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Improving accuracy of intention-based response classification using decision tree.


Ali, S. A. and Sulaiman, Md. Nasir and Mustapha, Aida and Mustapha, Norwati (2009) Improving accuracy of intention-based response classification using decision tree. Information Technology Journal, 8 (6). pp. 923-928. ISSN 1812-5638


This study focused on improving the dialogue act classification to classify a user utterance into a response class using a decision tree approach. Decision tree classifier is tested on 64 mixed-initiative, transaction dialogue corpus in theater domain. The result from the comparative experiment show that decision tree able to achieve 81.95% recognition accuracy in classification better than the 73.9% obtained using Bayesian networks and 71.3% achieved by using Maximum likelihood estimation. This result showed that the performance of decision tree as classifier is well suited for these tasks.

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Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.3923/itj.2009.923.928
Publisher: Asian Network for Scientific Information
Keywords: Classification; Decision tree; Natural language generation; Dialogue systems.
Depositing User: Ms. Nida Hidayati Ghazali
Date Deposited: 22 Jul 2013 08:05
Last Modified: 24 Nov 2015 03:46
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3923/itj.2009.923.928
URI: http://psasir.upm.edu.my/id/eprint/15143
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