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ECIR
2009
Springer

Mean-Variance Analysis: A New Document Ranking Theory in Information Retrieval

10 years 5 months ago
Mean-Variance Analysis: A New Document Ranking Theory in Information Retrieval
Abstract. This paper concerns document ranking in information retrieval. In information retrieval systems, the widely accepted probability ranking principle (PRP) suggests that, for optimal retrieval, documents should be ranked in order of decreasing probability of relevance. In this paper, we present a new document ranking paradigm, arguing that a better, more general solution is to optimize top-n ranked documents as a whole, rather than ranking them independently. Inspired by the Modern Portfolio Theory in finance, we quantify a ranked list of documents on the basis of its expected overall relevance (mean) and its variance; the latter serves as a measure of risk, which was rarely studied for document ranking in the past. Through the analysis of the mean and variance, we show that an optimal rank order is the one that maximizes the overall relevance (mean) of the ranked list at a given risk level (variance). Based on this principle, we then derive an efficient document ranking algori...
Jun Wang
Added 08 Mar 2010
Updated 08 Mar 2010
Type Conference
Year 2009
Where ECIR
Authors Jun Wang
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