This paper demonstrates that combination of multiple models achieves better classification performance than that obtained by existing individual models for question classification task in Bengali. We have exploited state of the art multiple model combination techniques, i.e., ensemble, stacking and voting on lexical, syntactical and semantic features of Bengali question for the question classification task. Bagging and boosting have been experimented as ensemble techniques. Na¨
['Somnath Banerjee', 'Sivaji Bandyopadhyay']
An Empirical Study of Combing Multiple Models in Bengali Question Classification