A hybrid user model in text categorisation
Kim, S., Hall, W. and Keane, A.J. (2000) A hybrid user model in text categorisation. In, Proceedings of KDD-2000: Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. KDD-2000: Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining USA, Association for Computing Machinery, 103-104.
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Description/Abstract
A user model that specifies user preferences on message handling is an essential component of an email message categorizer. We present an approach that combines two learning algortihms, i.e. the Naive Bayesian Classifier (NBC) and Progol, to model implicitly and explicitly reflected user preferences that may not be modelled by using either the algorithms alone. An experiment demonstrates the improvement of categorization performance compared to that of using the two algorithms independently.
| Item Type: | Book Section |
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| Related URLs: | |
| Keywords: | Text categorization, user modelling, symbolic learning, statistical learning, email communication |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | University Structure - Pre August 2011 > School of Engineering Sciences |
| Item ID: | 21404 |
| Date Deposited: | 27 Feb 2007 |
| Last Modified: | 28 Jun 2012 09:50 |
| Contributors: | Kim, S. (Author) Hall, W. (Author) Keane, A.J. (Author) |
| Date: | 2000 |
| Status: | Published |
| Publisher: | Association for Computing Machinery |
| URI: | http://eprints.soton.ac.uk/id/eprint/21404 |
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