Quantitative evaluation measures a search system’s accuracy and relevance over time by comparing actual results with defined desired outputs. It creates a repeatable baseline for judging future optimizations as usage grows. section 7.2.3
A practical evaluation process includes:
- Build ground truth from diverse queries that represent real user needs and specify desired results. section 7.2.3
- Manually rate the relevance of retrieved documents for each benchmark query. section 7.2.3
- Track precision, which indicates how many retrieved documents are relevant, alongside recall, which measures how many relevant documents were found. section 7.2.3
Search benchmark
A search team can test queries such as “best practices for workflow automation,” “customer feedback on the freemium plan,” and “API integration case studies,” then compare retrieved documents with manual relevance judgments. section 7.2.3
