A Sentiment Based Non-Factoid Question-Answering Framework


With the rapid advances in Artificial Intelligence, a question of emotional intelligence of a system may become as important as its accuracy. This paper investigates whether emotions should be considered for non-factoid “how” Question-Answering systems with the eventual goal of enabling the system to retrieve answers in a more emotionally intelligent way. This study proposes an architecture that adds extended representation of sentiment information to questions and answers, and reports on to what extent a prediction of the best answer be improved by the proposed architecture.

In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)
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Kanishka Misra
Kanishka Misra
PhD Candidate

My research interests include Natural Language Processing, Cognitive Science, and Deep Learning.