A critical review of state‐of‐the‐art chatbot designs and applications

IF 6.4 2区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery Pub Date : 2021-10-25 DOI:10.1002/widm.1434

Bei Luo, Raymond Y. K. Lau, Chunping Li, Yain-Whar Si

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引用次数: 72

Abstract

Chatbots are intelligent conversational agents that can interact with users through natural languages. As chatbots can perform a variety of tasks, many companies have committed numerous resources to develop and deploy chatbots to enhance various business processes. However, we lack an up‐to‐date critical review that thoroughly examines both state‐of‐the‐art technologies and innovative applications of chatbots. In this review, we not only critically analyze the various computational approaches used to develop state‐of‐the‐art chatbots, but also thoroughly review the usability and applications of chatbots for various business sectors. We also identify gaps in chatbot‐related studies and propose new research directions to address the shortcomings of existing studies and applications. Our review advances both academic research and practical business applications of state‐of‐the‐art chatbots. We provide guidance for practitioners to fully realize the business value of chatbots and assist in making sensible decisions related to the development and deployment of chatbots in various business contexts. Researchers interested in the design and development of chatbots can also gain useful insights from our critical review and identify fruitful research topics and future research directions based on the research gaps discussed herein.

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来源期刊

Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

22.70

自引率

2.60%

发文量

审稿时长

>12 weeks

期刊介绍： The goals of Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (WIREs DMKD） are multifaceted. Firstly, the journal aims to provide a comprehensive overview of the current state of data mining and knowledge discovery by featuring ongoing reviews authored by leading researchers. Secondly, it seeks to highlight the interdisciplinary nature of the field by presenting articles from diverse perspectives, covering various application areas such as technology, business, healthcare, education, government, society, and culture. Thirdly, WIREs DMKD endeavors to keep pace with the rapid advancements in data mining and knowledge discovery through regular content updates. Lastly, the journal strives to promote active engagement in the field by presenting its accomplishments and challenges in an accessible manner to a broad audience. The content of WIREs DMKD is intended to benefit upper-level undergraduate and postgraduate students, teaching and research professors in academic programs, as well as scientists and research managers in industry.