Search Query Hierarchical Interpretation for Relevance
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Solution Overview
Problem
Search engines fail to provide relevant Web pages because they do not interpret the hierarchical meaning of search terms, instead returning pages that merely contain the search terms or their variations.
Innovation Solution
A computer-implemented method that parses search queries into combinations of adjacent search terms, determines hierarchical relationships using taxonomy data, generates interpretations based on these relationships, and performs searches to identify relevant results, thereby providing more accurate search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If search engines use traditional keyword matching algorithms, then the search process is simple and fast, but the relevance of search results deteriorates because hierarchical meaning is not interpreted
Solution Approach 1:
The search query is segmented into individual terms, and each term is further analyzed for hierarchical relationships. The patent divides the search processing into discrete steps: term extraction, hierarchy level determination, and weighted scoring. This segmentation allows the complex task of hierarchical interpretation to be broken down into manageable components that can be processed systematically
Solution Approach 2:
The patent introduces hierarchical taxonomy data as an intermediary layer between the search query and the search results. This intermediary structure (such as ontologies or knowledge graphs) mediates the relationship between keywords and documents, enabling the system to interpret the intended meaning of search terms by determining their hierarchy levels and relationships within the taxonomy
2Reliability
If search engines interpret hierarchical meaning of search terms, then search result relevance improves, but processing time and computational resources increase
Solution Approach 1:
The hierarchical taxonomy data is pre-computed and organized before search operations. Hierarchy levels for terms are determined in advance and stored, so that during actual search execution, the system only needs to look up pre-determined hierarchy levels rather than computing them from scratch. This preliminary action significantly reduces processing time during query execution
Solution Approach 2:
The patent changes the parameter of term importance from binary (present/absent) to continuous (hierarchy-based weights). By assigning different weights based on hierarchy levels and relationships, the system transforms the search ranking problem into a weighted scoring problem that can be solved more efficiently than full semantic analysis while still capturing hierarchical meaning
3Productivity
If search engines only match search terms literally, then processing is straightforward, but the ability to retrieve intended information deteriorates
Solution Approach 1:
The patent replaces the mechanical keyword-matching system with a semantic interpretation system based on hierarchical relationships. Instead of simply checking for term presence, the system uses hierarchy level comparisons and relationship analysis to infer user intent. This substitution transforms the search mechanism from literal matching to meaning-based retrieval
Data Source
AI summary
A computer-implemented method may include receiving, from a device, a search query that includes search terms, parsing the search terms into combinations of search terms, where each of the combinations includes one or more adjacent search terms, determining whether a hierarchical relationship exists for the one or more adjacent search terms of each of the combinations, generating one or more interpretations for each of the combinations based on whether the hierarchical relationship exists for the one or more adjacent search terms, performing a search based on at least one of the one or more interpretations to identify search results, generating a search result document containing the search results, and providing, to the device, the search result document.