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Combining interaction and content for feedback-based ranking

Di Buccio, Emanuele; Melucci, Massimo and Song, Dawei (2011). Combining interaction and content for feedback-based ranking. In: 4th Information Retrieval Facility Conference, 7-9 June 2011, Vienna.

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Abstract

The paper is concerned with the design and the evaluation of the combination of user interaction and informative content features for implicit and pseudo feedback-based document re-ranking. The features are observed during the visit of the top-ranked documents returned in response to a query. Experiments on a TREC Web test collection have been carried out and the experimental results are illustrated. We report that the effectiveness of the combination of user interaction for implicit feedback depends on whether document re-ranking is on a single-user or a user-group basis. Moreover, the adoption of document re-ranking on a user-group basis can improve pseudo-relevance feedback by providing more effective document for expanding queries.

Item Type: Conference Item
Copyright Holders: 2011 Springer-Verlag
ISSN: 0302-9743
Extra Information: Multidisciplinary Information Retrieval
Second Information Retrieval Facility Conference, IRFC 2011, Vienna, Austria, June 6, 2011. Proceedings
Editors:Allan Hanbury, Andreas Rauber, Arjen P. de Vries
Lecture Notes in Computer Science, Volume 6653 2011
ISBN: 978-3-642-21352-6 (Print)
ISBN: 978-3-642-21353-3 (Online)
pp.46-61
Keywords: interaction features; geometric model; implicit feedback; pseudo-relevance feedback
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
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Item ID: 34944
Depositing User: Mary Mcmahon
Date Deposited: 26 Oct 2012 09:00
Last Modified: 01 Dec 2016 00:50
URI: http://oro.open.ac.uk/id/eprint/34944
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