Search Result Explanation System for Query Expansion and Relevance Scoring
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Solution Overview
Problem
Existing search modalities fail to provide effective explanations for search results, making it difficult for users to assess relevance and improve their search strategies, especially in large databases like family history records.
Innovation Solution
The system provides search-result explanations by determining scores for specific query components and results, offering insights into match types and suggesting improvements to the search query, such as narrowing or broadening search criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the search engine returns a large number of results to ensure comprehensive coverage, then the completeness of search results is improved, but the time and effort required for users to evaluate and locate relevant results increases significantly
Solution Approach 1:
The patent segments the search result evaluation process by providing structured explanations that break down match quality into distinct components (e.g., field-level match scores, match types). This allows users to quickly assess relevance without manually examining entire results, resolving the contradiction between comprehensive results and evaluation time.
Solution Approach 2:
The system performs preliminary analysis of search results by pre-computing and displaying match quality explanations before users interact with results. This preliminary action includes calculating match scores, identifying match types, and generating explanatory text, thereby reducing the time users need to spend evaluating each result.
2Ease of operation
If the search engine provides detailed information about each result to help users assess relevance, then the ease of operation is improved, but the complexity of the search interface increases
Solution Approach 1:
The patent applies local quality by providing detailed match explanations only where needed - specifically at the result level and field level - rather than overwhelming the entire interface. Users can access detailed match quality information for specific results without it cluttering the overall search interface, thus improving ease of operation while controlling complexity.
Solution Approach 2:
The system adds a new dimension to search results by including match quality explanations as a separate layer of information. This dimensional addition provides reassessment capability without fundamentally restructuring the existing search interface, allowing users to evaluate relevance through the new explanation dimension while maintaining interface simplicity.
3Loss of information
If the search engine provides explanations for match quality to help users understand result relevance, then the loss of information is reduced, but the device complexity increases
Solution Approach 1:
The system implements self-service by automatically generating and displaying match quality explanations without requiring user intervention or external tools. The search engine itself performs the analysis and presents the information, reducing the need for additional systems or manual assessment processes while minimizing information loss.
4Measurement precision
If users manually evaluate each search result to determine relevance, then the measurement precision of result relevance is improved, but the productivity of the search process decreases
Solution Approach 1:
The patent implements feedback by providing users with structured match quality information that directly reflects the relevance assessment criteria. This feedback loop allows users to make quicker, more informed decisions about result relevance without manual evaluation, thereby maintaining measurement precision while improving search productivity through reduced evaluation time.
Data Source
AI summary
Search-result explanation systems, methods, and computer-program products receive a user search query, expand the search query into a plurality of sub-queries, perform a database search using the expanded user search query, and determine which sub-queries of the plurality of sub-queries matched with a particular search result. Results from the database search are re-indexed in an index generated on-the-fly and in-memory, within which the results are searched using the sub-queries to determine matching fields and match types. A score is determined based on the type of match(es) with a particular search result based on one or more predefined weights and normalized using a denominator comprising a fictitious, on-the-fly record configured to receive a perfect score according to the received user search query. A user interface showing ranked results and explanations for the ranking, including a score for the result based on the expanded user search query.