Author(s): Megha Mishra, Vishnu Kumar Mishra, H.R. Sharma

Email(s): megha16shukla@gmail.com , vshn_mshr@rediffmail.com , hrsharmaji@indiatimes.com

DOI: Not Available

Address: Megha Mishra1, Vishnu Kumar Mishra2, H.R. Sharma3
1Research Scholar SOA University, Bhubneswar
2Asstt. Professor, BIT, Durg
3Dean R &D, RECT Raipur
*Corresponding Author

Published In:   Volume - 3,      Issue - 4,     Year - 2012


ABSTRACT:
Question classification is very important for question answering. This paper presents our research work on question classification through machine learning approaches. We have experimented with three machine learning algorithms: Nearest Neighbors (NN), Naïve Bayes (NB), and Support Vector Machines (SVM) using two kinds of features: bag-of-words and bag-of n grams. The experiment results show that with only surface text features the SVM outperforms the other four methods for this task. Further, we propose to use a lexico-syntactic combined feature of question classification.


Cite this article:
Megha Mishra, Vishnu Kumar Mishra, H.R. Sharma. An Impact of Machine Learning with Lexcio-Syntatics Features of Question Classification. Research J. Engineering and Tech. 3(4): Oct-Dec. 2012 page 327-331.


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DOI: 10.5958/2321-581X 


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