Design of Intelligent Customer Service Knowledge Base for Medical Insurance Based on Foundation-scale Models

Authors

  • Yixuan Lyu

DOI:

https://doi.org/10.54097/v4001r20

Keywords:

Medical insurance, knowledge base, vector database, natural language processing (NLP), foundation model.

Abstract

 In this paper, we propose a method for constructing an intelligent customer service knowledge base system for medical insurance based on natural language processing (NLP) models. This method utilizes a local vector database to construct the knowledge base system and retrieves industry knowledge by calling the vector database through foundation-scale models. The use of this technology ensures the security of business data and reduces platform training costs. The intelligent knowledge base of medical insurance constructed using this method can automatically handle user’s inquiries, complaints, and general business transactions, effectively improving the efficiency and intelligence level of customer service.

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References

Zhang, H., Ding, Y., Zhang, Y., Feng, S. (2021). Design and Implementation of an E-commerce Intelligent Customer Service System Based on Deep Neural Networks Software Engineering, 05: 33-37.

Wang, D., Wang, W., Wang, S., Fu, J., Zhu, F. (2017) A review of natural language understanding methods for limited domain question answering systems. Computer Science, 44 (8): 1-841.

Bao, J. (2014). Research on Knowledge Based Automatic Question Answering. Thesis of Harbin Institute of Technology.

Lu, J., Li, S. (2019) Design of an intelligent customer service robot question answering system based on a knowledge base. Computer Science and Applications, 9 (11): 2098-2104.

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Published

28-12-2023

Issue

Section

Articles

How to Cite

Lyu, Y. (2023). Design of Intelligent Customer Service Knowledge Base for Medical Insurance Based on Foundation-scale Models. Academic Journal of Science and Technology, 8(3), 56-59. https://doi.org/10.54097/v4001r20