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

Citation

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

Abstract

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.

Download File

Preview

PDF (Abstract)
Improving accuracy of intention.pdf
Download (84kB) | Preview

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
Statistic Details:	View Download Statistic

Actions (login required)

View Item