A Comprehensive Comparison of Machine Learning Based Methods Used in Bengali Question Classification
This work addresses the need for improved question classification in Bengali QA systems, but it is incremental as it focuses on comparing existing methods rather than introducing new ones.
The authors compared machine learning methods for Bengali question classification, evaluating performance and computational complexity to identify effective approaches for this task.
QA classification system maps questions asked by humans to an appropriate answer category. A sound question classification (QC) system model is the pre-requisite of a sound QA system. This work demonstrates phases of assembling a QA type classification model. We present a comprehensive comparison (performance and computational complexity) among some machine learning based approaches used in QC for Bengali language.