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Web of Proceedings - Francis Academic Press
Web of Proceedings - Francis Academic Press

Intelligent Customer Service System Design Based on Natural Language Processing

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DOI: 10.25236/iceeecs.2018.078


Wang Yijing

Corresponding Author

Wang Yijing


With the competition between the small and micro enterprises in the domestic market becoming increasingly fierce, many enterprises have considered reducing the internal operating costs and improving staff efficiency as well as external customer satisfaction to establish the company's own brand image gradually. On this occasion, building a company's own intelligent customer service system has gradually been taken seriously by many small businesses. However, the construction and maintenance costs of large-scale call center systems are not affordable for small enterprises. Therefore, developing a low-cost, small-capacity and easy-to-maintain voice system is crucial for the future development of small and micro enterprises. Based on this background, the machine learning and natural language processing techniques are used to implement the transformation of the customer service system from template-based responses to intelligent learning in this study. To explain the principles and analyze the advantages and disadvantages of the existing service systems, the common customer service systems on the market are summarized and classified firstly, which are used to summarize the requirements and outline the framework of the object design. On this basis, the "Turing Robot" platform is used to build an intelligent customer service system environment, of which test results shows that based on machine learning and semantic analysis, the intelligent customer service system tailored for small enterprises can provide accurate answers and intelligent services for customers all day.


Artificial Intelligence, Customer Service Systems, Natural Language Processing.