Information Segmentation System for Search Result Prioritization
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Solution Overview
Problem
Current search engines fail to effectively segment information, leading to a lack of tailored results for users, as they do not adequately categorize products, services, websites, or users' interests, and cannot efficiently compare and correlate different types of data, resulting in inefficient product suggestions and cumbersome search parameter modifications.
Innovation Solution
A system and method that segment information by displaying topic lists, allowing users to select topics, questions, and response forms, and providing filters and tracking overlays to sort and prioritize content, enabling users to manage profiles and compare them with correlated content, and generate pre-generated compounded topics for enhanced search functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If search engines present a large number of websites to users, then the coverage of search results is improved, but the user's ability to find relevant information deteriorates due to information overload
Solution Approach 1:
The patent segments information by creating multiple organized categories and subcategories within search results. Instead of presenting a flat list of websites, the system divides results into structured groups (e.g., product categories, service types, informational sections) that are easier for users to navigate and find relevant content quickly.
Solution Approach 2:
The patent introduces additional organizational dimensions beyond simple keyword matching. By adding categorical dimensions, hierarchical structures, and multiple classification levels, the system transforms the one-dimensional search result list into a multi-dimensional information space that users can explore through various pathways.
2Productivity
If suggestion engines use other customers' usage habits as a base, then product recommendations are generated, but the accuracy of suggestions deteriorates due to low correlating data
Solution Approach 1:
The patent implements preliminary action by collecting and organizing user profile data, preferences, and behavioral patterns in advance. Instead of relying solely on reactive usage habits, the system pre-processes user information to create comprehensive profiles that enable more accurate real-time suggestions without requiring extensive analysis of low-correlating data.
Solution Approach 2:
The patent incorporates feedback mechanisms where user interactions with suggestions and search results are continuously monitored and fed back into the recommendation system. This feedback loop allows the system to learn from user responses and improve suggestion accuracy over time by adjusting recommendations based on actual user preferences and behaviors.
3Measurement precision
If users are required to enter detailed data into the system, then personalized recommendations improve, but the time required for data entry deteriorates
Solution Approach 1:
The patent implements self-service by automatically collecting user data from multiple sources including search behavior, browsing patterns, purchase history, and interaction with the system. Instead of requiring users to manually enter detailed information, the system autonomously gathers and processes data to create and update user profiles, significantly reducing the time users must invest while maintaining high accuracy.
Solution Approach 2:
The patent creates a universal data collection framework that serves multiple functions simultaneously. The same data collection mechanisms support user profiling, recommendation generation, search personalization, and system improvement, eliminating the need for separate data entry processes for each function and reducing overall user burden.
4Measurement precision
If search engines require users to modify search parameters, then search precision improves, but the complexity of the search process deteriorates
Solution Approach 1:
The patent implements dynamic search parameter adjustment based on user behavior and context. Instead of requiring users to manually configure multiple parameters, the system automatically adapts search criteria based on user profiles, historical behavior, and real-time context, dynamically optimizing search precision while keeping the interface simple and intuitive.
Data Source
AI summary
A system and a computer-implemented method of gathering data on at least one website is provided where by placing a tracking overlay on a website, the tracking overlay operates independently from any concurrently active program, appearing concurrently within a user interface, allowing for work with said concurrently active program. The work including capturing data within said tracking overlay, including a plurality of identifying markers of said data from the website; and storing the data, including said plurality of identifying markers within at least one database. The stored data includes classifying the data and images with tags and meta-data.