Please use this identifier to cite or link to this item:
|Title:||On improving Pseudo-relevance feedback using Pseudo-irrelevant documents|
|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.|
|Appears in Collections:||Proceedings papers|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.