Search Query Processing with Tabbed Dashboard Results
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Solution Overview
Problem
Current search engines often return a multitude of unsatisfactory results due to the inability to accurately identify the nature and extent of information sought in a text query, requiring users to perform multiple searches and enter additional queries to obtain relevant information, which can lead to missed better results if incorrect terms are used or if the user lacks knowledge about the topic.
Innovation Solution
A method that processes search history data to identify primary and secondary search terms, including synonyms and antonyms, and displays these results in a web-based interface dashboard, organizing them into primary, secondary, and peripheral tabs to provide a holistic view of search results, anticipating user queries and improving search efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a simple text query is applied to search engines, then the search operation is simple and quick, but the results may not accurately reflect the nature or extent of information sought
Solution Approach 1:
The system performs preliminary actions by automatically generating multiple search queries with different terms and formulations before the user even completes their search. It anticipates what the user might be looking for and prepares multiple search strategies in advance, then presents results from all these searches simultaneously, resolving the contradiction between simple operation and accurate results.
2Loss of information
If users perform multiple searches to revise results, then more information can be obtained, but time is lost and better results may be omitted
Solution Approach 1:
The system merges multiple search operations into a single unified search interface. Instead of requiring users to perform sequential searches, it combines multiple search queries, synonyms, and related terms into one simultaneous search operation that returns comprehensive results across all search dimensions at once, eliminating time loss while maintaining information completeness.
3Measurement precision
If users compose and submit multiple follow-up queries, then satisfactory results can be obtained, but the quality relies on the user's knowledge of correct terms
Solution Approach 1:
The system performs self-service by automatically generating multiple search queries using synonyms, related terms, and different formulations without requiring user intervention. It autonomously expands the search vocabulary and tries multiple search strategies, then presents the best results from all attempts, making the search process independent of the user's knowledge of correct terminology while maintaining high result quality.
4Loss of information
If multiple search terms and follow-up queries are used, then more comprehensive results are returned, but the search process becomes more complex
Solution Approach 1:
The system segments the complex search process into distinct functional components: automatic query generation, synonym expansion, multi-term searching, and result aggregation. Each component handles a specific aspect of the search, and they work together in an organized pipeline. This segmentation makes the complex process manageable and transparent to the user, who simply enters one query and receives comprehensive results without needing to understand the underlying complexity.
Data Source
AI summary
Aspects retrieve, organize and display different classifications of sets of search results in different, respective tabbed sheets that are nested on top of one another in a web-based interface dashboard. A text string search query is classified into constituent primary search terms that are likely to return satisfactory search results as indicated by retrieved search history data as a function of search resources and language classification rules associated with the user identity indicia. Secondary search terms related to the primary search terms and including synonyms and antonyms are determined as substitutes for the primary search terms in response to search history indicating follow-up searches immediately subsequent to searches of the primary search terms at less than a specified threshold of frequency. The set of peripheral knowledge article results is generated by searching knowledge article resources for background information on the primary search terms or the secondary search terms.