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Milne, Peter; Wiratunga, Nirmalie; Lothian, Robert and Song, Dawei
(2009).
Abstract
The advent of Web 2.0 has created a proliferation of resource sharing sites where individual users tag resources. Retrieval performance is good when users share the same vocabulary, but deteriorates when users have diverging vocabularies. In this paper we propose a novel method of reusing search experience to transform the underlying representation of tagged resources. The aim is to favour those tags that best correspond to community consensus. A CBR approach is presented to learn from user search histories, modifying resource tags in response to implicit user feedback. We evaluate this method on a prototype image retrieval system IFETCH. Our evaluation shows that resource transformation progressively increases the ranking of those images that are generally deemed relevant by similar search sessions. Our results also confirm that the casebase weight update mechanism is more robust to erroneous user feedback compared to a naive constant weight update strategy.
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- Item ORO ID
- 35283
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- Conference or Workshop Item
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Workshop at the 8th International Conference on Case Based Reasoning
Lorraine McGinty, David C. Wilson (Eds.): Case-based Reasoning Research and Development, 8th International Conference on Case-Based Reasoning ICCBR 2009, Seattle, WA, USA, July 20-23, 2009 Proceedings. Lecture Notes in Computer Science, Vol. 5650 (Subseries: Lecture Notes in Artificial Intelligence) Springer 2009, ISBN 978-3-642-02997- - Academic Unit or School
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Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Copyright Holders
- © 2009 Authors
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- Mary Mcmahon