Subscribe Now Subscribe Today
Science Alert
 
Blue
   
Curve Top
Information Technology Journal
  Year: 2009 | Volume: 8 | Issue: 6 | Page No.: 923-928
DOI: 10.3923/itj.2009.923.928
 
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

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.
PDF Fulltext XML References Citation Report Citation
 RELATED ARTICLES:
  •    Effects of Hyperspectral Data Transformations on Urban Inter-class Separations using a Support Vector Machine
  •    K-Means Clustering to Improve the Accuracy of Decision Tree Response Classification
  •    A Modified Modulation Recognition Method against Doppler Effects
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

COMMENT ON THIS PAPER
 
 
 

 

 
 
 
 
 
 
 
 
 

 
 
 
 
 

Curve Bottom