Precision and recall are two key metrics used to evaluate the effectiveness of an IR system in retrieving relevant documents.
Precision is the proportion of retrieved documents that are relevant to the user's query. It measures how many of the results are actually useful. High precision means the system returns fewer irrelevant results.
Recall is the proportion of relevant documents that are retrieved by the system. It measures how well the system captures all relevant documents in the dataset. High recall means the system finds most of the relevant documents, even if some irrelevant ones are included.