(University of State Malang, Indonesia)(2) Aji Prasetya Wibawa
(University of State Malang, Indonesia)(3) Hariyono Hariyono
(University of State Malang, Indonesia)(4) Andrew Nafalski
(University of South Australia, Australia)*corresponding author
AbstractChatbot technology, a rapidly growing field, uses Natural Language Processing (NLP) methodologies to create conversational AI bots. Contextual understanding is essential for chatbots to provide meaningful interactions. Still, to date chatbots often struggle to accurately interpret user input due to the complexity of natural language and diverse fields, hence the need for a Systematic Literature Review (SLR) to investigate the motivation behind the creation of chatbots, their development procedures and methods, notable achievements, challenges and emerging trends. Through the application of the PRISMA method, this paper contributes to revealing the rapid and dynamic progress in chatbot technology with NLP learning models, enabling sophisticated and human-like interactions on the trends observed in chatbots over the past decade. The results, from various fields such as healthcare, organization and business, virtual personalities, to education, do not rule out the possibility of being developed in other fields such as chatbots for cultural preservation while suggesting the need for supervision in the aspects of language comprehension bias and ethics of chatbot users. In the end, the insights gained from SLR have the potential to contribute significantly to the advancement of chatbots on NLP as a comprehensive field. KeywordsDomain Chatbot; Rule-based Chatbot; Generative AI Chatbots; NLP; Culture Heritage
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DOIhttps://doi.org/10.31763/ijrcs.v3i4.1195 |
Article metrics10.31763/ijrcs.v3i4.1195 Abstract views : 955 | PDF views : 366 |
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