Automated Business Entity Research via Secondary Term Detection
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Solution Overview
Problem
Conventional online tools for researching business entities are time-consuming, requiring extensive manual labor to identify relevant information, making it difficult to find suitable business relationships and avoid irrelevant entities.
Innovation Solution
A method involving a user interface to obtain search terms, parse messages, detect relevant secondary search terms, and generate signals to represent reports on entities matching these terms, utilizing web crawlers and real-simple-syndication feeds to automate the process of connecting relevant business entities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional online tools are used to research business entities, then comprehensive information can be obtained, but the process requires extensive manual labor and time
Solution Approach 1:
The system automatically performs business entity research by crawling web content, parsing messages, detecting relevant terms, and generating reports without requiring manual intervention. The automated workflow includes obtaining search terms, crawling content items, parsing messages to detect secondary search terms, and generating research reports, thereby eliminating the need for extensive manual labor while maintaining comprehensive information gathering
Solution Approach 2:
The patent replaces manual mechanical research processes with an automated computational system. Instead of manually reviewing search results and extracting information, the system uses web crawlers to automatically obtain content items, parses messages using text processing algorithms, detects relevant secondary search terms, and generates reports through automated workflows, substituting human manual labor with machine-based processes
2Measurement precision
If manual research methods are used to identify relevant business entities, then accurate information can be found, but the process is unduly time-consuming
Solution Approach 1:
The system continuously performs research tasks through an automated workflow that operates without interruption. The process continuously obtains search terms, crawls content items, parses messages, detects relevant terms, and generates reports in an unbroken sequence, eliminating the intermittent nature of manual research and maintaining continuous productive action to reduce overall research time while preserving accuracy
Solution Approach 2:
The system performs preliminary actions by automatically obtaining search terms and crawling content items before the main analysis phase. The web crawler pre-fetches relevant content items based on search terms, and the system prepares message parsing and term detection in advance, thereby reducing the overall research time by completing preparatory tasks automatically before detailed analysis is required
Data Source
AI summary
Briefly, example methods, apparatuses, and/or articles of manufacture may be implemented to receive or obtain, responsive to transmitting the one or more search terms to a search entity, one or more primary content items that include messages that accord with the one or more search terms. The method may additionally include parsing the messages that accord with the one or more search terms to detect one or more relevant secondary search terms and obtaining secondary content items that accord with the one or more relevant secondary search terms. The method may further include generating signals to represent a report of entities that accord with the one or more relevant secondary search terms.