Dynamic Threshold Adjustment for Consistent Search Results
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Solution Overview
Problem
Information retrieval systems face challenges in providing a consistent user experience due to variations in score thresholds affecting the number of true hits, false alarms, precision, and recall, especially when searching large versus small corpora or varying audio quality.
Innovation Solution
The system dynamically adjusts the threshold based on user interactions, audio quality, and corpus characteristics to maintain consistent performance metrics such as false alarms, true positives, and computation time, using statistical models and rank-order statistics to optimize user experience across different search scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed threshold is applied to all queries, then the system operation is simple, but the user experience consistency deteriorates across different corpus sizes and audio qualities
Solution Approach 1:
The patent implements dynamic threshold adjustment based on corpus characteristics and audio quality metrics. The threshold is no longer fixed but adapts automatically to different search scenarios, maintaining consistent user experience across varying corpus sizes and audio qualities while preserving operational simplicity through automated adaptation.
2Reliability
If the threshold is adjusted for each query to maintain consistency, then user experience consistency is improved, but the system complexity increases
Solution Approach 1:
The patent changes the threshold parameter dynamically based on corpus size, audio quality metrics, and query characteristics. By adjusting this key parameter adaptively, the system maintains consistent user experience without requiring complex structural changes, achieving reliability improvement through parameter optimization rather than system redesign.
3Productivity
If more putative hits are returned to improve recall, then the number of true positives increases, but the number of false alarms increases
Solution Approach 1:
The patent applies different threshold levels for different regions or types of search results based on corpus characteristics and audio quality. By implementing local quality control through region-specific thresholding, the system can return more hits in high-quality regions while maintaining strict filtering in lower-quality regions, thereby improving overall recall without proportionally increasing false alarms.
Data Source
AI summary
An information retrieval system for search a corpus is configured to, for each of a plurality of searches of at least a subset of the corpus, generate a confidence score for each of a plurality of putative occurrences of a search query in the at least a subset of the corpus. The system is further configured to adjust a threshold to maintain a consistent user experience across the plurality of searches according to a consistency criterion. The system is further configured to display putative occurrences of the search query having a confidence score greater than the threshold.