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...

• Type: Conference
• Year: 2009
• Where: ECIR
• Authors: Jun Wang
• Keywords: Computer Science, Document Ranking, Document Ranking Algorithm, Document Ranking Paradigm, ECIR 2009