Automated SBS Evaluation Using Online Signals
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Solution Overview
Problem
Current Side-by-Side (SBS) evaluation methods for information retrieval systems require significant resource investment and highly trained judges to produce accurate results, making them inefficient and costly.
Innovation Solution
The use of online signals, such as user behavior data, to generate and aggregate satisfaction metrics for search result lists, allowing for automated preference judgments that can be compared to or used as hints for human judges to improve judgment quality and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional SBS evaluation methods are used with human judges, then judgment accuracy is improved, but resource investment and cost increase significantly
Solution Approach 1:
The patent introduces automated evaluation systems and online signals as intermediary components between the search result lists and human judges. These intermediaries process and pre-evaluate the results, reducing the burden on human judges while maintaining evaluation quality. The automated system handles routine assessments, allowing human judges to focus on more complex cases.
Solution Approach 2:
The patent creates automated copies of the evaluation process using algorithms and online signals that mimic human judgment behavior. These automated evaluation systems generate preference judgments that can be compared with or used to guide human judges, reducing the need for extensive human resource investment while maintaining judgment accuracy.
2Measurement precision
If highly trained judges are used for SBS evaluation, then judgment quality is improved, but time consumption and timeliness worsen
Solution Approach 1:
The patent implements preliminary automated evaluation of search result lists using online signals before human judges perform their assessments. This preliminary action pre-processes the data, identifies obvious preferences, and prepares evaluation materials in advance, significantly reducing the time required for human judges to reach accurate conclusions.
Solution Approach 2:
The patent establishes a feedback loop where automated evaluation results are compared with human judge judgments. The discrepancies and patterns from this feedback are used to continuously improve both the automated system and guide human judges, enabling faster and more accurate evaluations over time without requiring increased training time.
3Measurement precision
If more judges are deployed for evaluation, then judgment coverage and accuracy are improved, but cost and resource requirements increase
Solution Approach 1:
The patent creates a multi-functional evaluation system that combines automated algorithms, online signal processing, and human judgment capabilities into a single unified framework. This universal system can operate in different modes (fully automated, hybrid, or human-only) depending on the evaluation needs, reducing the complexity of managing separate systems for different evaluation scenarios.
Data Source
AI summary
Examples of the present disclosure describe systems and methods for using online signals to improve judgment quality in Side-by-Side (SBS) evaluation. In aspects, two or more search result lists may be accessed within a query log. The search result lists may be used to generate and/or determine satisfaction metrics between the search result lists. The satisfaction metrics may be aggregated to automatically generate preference judgments for the search result lists. In some aspects, the preference judgments may be compared to the preference judgments of judges to measure the judgment quality of the judges.