Abstract
Recently, the conversational agents like Chatbots are widely employed for achieving a better Human-Computer Interaction (HCI). In this paper, a retrieval based chatbot is designed using Natural Language Processing (NLP) techniques and a Multilayer Perceptron (MLP) neural network. The purpose of the chatbot is to extract user’s feedback based on the services provided to them. User feedback is a very essential component for the betterment of the service. Chatbot serves as a better interface for obtaining an appropriate user feedback. Furthermore, sentiment analysis is done on the feedback as a result a suitable response is delivered to the user. A Long Short Term Neural Network (LSTM) is used to classify the sentiment of the feedback.
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Nivethan, Sankar, S. (2020). Sentiment Analysis and Deep Learning Based Chatbot for User Feedback. In: Balaji, S., Rocha, Á., Chung, YN. (eds) Intelligent Communication Technologies and Virtual Mobile Networks. ICICV 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 33. Springer, Cham. https://doi.org/10.1007/978-3-030-28364-3_22
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DOI: https://doi.org/10.1007/978-3-030-28364-3_22
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