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.
पूरी विधि पढ़ें
यह खंड पढ़ने के लिए निःशुल्क खाते से साइन इन करें।
पद्धति मानचित्र
सम्बन्धित पद्धतियों का परिवेश — अन्वेषण हेतु किसी नोड का चयन करें।
स्रोत
- 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
इस पृष्ठ का उद्धरण कैसे दें
ScholarGate. (2026, June 23). Mean Average Precision (MAP) for Ranked Retrieval Evaluation. ScholarGate. https://scholargate.app/hi/bibliometrics/mean-average-precision
कौन-सी पद्धति?
इस पद्धति को उसकी निकटतम सजातीय पद्धतियों के साथ रखकर उन्हें साथ-साथ पढ़ें — पुस्तकालय पुस्तकें मेज़ पर रख देता है; चुनाव आपका है।
- BM25 Probabilistic Ranking (Okapi)ग्रंथमिति↔ तुलना करें
- Citation Context and Sentiment Analysisग्रंथमिति↔ तुलना करें
- Normalized Discounted Cumulative Gain (nDCG)ग्रंथमिति↔ तुलना करें