面向搜索引擎的自然语言理解的设计与实现

Design and Implementation of Natural Language Understanding for Search Engine

提出了一种针对智能检索的自然语言理解的实现模型。该模型通过句模分析、分词和概念扩展的方法来理解问句,在一定程度上提高理解自然语言的能力。详细介绍了其系统架构、实现思想和原理。最后通过一系列的实例来对普通搜索引擎和加载了本模型的搜索引擎进行测试。实验结果表明,提出的模型能有效地分析自然语言提问,提高信息检索的准确性和智能性。

Natural Language Understanding （NLU） has been one of the highlights in computer science, and the paper proposes a model which can implement NLU for the intelligent search engine, it understands the natural language by sentence model analysis, word segment and concept, so it can increase the ability of understanding the natural language. Then we introduce the system architecture, idea, and theory in detail. Finally, we compare the normal search engine and another which based on our model by some concrete sentences, the results show that the model can increase the precision and the intelligence of information retrieval.