Proposal of a Generative type Travel Chatbot using Seq2Seq model - Jana, Subhadeep; Ghosh, Souradeep (International Journal of Computer Sciences and Engineering, 2020)
Artificial Intelligence and Machine Learning can be cited as one of the greatest technological advancements in this century. They are revolutionizing the fields of computing, finance, healthcare, agriculture, space, tourism. Powerful models have achieved excellent performance on a myriad of complex learning tasks. One such product of AI is a chatbot. A chatbot is an intelligent software which can simulate a conversation with a user like a real human being. Chatbots have found their use in customer service, recommender systems, smart appliances, etc. Chatbots can be broadly divided into 2 types: Retrieval and Generative. Retrieval type chatbots are trained to provide the best fit answer from a database of predefined responses, whereas, generative type chatbots can generate the final answer from a training corpus. This paper proposes the design and implementation of a generative type travel chatbot using seq2seq model, which can generate answers to the user queries based on Kolkata tourism.