Intuition behind Average Precision and MAP

The Technical Experience Page

Average Precision (AP), more commonly, further averaged over all queries and reported as a single score — Mean Average Precision (MAP) — is a very popular performance measure in information retrieval. However, it is quite tricky to interpret and compare the scores that are seen. From my observations, most hard challenges (TRECVID Semantic Indexing / Genre Classification) have very low (0.05 to 0.3) MAP scores (max 1).

This post is my view on what the score conveys. I will also try to interpret what is a “good” MAP score, and what is “bad”. While this depends on the application, it is still good to have an idea of what to expect.

So firstly, what is MAP, or AP. Suppose we are searching for images of a flower and we provide our image retrieval system a sample picture of a rose (query), we do get back a bunch of ranked images…

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