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.
Cite(Electronic):
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. Available on: https://www.ijersonline.org/AbstractView.aspx?PID=2012-3-4-12