  Artificial intelligence and natural language processing (NLP) are
increasingly being used in customer service to interact with users and answer
their questions. The goal of this systematic review is to examine existing
research on the use of NLP technology in customer service, including the
research domain, applications, datasets used, and evaluation methods. The
review also looks at the future direction of the field and any significant
limitations. The review covers the time period from 2015 to 2022 and includes
papers from five major scientific databases. Chatbots and question-answering
systems were found to be used in 10 main fields, with the most common use in
general, social networking, and e-commerce areas. Twitter was the second most
commonly used dataset, with most research also using their own original
datasets. Accuracy, precision, recall, and F1 were the most common evaluation
methods. Future work aims to improve the performance and understanding of user
behavior and emotions, and address limitations such as the volume, diversity,
and quality of datasets. This review includes research on different spoken
languages and models and techniques.
