基于BP神经网络的自然语言处理与信息检索系统

Zeyang Zheng
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引用次数: 1

摘要

自然语言处理是利用自然语言实现人机交流,帮助计算机快速理解自然语言所表达的意义的重要手段。自然语言处理技术最常见的应用系统是信息检索系统。在此基础上,讨论了一种基于BP神经网络(BPNN)和统计方法的信息处理模型,并详细说明了BPNN的原理。在对这些现象进行分析后,研究者认为自然语言处理更适合于需要准确结果的任务,并将自然语言处理的理解水平从低到高分为七个层次:语音层次→词法层次→词汇层次→句法层次→语义层次→语用层次→语境层次。在此基础上,讨论了自然语言处理在信息检索系统中的应用。
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Natural language processing and information retrieval system based on BP neural network
Natural language processing is an important means to realize the communication between man and machine using natural language, and help computers quickly understand the meaning expressed by natural language. The most common application system using natural language processing technology is information retrieval system. On this basis, an information processing model based on BP neural network (BPNN) and statistical method is discussed, and the principle of BPNN is explained in detail. After analyzing these phenomena, researchers think that natural language processing is more suitable for tasks requiring accurate results, and the understanding level of natural language processing is divided into seven levels from low level to high level: pronunciation level → morphology level → vocabulary level → syntax level → semantics level → pragmatics level → context level. On this basis, the application of natural language processing in information retrieval system is discussed.
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