Search Engine Suggestion via Query Match Degree Analysis
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Solution Overview
Problem
Current meta search engines cannot effectively suggest the most suitable search engine to users based on the characteristics of different search engines, limiting the quality of search results.
Innovation Solution
A method and apparatus that obtain a query input, generate a query suggestion set for multiple search engines, determine a match degree between each search engine and the query using background association information, and suggest search engines based on these match degrees, reflecting the search characteristics and user intentions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a meta search engine integrates search results from multiple preset search engines, then the coverage of search results is improved, but the ability to suggest a suitable search engine based on query characteristics is lost
Solution Approach 1:
The patent segments the search process into two distinct phases: (1) obtaining query suggestion sets from multiple search engines, and (2) determining match degrees between search engines and queries. This segmentation allows the system to evaluate individual search engine characteristics without immediately integrating results, thereby preserving the ability to suggest suitable engines while maintaining comprehensive coverage.
Solution Approach 2:
The patent performs preliminary evaluation of search engines by obtaining query suggestion sets before actual search execution. By pre-assessing the match degree between search engines and queries using background association information, the system can suggest the most suitable search engine in advance, avoiding the loss of adaptability that occurs when results are simply integrated without evaluation.
2Measurement precision
If query suggestion sets are obtained for multiple search engines, then the measurement of query quality is improved, but the system complexity increases
Solution Approach 1:
The patent introduces background association information as an intermediary element that facilitates the comparison between query suggestion sets from different search engines. This intermediary enables the determination of match degrees without requiring direct complex interactions between multiple search engine systems, thereby improving measurement precision while controlling system complexity through the use of a mediating information layer.
Data Source
AI summary
A search engine suggestion method, apparatus, and non-transitory article of manufacture embodying computer readable instructions for data search. The method includes: obtaining a query input by a user; obtaining a query suggestion set for the query for each of a plurality of different search engines, the query suggestion set including at least one query suggestion; determining a match degree between each of the search engines and the query based on the query suggestion set and background association information of the query; and suggesting among the plurality of different search engines based on the match degrees. By use of the solutions proposed by this application, it is possible to suggest the user a more appropriate search engine(s) for data search.