Context-Aware Search Using Tolerance Limits for Relevant Results
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Solution Overview
Problem
Existing AI-based search systems fail to provide search results that accurately match a user's context and intentions, leading to suboptimal user experiences.
Innovation Solution
A method and system that determine a user's search context based on input and context information, set a tolerance limit, and provide search results according to this condition, utilizing a personal knowledge graph to enhance relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AI-based search systems use general search algorithms, then search speed and coverage are improved, but search result relevance to user context deteriorates
Solution Approach 1:
The search system is segmented into multiple independent modules: a context analysis module that processes user input and contextual information separately, a tolerance limit determination module that calculates acceptable deviation thresholds, and a search execution module that applies these parameters. This segmentation allows each module to specialize in its function, improving overall search relevance without sacrificing speed.
Solution Approach 2:
The system performs preliminary analysis of user context and determines tolerance limits before executing the actual search. By pre-processing contextual information and establishing acceptance criteria in advance, the system avoids reprocessing during search execution, thereby maintaining high search speed while improving result relevance through context-aware filtering.
2Measurement precision
If search systems consider detailed user context and intentions, then search result accuracy is improved, but system complexity increases
Solution Approach 1:
The system transforms complex contextual analysis into a simplified parameter representation by determining a tolerance limit value that quantifies acceptable deviation from user intent. This parameter transformation reduces the complexity of handling detailed contextual information while maintaining search result accuracy through the tolerance threshold mechanism.
Solution Approach 2:
The tolerance limit determination module acts as an intermediary between context analysis and search execution. It translates complex user context and intentions into a simplified tolerance parameter that guides the search process, thereby reducing system complexity while preserving search accuracy through this mediating layer.
3Device complexity
If existing AI search systems provide generic search results, then system simplicity is maintained, but user experience quality deteriorates
Solution Approach 1:
The system automatically performs context analysis and tolerance limit determination without requiring user intervention. It self-adjusts search parameters based on analyzed context, providing personalized search results while maintaining system simplicity. This self-service approach improves user experience quality without adding operational complexity for users.
Data Source
AI summary
A method of providing search results based on a user's search context is provided. The method includes determining a user's search context based on a user input and context information for a search, determining a tolerance limit representing a degree to which a user is tolerable from the determined user's search context, obtaining a search condition for the search, based on the determined tolerance limit, and providing search results according to the obtained search condition.