Search Relevance Scoring via Textual Match Segmentation
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Solution Overview
Problem
Conventional search engines struggle to provide high-quality search results due to the sheer volume of information, where users often access only a limited number of results, as the rank ordering does not accurately reflect the relevance of search results to the user's query.
Innovation Solution
A method and system that assigns relevance scores to Internet-accessible information items based on the closeness of textual matches with the search terms, categorizing items into groups such as exact matches, partial matches, and matches within titles or descriptions, to prioritize and order search results effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional search engines use general relevancy ranking algorithms, then a large volume of search results can be generated, but the quality and accuracy of the ranked results deteriorate
Solution Approach 1:
The patent segments search results into distinct categories (exact match, partial match, contained match, no match) based on the degree of textual correspondence between search terms and information items. This segmentation allows the system to handle different match qualities differently, improving ranking accuracy while maintaining comprehensive result coverage.
Solution Approach 2:
The patent applies different relevance scoring rules to different portions of information items. Specifically, it evaluates the title field separately from the body field, assigning higher weights to title matches. This local quality approach ensures that information items with relevant titles are prioritized, improving the overall accuracy of the relevancy ranking.
2Quantity of substance
If search results are ordered by general relevancy algorithms, then comprehensive coverage of information is achieved, but user efficiency in finding high-quality results decreases
Solution Approach 1:
The patent performs preliminary sorting of search results by relevance score before presenting them to the user. By pre-organizing results in descending order of relevance, the system ensures that the most valuable information appears first, allowing users to access high-quality results efficiently without having to sift through irrelevant content.
Solution Approach 2:
The patent replaces manual or generic sorting mechanisms with an automated relevance scoring system that objectively evaluates and ranks information items based on textual match quality. This substitution enables comprehensive result coverage while simultaneously optimizing user efficiency through accurate automatic ranking.
3Measurement precision
If detailed textual matching analysis is performed on all search results, then the accuracy of relevance scoring is improved, but the computational complexity and processing time increase
Solution Approach 1:
The patent segments the textual analysis process into distinct evaluation stages: first checking for exact matches, then partial matches, then contained matches, and finally no matches. This segmented approach improves scoring accuracy by systematically evaluating different match qualities while managing computational complexity through a structured hierarchy of checks.
Solution Approach 2:
The patent changes the parameter of textual matching from binary (match/no match) to a multi-level scale (exact match, partial match, contained match, no match). This parameter change enables more accurate relevance scoring by distinguishing between different degrees of textual correspondence, while the systematic evaluation method keeps processing complexity manageable.
Data Source
AI summary
A method for performing an Internet search is provided. The method includes: receiving a textual input that includes at least one search term; using the at least one search term to identify a plurality of Internet-accessible information items that relate to the at least one search term; assigning a respective relevance score to each item of the identified plurality of Internet-accessible information items, such that each respective relevance score is based on a degree of closeness of a textual match between the corresponding information item and the at least one search term; and outputting an ordered list of results, the order of which is based on the relevance scores.