Arabic question classification using support vector machines and convolutional neural networks

Abstract

A Question Classification is an important task in Question Answering Systems and Information Retrieval among other NLP systems. Given a question, the aim of Question Classification is to find the correct type of answer for it. The focus of this paper is on Arabic question classification. We present a novel approach that combines a Support Vector Machine (SVM) and a Convolutional Neural Network (CNN). This method works in two stages: in the first stage, we identify the coarse/main question class using an SVM model; in the second stage, for each coarse question class returned by the SVM model, a CNN model is used to predict the subclass (finer class) of the main class. The performed tests have shown that our approach to Arabic Questions Classification yields very promising results.