User-Guided Search Query Expansion for Precision and Completeness
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Solution Overview
Problem
Current search technologies often yield incomplete results by limiting searches to exact matches, missing relevant information that includes related terms or misspellings of the initial search query.
Innovation Solution
A device and method that expand an initial search query using various techniques such as misspelling analysis, semantic relatedness analysis, alias analysis, and containment analysis to generate a set of expanded search queries, allowing for the identification of relevant sections in a text that may not contain an exact match.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If search technologies limit searches to exact matches, then search precision is improved, but search completeness deteriorates
Solution Approach 1:
The search query is segmented into multiple components (terms, phrases, concepts) and each component is searched separately using different techniques. This allows the system to maintain precision for exact matches while also capturing related terms and concepts that may have been misspelled or expressed differently, thus improving search completeness without sacrificing precision.
Solution Approach 2:
An intermediary search query expansion mechanism is introduced between the user's original query and the final search execution. This intermediary layer analyzes the query, identifies related terms and concepts, and generates multiple expanded queries that capture both exact matches and variations, thereby resolving the contradiction between precision and completeness.
2Loss of information
If search technologies use multiple expansion techniques, then search completeness is improved, but device complexity increases
Solution Approach 1:
A universal search query expansion system is designed that can perform multiple functions (misspelling correction, synonym expansion, concept expansion, phrase extraction) using a unified architecture. This multi-functional approach improves search completeness by handling various query variations while avoiding the complexity of separate dedicated systems for each function.
Solution Approach 2:
The system performs preliminary analysis of the search query to identify key terms, concepts, and potential variations before executing the actual search. This preliminary action includes analyzing query structure, identifying related terms, and preparing expanded queries in advance, which simplifies the overall search process while maintaining high completeness.
Data Source
AI summary
A device may receive information that identifies a search query to be used to search a text. The device may provide information that identifies multiple search query expansion techniques for expanding the search query. The device may receive a selection of one or more search query expansion techniques, of the multiple search query expansion techniques, to be performed to expand the search query. The device may perform the one or more search query expansion techniques to generate a set of expanded search queries based on the search query and the text. The device may search the text, using the set of expanded search queries, to identify multiple sections of the text that include an expanded search query included in the set of expanded search queries. The device may provide search results that identify the multiple sections of the text based on searching the text.