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
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
ePrint ID: 21404
Date Deposited: 27 Feb 2007
Last Modified: 27 Mar 2014 18:10
Publisher: Association for Computing Machinery
URI: http://eprints.soton.ac.uk/id/eprint/21404

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