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Question Classification using Machine Learning Approaches
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 48 - Number 13 |
| Year of Publication: 2012 |
| Authors: Arun D Panicker, Athira U, Sreesha Venkitakrishnan |
10.5120/7405-0101
|
Arun D Panicker, Athira U, Sreesha Venkitakrishnan . Question Classification using Machine Learning Approaches. International Journal of Computer Applications. 48, 13 ( June 2012), 1-4. DOI=10.5120/7405-0101
Abstract
Question classification is the process by which a system analyzes a question and labels the question based on the category to which it belongs. The automated categorization (or classification) of questions into predefined categories has witnessed a booming interest due to the increased popularity of web technologies. The recent advancement in the form of E-Learning calls for the need of question categorization. In network based learning the questions posted by students need to be categorized on the basis of the concerned concepts. This point to the relevance of question categorization in this area. Many approaches to question classification have been proposed and have achieved reasonable results. The dominant approaches are machine learning and context based classification. There are several Machine Learning methods for question categorization. Here we are extending the previous methods for text categorization to question categorization and making a comparative study of the performance of two approaches, Naïve Bayes and Support Vector Machine
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