Research Journal of Engineering and Technology

  • Year: 2012
  • Volume: 3
  • Issue: 4

An Impact of Machine Learning with Lexcio-Syntatics Features of Question Classification

  • Author:
  • Megha Mishra1,, Vishnu Kumar Mishra2,, H.R. Sharma3,
  • Total Page Count: 5
  • DOI:
  • Page Number: 327 to 331

1Research Scholar, SOA University, Bhubneswar

2Asstt. Professor, BIT, Durg

3Dean R &D, RECT, Raipur

*Corresponding Author: megha16shukla@gmail.com

**E-mail: vshn_mshr@rediffmail.com

***E-mail: hrsharmaji@indiatimes.com

Online published on 21 February, 2013.

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: bagof-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.

Keywords

Question Answering, Machine Learning, Support Vector Machine, Question Classifications, Lexical Features, Syntactical Feature