A Natural Language Processing Framework for Building Intelligent Customer Service Systems
Keywords:
Natural language processing technology, Intelligent customer service system, Multilingual supportAbstract
With the continuous development and improvement of artificial intelligence technology, natural language processing (NLP) has gained increasingly broad applications, especially in intelligent customer service systems, where it can both enhance service efficiency and improve user experience. This paper conducts an in-depth exploration of the application of NLP technology in intelligent customer service systems and analyzes the challenges it faces and its future development trends. The analysis reveals that by understanding, interpreting, and generating human language, NLP technology can effectively improve the efficiency and user experience of intelligent customer service systems. Its applications include semantic understanding and intent recognition, multi-turn dialogue management, sentiment analysis, speech recognition and generation, and machine translation. At the same time, the study finds that challenges such as linguistic diversity and ambiguity, context tracking and multi-turn dialogue difficulties, accuracy issues in sentiment analysis, and data privacy and security remain. In the future, dialogue management in intelligent customer service systems will become smarter, sentiment analysis more accurate, and multimodal interaction will become widespread.
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Copyright (c) 2025 Hanbing Wu
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