Malayalam Questions Classification in Question Answering Systems using Support Vector Machine - Bibin, PA; Babu Anto, P (International Journal of Computer Sciences and Engineering, 2019)
We consider Question answering systems (QAS) as the next step in information retrieval, allowing users to create questions in natural language and get concise answers. Researches show that exact classification of questions with respect to the expected answer type is imperative to make a successful QAS. The duty of classifying distinctive questions becomes hard and challenging because there are variety of Natural Language Questions. Due to the agglutinative nature researchers find so many difficulties in Malayalam based QAS. So a very limited researches have been done in classifying Malayalam Questions with the help of Machine Learning Techniques. In this paper, we have used Support Vector Machines (SVM) to classify Questions. In Malayalam we can classify the question into following types എന്ത് (what), എപ്പോൾ (when), എങ്ങനെ (how), എവിടെ(where), എന്തുകൊണ്ട്(why), എത്ര (how many/how much) and ആര്(who). For Malayalam Question classification using SVM 1is the average precision, 0.93 is the average recall and the average F1 Score is 0.95. So the outcome that we obtained shows the effectiveness of Support Vector Machines in classifying the question.