Boolean Search Query Optimization via Usage-Based Scope Reduction
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Solution Overview
Problem
Search servers experience performance degradation due to high loads from simultaneous search queries from multiple users, leading to reduced quality of service.
Innovation Solution
A method that modifies boolean search queries based on usage information and performance thresholds to reduce the number of content databases searched, by removing less frequently accessed resources and constraining results to preferred formats, thereby optimizing search performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If text searching is performed across all content databases to satisfy user information needs, then search completeness and accuracy are improved, but search server performance degrades due to high loads from simultaneous queries
Solution Approach 1:
The patent applies local quality by customizing search behavior based on user-specific attributes and preferences. Instead of uniform searching across all databases, the system selectively searches only relevant content databases and formats based on individual user profiles, thereby maintaining search accuracy while reducing overall server load.
Solution Approach 2:
The system dynamically adjusts search parameters including selected content databases, result formats, and search scope based on real-time user attributes and current server load conditions. This dynamic adaptation allows the search system to maintain accuracy when necessary while reducing resource consumption during high-load periods.
2Quantity of substance
If comprehensive text searching is performed to show all locations of search phrases, then search completeness is improved, but resource intensity and search load increase
Solution Approach 1:
The patent extracts and removes unnecessary search operations by identifying and excluding content databases that are not relevant to the specific user's needs based on their attributes and preferences. This extraction principle eliminates wasted computational resources while preserving complete search coverage for relevant databases.
Solution Approach 2:
The system performs partial searching by selectively searching only a subset of content databases that are relevant to each user, rather than performing excessive comprehensive searches across all databases. This partial action maintains result completeness for relevant content while significantly reducing resource intensity.
3Productivity
If search queries are modified to reduce search scope, then search performance is improved, but search completeness may be compromised
Solution Approach 1:
The system performs preliminary actions by pre-processing user queries to determine relevant content databases and preferred result formats before executing the search. User attributes and preferences are analyzed in advance to configure the search scope, ensuring that performance optimization does not compromise result accuracy for relevant content.
Solution Approach 2:
The search system uses feedback from user attributes, historical behavior, and preference data to continuously refine search scope and parameters. This feedback mechanism ensures that modified search queries maintain reliability by adapting to user needs while optimizing performance based on learned patterns.
Data Source
AI summary
A method, executed by a computer, for optimizing searches includes receiving a boolean search query comprising a plurality of operators and operands and usage information corresponding to a user, determining modifications to be made to the boolean search query according to the usage information, and modifying the boolean search query according to the modifications. A computer program product and computer system corresponding to the above method are also disclosed herein.