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An Overview of Machine Learning in Chatbots

Prissadang Suta 1, Xi Lan 2, Biting Wu 2, Pornchai Mongkolnam 1, and Jonathan H. Chan 1
1. School of Information Technology, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand
2. Division of Engineering Science, University of Toronto, Ontario, Canada

Abstract—A chatbot is an intelligent system which can hold a conversation with a human using natural language in real time. Due to the rise of Internet usage, many businesses now use online platforms to handle customer inquiries, and many of them turn to chatbots for improving their customer service or for streamlining operations and increasing their productivity. However, there is still a gap between existing chatbots and the autonomous, conversational agents businesses hope to implement. As such, this paper will first provide an overview of chatbots and then focus on research trends regarding the development of human-like chatbots capable of closing this technological gap. We reviewed the literature published over the past decade, from 1998 to 2018, and presented an overview of chatbots using a mind-map. The research findings suggest that chatbots operate in three steps: understanding the natural language input; generating an automatic, relevant response; and, constructing realistic and fluent natural language responses. The current bottleneck in designing artificially intelligent chatbots lies in the industry’s lack of natural language processing capabilities. Without the ability to properly understand the content and context of a user’s input, the chatbot cannot generate a relevant response.

Index Terms—chatbots, conversational agents, dialog system, human computer interaction

Cite: Prissadang Suta, Xi Lan, Biting Wu, Pornchai Mongkolnam, and Jonathan H. Chan, "An Overview of Machine Learning in Chatbots" International Journal of Mechanical Engineering and Robotics Research, Vol. 9, No. 4, pp. 502-510, April 2020. DOI: 10.18178/ijmerr.9.4.502-510