Search Engine Evaluation Metrics: NDCG@10, MRR, MAP, Precision & Recall

Quantifying search relevance improvements requires rigorous statistical evaluation metrics grounded in information retrieval science.

1. Normalized Discounted Cumulative Gain (NDCG@K)

NDCG measures ranking quality by penalizing relevant documents that appear further down the results page. NDCG@10 values ≥ 0.85 indicate strong ranking alignment with human evaluators.

2. Mean Reciprocal Rank (MRR)

MRR evaluates queries where there is typically a single correct answer (e.g., navigational queries). It computes the average reciprocal rank of the first relevant result across all test queries.

3. Online A/B Testing & Interleaving

In production environments, ranking algorithms are benchmarked using Team Draft Interleaving, interleaving results from Algorithm A and Algorithm B into a unified page to measure user click preferences with zero bias.