tools or software used to automatically gather information related to specific keywords and competitor names from websites.

[1534] "Natural language processing means" refers to the technology and software used to analyze collected text data and extract useful information.

[1535] "Social media analytics tools" refer to technologies and software used to collect and analyze competitors' posts and follower numbers from social media platforms.

[1536] "Notification means" refers to a system or function that generates an alert and notifies users when a news article or press release related to a competitor is issued.

[1537] "Interactive agent means" refers to chatbot technology that uses artificial intelligence to provide competitive information through dialogue with users.

[1538] "Emotion recognition means" refers to the technology and software for recognizing emotions from user interactions and operations and adjusting the system's behavior.

[1539] This invention is a system that allows companies to quickly and efficiently collect and analyze information on their competitors and use it to formulate their own strategies and develop products. The system mainly consists of a server, a terminal, and a user. The server collects information, analyzes it, generates notifications, manages the database, and recognizes emotions, while the terminal accepts input from the user, displays the results, and generates reports. The user operates the terminal to set competitive information, check the results, and interact with the chatbot.

[1540] Hardware and software used

[1541] server

[1542] 1. Information collection method: The server uses a web crawling tool such as "Scrapy" to automatically crawl websites on the Internet and collect information related to specific keywords and competitor names. The collected data is temporarily stored in a database such as "MongoDB."

[1543] 2. Natural language processing: The server uses tools like "spaCy" and "NLTK" to analyze the collected text data and extract useful information, such as "new product announcements" and "executive personnel changes," and stores this information in a database.

[1544] 3. Social media analysis: The server uses the Twitter API and Facebook Graph API to periodically collect and analyze information such as competitors' latest posts and follower numbers. The analyzed data is stored in a database.

[1545] 4. Notification Method: The server uses the Google News API and RSS feeds to monitor news articles and press releases related to competitors, and when new information is released, it generates an alert and notifies the user's device.

[1546] 5. Conversational Agent: The server uses chatbot engines such as Dialogflow and Rasa to respond to user questions. When a user inputs a question about competitive information, the chatbot searches the database and provides relevant information.

[1547] 6. Emotion Recognition: The server uses emotion recognition engines such as IBM Watson Tone Analyzer and Microsoft Azure Emotion API to recognize emotions from the user's interactions and actions. The recognized emotion data is stored in a database and the system's behavior is adjusted based on the user's emotions.

[1548] Terminal

[1549] 1. Accepting user input: The terminal provides an interface for accepting input from the user. For example, the user can register competitor names and related keywords on the management screen on the browser.

[1550] 2. Displaying Results: The device displays the analyzed data and alerts to the user, including the collected competitive information and analysis results.

[1551] 3. Report generation: The terminal generates a report based on the collected and analyzed data and provides it to the user.

[1552] Examples of concrete examples and prompts

[1553] For example, if a user wants to collect the latest information about "Competitor A," they can input keywords such as "new product announcement" and "management change" into the system. The server then performs web crawling, analyzes the collected data using a natural language processing engine, and extracts useful information. Using social media analysis tools, the server collects and analyzes "Competitor A's" latest posts and changes in the number of followers. It also monitors news articles and press releases related to "Competitor A" and notifies the user when new information is released. Furthermore, the user can use a chatbot to input questions such as "Tell me about Competitor A's new product," and the chatbot will search the database and provide relevant information. The server recognizes the user's emotions from their interactions and actions and adjusts the response accordingly.

[1554] Prompt Sentence Examples

[1555] "Collect the latest competitive information about competitor A."

[1556] "Please tell me about competitor A's new product."

[1557] "Check out competitor A's social media activity."

[1558] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1559] Step 1: User Input

[1560] The user logs into the system using a terminal and registers the name of the competitor and related keywords on the management screen. For example, they enter keywords such as "Competitor A," "New product announcement," and "Changes in management." When this input is sent to the server, the conditions for collecting competitive information are set and the basic setup is complete.

[1561] Input: Competitor name (Competitor A), related keywords (new product announcement, management changes)

[1562] Output: Basic setup for competitive intelligence gathering completed

[1563] Step 2: Perform a web crawl

[1564] The server uses Scrapy to crawl websites on the Internet based on set keywords. For example, it automatically collects blogs and news articles related to competitor A. The collected information is temporarily stored in MongoDB.

[1565] Input: Competitor name, related keywords

[1566] Output: Collected information (raw)

[1567] Step 3: Natural Language Processing (NLP)

[1568] The server uses "spaCy" or "NLTK" to analyze the collected text data and extract useful information. For example, specific information such as "Competitor A has announced a new product" or "The director has been transferred" is identified and stored in a database.

[1569] Input: Collected text data

[1570] Output: Extracted useful information (e.g., new product launches, executive personnel changes)

[1571] Step 4: Social Media Monitoring

[1572] The server uses the Twitter API and Facebook Graph API to periodically collect the latest posts and changes in the number of followers of competitor A. The collected data is analyzed, and specific information such as "Competitor A's new tweets" and "increased followers" is stored in a database.

[1573] Input: Competitor's social media account information

[1574] Output: Parsed social media data

[1575] Step 5: Generate a news alert

[1576] The server uses the Google News API and RSS feeds to monitor news articles and press releases related to competitor A. For example, if news comes out that competitor A has announced a new product, an alert is immediately generated and the user is notified.

[1577] Input: News feed URL

[1578] Output: Generated alert notification

[1579] Step 6: Artificial Intelligence Chatbots

[1580] A user accesses the chatbot using a device and inputs a question such as, "Please tell me about Competitor A's new product." The server uses Dialogflow to analyze the question, searches the database, and provides relevant information. It then returns a specific answer to the user, such as, "Competitor A has announced a new smartphone."

[1581] Input: User question

[1582] Output: Chatbot response

[1583] Step 7: Emotion Recognition

[1584] The server uses IBM Watson Tone Analyzer to recognize emotions from the user's dialogue and actions. For example, if the user is emotionally charged, the server adjusts the dialogue accordingly. This emotional data is stored in a database.

[1585] Input: User interaction content, operation information

[1586] Output: Emotion recognition results, adjusted dialogue content

[1587] (Application example 2)

[1588] 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."

[1589] Modern companies need to quickly and efficiently collect and analyze information about their competitors, but they lack the appropriate systems to do so. There is also a need for integrated support tools that enable store managers to collect and analyze competitive information and utilize it in store operations. Furthermore, there is a lack of systems that recognize user emotions and adjust interactions. There is a need to resolve these issues and support corporate strategy planning, product development, and efficient store operations.

[1590] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1591] In this invention, the server includes a web crawling means for collecting information related to specific keywords and competitor names from websites, a natural language processing means for analyzing the collected text data and extracting specific information such as new product announcements and executive personnel changes, a social media monitoring means for collecting information on competitors' posts and follower numbers from social media platforms, a news alert means for receiving alerts when news articles or press releases related to competitors are issued, an AI chatbot means for collecting competitor information through dialogue with users, an emotion recognition means for recognizing user emotions and adjusting the content of the dialogue based on the emotions, and a smart store management means for allowing store managers to collect and analyze competitor information and use it in store operations. This enables companies to efficiently collect and analyze competitor information and effectively use it in store operations.

[1592] "Web crawling" is a technique for automatically collecting information from websites.

[1593] "Natural language processing" is a technology that uses computers to analyze, understand, and generate human language.

[1594] "Social media monitoring" is a technique for monitoring and collecting activity on social media.

[1595] "News Alert" is a technology that notifies you when news articles or press releases related to specified keywords are published.

[1596] An "artificial intelligence chatbot" is a system that provides and collects information through dialogue with users.

[1597] "Emotion recognition" is a technology that estimates and recognizes a user's emotions from their words, actions, and facial expressions.

[1598] "Smart Store Management" is an integrated support system that allows store managers to collect and analyze competitive information and utilize it in store operations.

[1599] This invention is a system that allows companies to quickly and efficiently collect and analyze information on their competitors and use it to formulate their own strategies and develop products. This system incorporates web crawling, natural language processing, social media monitoring, news alerts, AI chatbots, emotion recognition, and smart store management. We will explain the details of each method and how the entire system works.

[1600] Hardware and Software

[1601] The system consists of a server, user terminals, and a network. The hardware used includes regular desktop PCs, smartphones, and servers. The software uses the following technologies:

[1602] BeautifulSoup: Used to extract information from web pages.

[1603] SpaCy: Used for natural language processing.

[1604] Tweepy: Used to collect data from social media (Twitter).

[1605] Transformers (Hugging Face): Used for emotion recognition and chatbots.

[1606] NewsAPI: Used to collect news articles.

[1607] System Features

[1608] Web crawling

[1609] The server crawls websites based on registered keywords using BeautifulSoup and collects related information, which is then temporarily stored on the server in text format.

[1610] Natural Language Processing

[1611] The collected text data is analyzed on the server using SpaCy to extract useful information such as new product announcements and executive personnel changes, and the most relevant data is then stored in a database.

[1612] Social Media Monitoring

[1613] The server uses Tweepy to collect and analyze data on competitors' latest posts and follower numbers from social media APIs (such as Twitter), and the analysis data is stored in its own database.

[1614] News Alerts

[1615] The server uses the NewsAPI to alert users when news articles or press releases related to specific keywords are published, via email or in-app notifications.

[1616] Artificial Intelligence Chatbot

[1617] The server uses a chatbot engine based on Transformers to respond to user questions. For example, if a user asks, "Tell me about a new product from a competitor's company," the chatbot will search the database and provide relevant information.

[1618] emotion recognition

[1619] The server uses Transformers' emotion recognition engine to analyze emotions from user interactions, allowing it to tailor the chatbot's responses based on the user's emotional state.

[1620] Smart store management

[1621] Store managers can use this system to collect competitive information and develop store management strategies based on the analysis results, helping them maintain an advantage over their competitors.

[1622] Specific examples

[1623] For example, if a user asks "What is the latest information on a new product from a competitor's name?" the system will do the following:

[1624] Perform web crawling and collect relevant information.

[1625] Analyze and extract collected text data using natural language processing.

[1626] Collect the latest information on social media through social media monitoring.

[1627] News alerts detect new news articles and notify you accordingly.

[1628] An artificial intelligence chatbot responds to questions and provides relevant information from a database.

[1629] Emotion recognition generates responses based on the user's emotions.

[1630] Prompt Sentence Examples

[1631] "Please give me the latest information on new products from competitors' names."

[1632] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1633] Step 1:

[1634] A user logs into the system using a terminal and registers keywords such as "competitor company name, new product, executive personnel changes" on the administration screen.

[1635] Input: Keywords entered by the user on the device

[1636] Data processing: The server sets the basic settings for information collection based on this keyword.

[1637] Output: The set keywords are registered in the system.

[1638] Step 2:

[1639] The server periodically crawls websites on the Internet using BeautifulSoup and collects information related to registered keywords.

[1640] Input: Registered keyword

[1641] Data processing: Extracting text data from website HTML

[1642] Output: The collected text data is temporarily stored on the server.

[1643] Step 3:

[1644] The text data collected by the server is analyzed using SpaCy to extract useful information (e.g., new product announcements, executive personnel changes, etc.).

[1645] Input: Collected text data

[1646] Data processing: Extracting useful information through natural language processing

[1647] Output: The extracted information is registered in the database.

[1648] Step 4:

[1649] The server uses Tweepy to collect and analyze competitors' latest posts and follower counts from social media APIs.

[1650] Input: Registered keyword

[1651] Data processing: Analyzing data obtained from social media APIs

[1652] Output: The parsed information is registered in the database

[1653] Step 5:

[1654] The server uses the NewsAPI to monitor news articles and press releases related to competitors and generate alerts when new information is released.

[1655] Input: Specific keywords

[1656] Data processing: Monitor news feeds and generate notifications when new information is published.

[1657] Output: A notification is sent to the user's device

[1658] Step 6:

[1659] The user inputs a question to the chatbot through the terminal, such as "Please tell me about a new product from a competitor's company."

[1660] Input: User question (prompt)

[1661] Data processing: The server uses the chatbot engine to search the database and extract relevant information.

[1662] Output: The extracted information is provided to the user

[1663] Step 7:

[1664] The server uses Transformers to recognize emotions from the user's dialogue and adjust the dialogue content.

[1665] Input: User interaction

[1666] Data processing: Analyze emotions with an emotion recognition engine and tailor responses accordingly

[1667] Output: An appropriate response is generated according to the user's emotions.

[1668] Step 8:

[1669] Store managers use this system to collect and analyze competitive information and develop strategies for store operations.

[1670] Input: Collected and analyzed competitive information

[1671] Data processing: Formulate operational strategies based on results

[1672] Output: A new strategy for store operations is implemented.

[1673] The above processing steps enable business and store managers to quickly and efficiently collect and analyze competitive information and use it to develop appropriate business strategies.

[1674] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1675] 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.

[1676] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1677] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1678] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1679] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1680] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1681] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1682] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1683] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1684] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1685] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1686] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1687] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1688] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1689] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1690] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1691] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1692] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1693] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1694] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1695] The following is further disclosed regarding the above embodiment.

[1696] (Claim 1)

[1697] a web crawling means for collecting information related to specific keywords and competitor names from websites;

[1698] Natural language processing means to analyze the collected text data and extract specific information such as new product announcements and executive personnel changes;

[1699] Social media monitoring tools to gather information on competitors' posts and follower numbers from social media platforms;

[1700] News alerts to receive alerts when news articles or press releases related to competitors are issued;

[1701] An artificial intelligence chatbot means for collecting competitive intelligence through user interaction;

[1702] A system including:

[1703] (Claim 2)

[1704] 2. The system according to claim 1, further comprising an analysis means for analyzing information on competitors' social media activities to understand their marketing strategies and customer responses.

[1705] (Claim 3)

[1706] The system of claim 1, further comprising a control means for integrating and operating the means of web crawling, natural language processing, social media monitoring, news alerts, and artificial intelligence chatbots based on keywords and competitor names set by the user.

[1707] "Example 1"

[1708] (Claim 1)

[1709] an input means for a user to register specific keywords and competitor names using a terminal;

[1710] a web crawling means for collecting information related to specific keywords and competitor names from websites;

[1711] Natural language processing means to analyze the collected text data and extract specific information such as new product announcements and executive personnel changes;

[1712] Social media monitoring tools to gather information on competitors' posts and follower numbers from social media platforms;

[1713] News alerting means for generating alerts when news articles or press releases related to competitors are issued;

[1714] an artificial intelligence chatbot means for providing competitive information through dialogue with a user;

[1715] A system including:

[1716] (Claim 2)

[1717] 2. The system according to claim 1, further comprising an analysis means for analyzing information on competitors' social media activities to understand their marketing strategies and customer responses.

[1718] (Claim 3)

[1719] The system of claim 1 further comprising a control means for integrating and operating the means of web crawling, natural language processing, social media monitoring, news alerts, and artificial intelligence chatbots based on keywords and competitor names set by the user.

[1720] "Application Example 1"

[1721] (Claim 1)

[1722] a web crawling means for collecting information related to specific keywords and competitor names from websites;

[1723] Natural language processing means to analyze the collected text data and extract specific information such as new product announcements and executive personnel changes;

[1724] Social media monitoring tools to gather information on competitors' posts and follower numbers from social media platforms;

[1725] News alerts to receive alerts when news articles or press releases related to competitors are issued;

[1726] An artificial intelligence chatbot means for collecting competitive intelligence through user interaction;

[1727] cybersecurity monitoring means for collecting and analyzing information related to security risks;

[1728] A system including:

[1729] (Claim 2)

[1730] 2. The system according to claim 1, further comprising an analysis means for analyzing information on competitors' social media activities to understand their marketing strategies and customer responses.

[1731] (Claim 3)

[1732] The system of claim 1 further comprising a control means for integrating and operating the means of web crawling, natural language processing, social media monitoring, news alerts, artificial intelligence chatbots, and cybersecurity monitoring based on keywords and competitor names set by the user.

[1733] "Example 2: Combining Emotion Engines"

[1734] (Claim 1)

[1735] an information gathering means for gathering information related to specific keywords and competitor names from websites;

[1736] Natural language processing means to analyze the collected text data and extract specific information such as new product announcements and executive personnel changes;

[1737] Social media analytics tools to gather information about competitors' posts and follower counts from social media platforms;

[1738] A notification mechanism to generate alerts and notify users when news articles or press releases related to competitors are issued;

[1739] an interactive agent means for providing competitive information through interaction with a user;

[1740] emotion recognition means for recognizing the user's emotions and adjusting the system's behavior;

[1741] A system including:

[1742] (Claim 2)

[1743] 2. The system according to claim 1, further comprising an analysis means for analyzing information on competitors' social media activities to understand their marketing strategies and customer responses.

[1744] (Claim 3)

[1745] The system of claim 1 further comprising a control means for integrating and operating the means of information gathering, natural language processing, social media analysis, notification, and interactive agents based on keywords and competitor names set by the user.

[1746] "Application example 2 when combining emotion engines"

[1747] (Claim 1)

[1748] a web crawling means for collecting information related to specific keywords and competitor names from websites;

[1749] Natural language processing means to analyze the collected text data and extract specific information such as new product announcements and executive personnel changes;

[1750] Social media monitoring tools to gather information on competitors' posts and follower numbers from social media platforms;

[1751] News alerts to receive alerts when news articles or press releases related to competitors are issued;

[1752] An artificial intelligence chatbot means for collecting competitive intelligence through user interaction;

[1753] emotion recognition means for recognizing an emotion of a user and adjusting dialogue content based on the emotion;

[1754] A smart store management tool that allows store managers to collect and analyze competitive information and utilize it for store management.

[1755] A system including:

[1756] (Claim 2)

[1757] 2. The system according to claim 1, further comprising an analysis means for analyzing information on competitors' social media activities to understand their marketing strategies and customer responses.

[1758] (Claim 3)

[1759] The system of claim 1, further comprising a control means for integrating and operating the means of web crawling, natural language processing, social media monitoring, news alerts, and artificial intelligence chatbots based on keywords and competitor names set by the user. [Explanation of symbols]

[1760] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a web crawling means for collecting information related to specific keywords and competitor names from websites; Natural language processing means to analyze the collected text data and extract specific information such as new product announcements and executive personnel changes; Social media monitoring tools to gather information on competitors' posts and follower numbers from social media platforms; News alerts to receive alerts when news articles or press releases related to competitors are issued; An artificial intelligence chatbot means for collecting competitive intelligence through user interaction; A system including:

2. The system according to claim 1, further comprising an analysis means for analyzing information on the social media activities of competitors to understand their marketing strategies and customer responses.

3. The system of claim 1 further comprising a control means for integrating and operating the means of web crawling, natural language processing, social media monitoring, news alerts, and artificial intelligence chatbots based on keywords and competitor names set by the user.

Images