Journal of Engineering Research

This paper focuses on the application cases of natural language processing technology based on deep learning in intelligent customer service. Firstly, it expounds on the challenges faced by current intelligent customer service systems, such as understanding complex user intents and providing accurate responses. Then, it conducts a detailed analysis of several key deep learning technologies, including but not limited to Recurrent Neural Network (RNN), Long Short-Term Memory network (LSTM), and Transformer model, and explains how these technologies can improve the performance of such systems. Through practical case studies, the potential of these technologies in enhancing customer service efficiency and improving the user experience is demonstrated. The adoption of deep learning technologies can significantly enhance the understanding ability and response quality of intelligent customer service, and provide users with more personalized and efficient services.

Deep learning; Natural language processing; Intelligent customer service; User intent recognition; Response accuracy