Upadhya, B.A.Udupa, S.Kamath S․, S.S.2026-02-0620192019 10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019, 2019, Vol., , p. -https://doi.org/10.1109/ICCCNT45670.2019.8944861https://idr.nitk.ac.in/handle/123456789/31025Automatic generation of responses to questions is a challenging problem that has applications in fields like customer support, question-answering forums etc. Prerequisite to developing such systems is a requirement for a methodology that classifies questions as yes/no or opinion-based questions, so that quick and accurate responses can be provided. Performing this classification is advantageous, as yes/no questions can generally be answered using the data that is already available. In the case of an opinion-based or a yes/no question that wasn't previously answered, an external knowledge source is needed to generate the answer. We propose a LSTM based model that performs question classification into the two aforementioned categories. Given a question as an input, the objective is to classify it into opinion-based or yes/no question. The proposed model was tested on the Amazon community question-answer dataset as it is reflective of the problem statement we are trying to solve. The proposed methodology achieved promising results, with a high accuracy rate of 91% in question classification. © 2019 IEEE.ClassificationDeep LearningSoft ComputingSupervised learning