Facet Map Keyword Adaptation for Search Performance
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Solution Overview
Problem
Current facet search mechanisms face challenges in improving performance for practical use, despite recent refinements.
Innovation Solution
An information processing apparatus and method that provides a facet map with keyword usage frequency calculations, allowing new keywords to be added as elements based on predetermined conditions, tailored to user-specific usage styles for enhanced facet search performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the facet map is updated with new keywords based on usage frequency, then the facet search performance and adaptability are improved, but the system complexity and processing overhead increase
Solution Approach 1:
The facet map automatically updates itself by monitoring keyword usage frequencies from search queries and adding new keywords when they meet predetermined conditions. This self-service mechanism eliminates the need for manual facet map maintenance while continuously adapting to user needs, resolving the contradiction between adaptability improvement and system complexity increase
Solution Approach 2:
The system implements feedback loops where search query data is analyzed to calculate keyword usage frequencies, which then feed back into the facet map update process. This closed-loop feedback mechanism enables automatic adaptation based on actual usage patterns without requiring complex manual intervention, balancing adaptability gains with manageable system complexity
2Productivity
If keyword usage frequency is calculated and new keywords are added dynamically, then the search efficiency is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing keyword usage frequencies as they accumulate from search queries. Rather than performing complex analysis at search time, the frequency calculation and keyword selection are prepared in advance based on predetermined conditions, reducing real-time processing time while maintaining high search efficiency
Solution Approach 2:
The system changes parameters by using predetermined thresholds and conditions for keyword addition that can be adjusted based on system load and performance requirements. This allows optimization of the balance between processing time and search efficiency by tuning parameters such as minimum usage frequency thresholds and keyword selection criteria
Data Source
AI summary
Provided is an information processing apparatus including a control section that provides, to a terminal of a user, a relationship among a plurality of keywords each as an element constituting a facet that is used as an index for searching for a content, as a facet map, and a facet selection environment that is based on at least one keyword addable to the facet map as a new element of the facet, calculates a usage frequency of each of the keywords in the terminal, and adds a keyword whose calculated usage frequency satisfies a predetermined condition to the facet map as the new element of the facet.