Information retrieval

Information retrieval finds material relevant to an information need within a collection, commonly documents or passages. A query expresses part of that need; a retrieval system selects or ranks candidate material. Relevance is therefore part of the task, beyond simply checking whether a stored identifier matches.^[ref]

For example, suppose a query returns five documents, three relevant, while the collection contains six relevant documents altogether. Its precision is $3/5$, while its recall is $3/6$. Returning everything increases coverage but can overwhelm the user with irrelevant material. An inverted index accelerates term lookup; scoring and evaluation address which retrieved results are useful. Information retrieval consequently combines data structures, ranking algorithms and evidence about the user's task.