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


Affiliations
1 SOA University, Bhubneswar, India
2 BIT, Durg, India
3 R &D, RECT Raipur, India
     

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

Abstract Views: 183  |  PDF Views: 1

Authors

Megha Mishra
SOA University, Bhubneswar, India
Vishnu Kumar Mishra
BIT, Durg, India
H. R. Sharma
R &D, RECT Raipur, India

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.