Journal article

Rank-Biased Precision for Measurement of Retrieval Effectiveness

Alistair Moffat, Justin Zobel

ACM TRANSACTIONS ON INFORMATION SYSTEMS | ASSOC COMPUTING MACHINERY | Published : 2009

Abstract

A range of methods for measuring the effectiveness of information retrieval systems has been proposed. These are typically intended to provide a quantitative single-value summary of a document ranking relative to a query. However, many of these measures have failings. For example, recall is not well founded as a measure of satisfaction, since the user of an actual system cannot judge recall. Average precision is derived from recall, and suffers from the same problem. In addition, average precision lacks key stability properties that are needed for robust experiments. In this article, we introduce a new effectiveness metric, rank-biased precision, that avoids these problems. Rank-biased pre-c..

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