A Review of AI-Driven Conversational Chatbots Implementation Methodologies and Challenges (1999–2022)

Chien-Chang Lin, Anna Y. Q. Huang and Stephen J. H. Yang ()
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Chien-Chang Lin: Department of Computer Science and Information Engineering, National Central University, Taoyuan 320317, Taiwan
Anna Y. Q. Huang: Department of Computer Science and Information Engineering, National Central University, Taoyuan 320317, Taiwan
Stephen J. H. Yang: Department of Computer Science and Information Engineering, National Central University, Taoyuan 320317, Taiwan

Sustainability, 2023, vol. 15, issue 5, 1-13

Abstract: A conversational chatbot or dialogue system is a computer program designed to simulate conversation with human users, especially over the Internet. These chatbots can be integrated into messaging apps, mobile apps, or websites, and are designed to engage in natural language conversations with users. There are also many applications in which chatbots are used for educational support to improve students’ performance during the learning cycle. The recent success of ChatGPT also encourages researchers to explore more possibilities in the field of chatbot applications. One of the main benefits of conversational chatbots is their ability to provide an instant and automated response, which can be leveraged in many application areas. Chatbots can handle a wide range of inquiries and tasks, such as answering frequently asked questions, booking appointments, or making recommendations. Modern conversational chatbots use artificial intelligence (AI) techniques, such as natural language processing (NLP) and artificial neural networks, to understand and respond to users’ input. In this study, we will explore the objectives of why chatbot systems were built and what key methodologies and datasets were leveraged to build a chatbot. Finally, the achievement of the objectives will be discussed, as well as the associated challenges and future chatbot development trends.

Keywords: conversational chatbot; chatbot; dialogue system; dialogue response; dialogue strategies; dialogue generation; machine learning; conversational agents (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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