Recall (information retrieval)

From Wikipedia, the free encyclopedia

Merge arrow
 It has been suggested that this article or section be merged into Precision and recall. (Discuss)

Recall in Information Retrieval is the fraction of the documents that are relevant to the query that are successfully retrieved.

\mbox{recall}=\frac{|\{\mbox{relevant documents}\}\cap\{\mbox{retrieved documents}\}|}{|\{\mbox{relevant documents}\}|}

In binary classification, recall is called sensitivity. So it can be looked at as the probability that a relevant document is retrieved by the query.

It is trivial to achieve recall of 100% by returning all documents in response to any query. Therefore recall alone is not enough but one needs to measure the number of non-relevant documents also, for example by computing the precision.