Assessing efficiency–effectiveness tradeoffs in multi-stage retrieval systems without using relevance judgments

Abstract

© 2016 Springer Science+Business Media New York Large-scale retrieval systems are often implemented as a cascading sequence of phases—a first filtering step, in which a large set of candidate documents are extracted using a simple technique such as Boolean matching and/or static document scores; and then one or more ranking steps, in which the pool of documents retrieved by the filter is scored more precisely using dozens or perhaps hundreds of different features. The documents returned to the user are then taken from the head of the final ranked list. Here we examine methods for measuring the quality of filtering and preliminary ranking stages, and show how to use these measurements to tune..