Title :
Comparative study of machine learning techniques for boundary determination of explanation knowledge from text
Author :
Pechsiri, Chaveevan ; Saint-Dizier, Patrick ; Piriyakul, Rapeepun
Author_Institution :
Inf. Technol. Dept., Dhurakijpundit Univ., Bangkok, Thailand
Abstract :
This research aim to determine the explanation knowledge boundary for improvement of basic diagnosis. This paper compares different machine learning techniques including Maximum Entropy, Bayesian Networks, and Naive Bayes for solving the boundary determination problems of the discourse marker´s connection problem, usage of several discourse markers within the boundary, and implicit discourse marker. The results have shown an improvement through using machine learning techniques comparing with Centering Theory used in the previous work.
Keywords :
Bayes methods; belief networks; learning (artificial intelligence); optimisation; text analysis; Bayesian network; Naive Bayes method; boundary determination; explanation knowledge boundary; machine learning; marker connection problem; maximum entropy; Bayesian methods; Data mining; Entropy; Machine learning; Natural language processing; Niobium; Pattern recognition; Support vector machines; Unsupervised learning;
Conference_Titel :
Natural Language Processing, 2009. SNLP '09. Eighth International Symposium on
Conference_Location :
Bangkok
Print_ISBN :
978-1-4244-4138-9
Electronic_ISBN :
978-1-4244-4139-6
DOI :
10.1109/SNLP.2009.5340938