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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/100/2032

Title: On improving Pseudo-relevance feedback using Pseudo-irrelevant documents
Authors: RAMAN, K
UDUPA, R
BHATTACHARYA, P
BHOLE, A
Issue Date: 2010
Publisher: SPRINGER-VERLAG BERLIN
Citation: ADVANCES IN INFORMATION RETRIEVAL, PROCEEDINGS,5993,573-576
Abstract: Pseudo-Relevance Feedback (PRF) assumes that the top-ranking n documents of the initial retrieval are relevant and extracts expansion terms from them. In this work, we introduce the notion of pseudo-irrelevant documents, i.e. high-scoring documents outside a top n that, are highly unlikely to be relevant. We show how pseudo-irrelevant documents can be used to extract; better expansion terms from the top-ranking n documents: good expansion terms are those which discriminate the top-ranking n documents from the pseudo-irrelevant documents. Our approach gives substantial improvements in retrieval performance over Model-based Feedback on several test collections.
URI: http://dspace.library.iitb.ac.in/xmlui/handle/10054/15307
http://hdl.handle.net/100/2032
ISBN: 978-3-642-12274-3
ISSN: 0302-9743
Appears in Collections:Proceedings papers

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