The notion that most search strategies can be adjusted to increase Precision at the expense of Recall, or vice versa. At one extreme, 100% Recall could be achieved by a search that returned the entire Document Population, but Precision would be low (equal to Prevalence). At the other extreme, 100% Precision could be achieved by a search that returned a single Relevant Document, but Recall would be low (equal to 1/N, where N is the number of Relevant Documents in the Document Population). More generally, a broader search returning many Documents will have higher Recall and lower Precision, while a narrower search returning fewer Documents will have lower Recall and higher Precision. A Precision-Recall Curve illustrates the Precision-Recall Tradeoff for a particular search method. 1
