What is the difference between precision and recall in information retrieval?

What is the difference between precision and recall in information retrieval?

Precision and recall are two important metrics used to evaluate the performance of information retrieval systems.

Precision measures the accuracy of the retrieved results. It is the ratio of the number of relevant documents retrieved to the total number of documents retrieved. In other words, precision indicates how many of the retrieved documents are actually relevant to the user's query. A high precision value indicates that the system retrieves mostly relevant documents.

Recall, on the other hand, measures the completeness of the retrieved results. It is the ratio of the number of relevant documents retrieved to the total number of relevant documents in the collection. Recall indicates how many of the relevant documents were actually retrieved by the system. A high recall value indicates that the system retrieves a large portion of the relevant documents.

In summary, precision focuses on the accuracy of the retrieved results, while recall focuses on the completeness of the retrieved results. Both metrics are important in information retrieval, and a good system should aim to achieve a balance between high precision and high recall.