Mean Average Precision (MAP)
Mean Average Precision (MAP) is the classic single-number summary of ranked-retrieval effectiveness under binary relevance and the headline metric of the TREC ad hoc retrieval tracks. For a single query, average precision (AP) computes the precision of the result list at each rank where a relevant document appears and averages those values, rewarding systems that rank all relevant documents highly; MAP is then the mean of AP across a set of queries. Buckley and Voorhees's 2000 SIGIR analysis of evaluation-measure stability showed that average precision is among the most stable and discriminating IR measures, requiring fewer queries than alternatives like precision at a fixed cutoff to reliably tell two systems apart. MAP remains a standard reporting metric for ranked retrieval, complementing graded-relevance measures such as nDCG.
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Vyanzo
- Buckley, C., & Voorhees, E. M. (2000). Evaluating evaluation measure stability. In Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '00), 33-40. DOI: 10.1145/345508.345543 ↗
- Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to Information Retrieval. Cambridge University Press. ISBN: 9780521865715
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 23). Mean Average Precision (MAP) for Ranked Retrieval Evaluation. ScholarGate. https://scholargate.app/sw/bibliometrics/mean-average-precision
Mbinu ipi?
Weka mbinu hii kando ya jamaa zake wa karibu na uzisome bega kwa bega — maktaba huweka vitabu mezani; uamuzi ni wako.
- BM25 Probabilistic Ranking (Okapi)Bibliometriki↔ linganisha
- Citation Context and Sentiment AnalysisBibliometriki↔ linganisha
- Normalized Discounted Cumulative Gain (nDCG)Bibliometriki↔ linganisha
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