Partial matching isn’t just more efficient; it works better too! In fact, Persin claims superior performance (29.1 versus 28.9 percent, 11-point average precision on the TREC/Tipster corpus) using partial ranking than if all postings are considered. He attributes this to the “. . . pruning of common terms that are encountered in almost every document and that create informational noise rather than help discriminate between documents.” [Persin, 1994, p. 345]