News Search Supplemental Topic Clustering
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Solution Overview
Problem
Users often face challenges in finding specific news items when searching, as existing search results may not provide the exact information needed, requiring users to refine or extend their queries through trial-and-error.
Innovation Solution
A method that groups search results into clusters, identifies similarities, determines related topics and categories, and provides supplemental information to help users narrow or expand their queries by linking to relevant content items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users refine or extend their query through trial-and-error to find specific news items, then the precision of search results can be improved, but the time and complexity of the search process increases
Solution Approach 1:
The system performs preliminary clustering and analysis of search results to identify related topics and categories before the user needs to refine their query. By pre-processing the search results into organized clusters with identified relationships, the system prepares supplemental information in advance, allowing users to immediately access relevant topics without undergoing trial-and-error query refinement, thus maintaining precision while reducing time loss
Solution Approach 2:
The system introduces supplemental information including related topics and categories as an intermediary between the initial search results and the user's final target information. This intermediary layer provides structured guidance through identified relationships in the clusters, helping users navigate to specific news items more efficiently without requiring multiple query refinements, thereby reducing search time while maintaining precision
2Measurement precision
If users refine or extend their query through trial-and-error to find specific news items, then the precision of search results can be improved, but the complexity of the search process increases
Solution Approach 1:
The system segments the search results into distinct clusters based on identified relationships and groups similar results together. By organizing the search space into segmented clusters with labeled related topics and categories, the system simplifies the complexity for users who would otherwise need to manually refine queries through trial-and-error, while maintaining the ability to achieve precise results through guided navigation
Solution Approach 2:
The system introduces supplemental information including related topics and categories as an intermediary that reduces search process complexity. This intermediary provides structured organization and guidance, transforming the complex trial-and-error query refinement process into a simpler navigation task where users can explore related topics and categories to find specific news items, thereby reducing complexity while maintaining precision
Data Source
AI summary
In one aspect, a method includes receiving a query, identifying search results in response to the query, grouping the search results into one or more clusters, identifying similarities across the one or more clusters, determining a related topic associated with the query based on the similarities of the one or more clusters, determining a categories associated with the query, identifying supplemental information based on the related topic and the category, and providing the search results and the supplemental information for display in response to the query.