
	Information Technology Journal
	Year: 2009 \| Volume: 8 \| Issue: 6 \| Page No.: 923-928 DOI: 10.3923/itj.2009.923.928

Improving Accuracy of Intention-Based Response Classification using Decision Tree

S.A. Ali, N. Sulaiman, A. Mustapha and N. Mustapha

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.

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How to cite this article:

S.A. Ali, N. Sulaiman, A. Mustapha and N. Mustapha, 2009. Improving Accuracy of Intention-Based Response Classification using Decision Tree. Information Technology Journal, 8: 923-928.

DOI: 10.3923/itj.2009.923.928

URL: https://scialert.net/abstract/?doi=itj.2009.923.928

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