🔎 Mean Average Precision (MAP)

Mean Average Precision (MAP)#

The mean of average-precision scores across queries.

Important

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What it is#

Mean Average Precision is the mean, across all users, of each user’s Average Precision (AP). AP averages the precision measured at every rank where a relevant item appears — the area under that user’s precision–recall curve:

\[\text{MAP} = \frac{1}{|U|}\sum_{u \in U} \text{AP}_u.\]

It rolls per-user ranking quality into one number.

What AP rewards#

Because AP recomputes precision at each relevant position, it emphasizes getting relevant items early — a relevant item at rank 1 lifts every later precision term, while one at rank 10 lifts few. So MAP is strongly order-sensitive, rewarding front-loaded relevance.

How it compares#

MAP works with binary relevance (relevant or not), where NDCG handles graded relevance; MAP summarizes the whole precision–recall trade-off, where Hit Rate only checks for any hit. Reported at a cutoff (MAP@K), it is a standard top-N metric for search and recommendation.

Theme: Ranking & Interleaving · All terminology

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Mind map — connected ideas

Average Precision (AP) · NDCG (Normalized Discounted Cumulative Gain) · Hit Rate (HR) · DCG (Discounted Cumulative Gain) · Precision (a.k.a. Positive Predictive Value, PPV) · Relevance in Recommender Systems

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More in Ranking & Interleaving

Balanced Interleaving · DCG (Discounted Cumulative Gain) · Interleaving Tests · NDCG (Normalized Discounted Cumulative Gain) · Probabilistic Interleaving · Ranking Algorithms · Team Draft Interleaving (TDI) · TREC (Text REtrieval Conference)