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Semantic Feature Expansion Technology Based on Knowledge Map

机译:基于知识图的语义特征扩展技术

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As one of the key techniques for improving both recall and precision rate in information retrieval, feature expansion has gradually become a hot direction in recent years. Feature expansion can effectively improve the problem of low retrieval efficiency brought by short query word ambiguity. Semantic features contain a lot of useful information but cannot be obtained directly from data, it is need to use some special methods and thus enable correct decoding of implicit messages. According to fact that knowledge graph has a lot of semantic concepts and semantic relations, this paper designed an automatic acquisition method of semantic feature expansion based on TCM knowledge graph. Experimental results for this method have verified semantic feature expansion technology.
机译:作为提高信息检索中召回和精密速率的关键技术之一,近年来的特征扩展逐渐成为一个热点。特征扩展可以有效地提高短查询词歧义所带来的低检索效率问题。语义功能包含大量有用的信息,但不能直接从数据获得,需要使用一些特殊方法,从而可以正确地解码隐式消息。根据知识图表有很多语义概念和语义关系,本文设计了一种基于TCM知识图的语义特征扩展的自动采集方法。该方法的实验结果已验证了语义特征扩展技术。

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