Milne, Peter; Wiratunga, Nirmalie; Lothian, Robert and Song, Dawei
(2009).
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| URL: | http://59.67.33.37/faculty/dsong/papers/webcbr09-p... |
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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 vo- cabularies. In this paper we propose a novel method of reusing search experi- ence to transform the underlying representation of tagged resources. The aim is to favour those tags that best correspond to community consensus. A CBR ap- proach is presented to learn from user search histories, modifying resource tags in response to implicit user feedback. We evaluate this method on a prototype im- age 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.
| Item Type: | Conference Item |
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| Copyright Holders: | 2009 The Authors |
| Extra Information: | Workshop at the 8th International Conference on Case Based Reasoning |
| Academic Unit/Department: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Related URLs: | |
| Item ID: | 35330 |
| Depositing User: | Dawei Song |
| Date Deposited: | 14 Nov 2012 14:49 |
| Last Modified: | 04 Aug 2016 06:54 |
| URI: | http://oro.open.ac.uk/id/eprint/35330 |
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