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ICTIR
2009
Springer

"A term is known by the company it keeps": On Selecting a Good Expansion Set in Pseudo-Relevance Feedback

9 years 1 months ago
"A term is known by the company it keeps": On Selecting a Good Expansion Set in Pseudo-Relevance Feedback
Abstract. It is well known that pseudo-relevance feedback (PRF) improves the retrieval performance of Information Retrieval (IR) systems in general. However, a recent study by Cao et al [3] has shown that a non-negligible fraction of expansion terms used by PRF algorithms are harmful to the retrieval. In other words, a PRF algorithm would be better off if it were to use only a subset of the feedback terms. The challenge then is to find a good expansion set from the set of all candidate expansion terms. A natural approach to solve the problem is to make term independence assumption and use one or more term selection criteria or a statistical classifier to identify good expansion terms independent of each other. In this work, we challenge this approach and show empirically that a feedback term is neither good nor bad in itself in general; the behavior of a term depends very much on other expansion terms. Our finding implies that a good expansion set can not be found by making term in...
Raghavendra Udupa, Abhijit Bhole, Pushpak Bhattach
Added 26 May 2010
Updated 26 May 2010
Type Conference
Year 2009
Where ICTIR
Authors Raghavendra Udupa, Abhijit Bhole, Pushpak Bhattacharyya
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