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Novel method for searching ontologies on semantic web

机译:在语义网上搜索本体的新方法

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摘要

In order to solve the problem of information retrieval on the semantic web, a new semantic information retrieval (SIR) model for searching ontologies on the semantic web is proposed. First, SIR transformed domain ontologies into global ontologies. Then semantic index terms were extracted from these global ontologies. Based on semantic index terms, logical inferences can be performed and the logical views of the concept can be obtained. These logical views represent the expanded meaning of the concept. Using logical views, SIR can perform the information retrieval and inferences based on the semantic relationships in the documents, not only on the syntactic analysis of the documents. SIR can significantly enhance the recall and precision of the information retrieval by the semantic inference. Finally, the practicability of the SIR model is analyzed.
机译:为了解决语义网络上信息检索的问题,提出了一种新的语义信息检索(SIR)模型,用于在语义网络上进行本体搜索。首先,SIR将领域本体转换为全球本体。然后从这些全局本体中提取语义索引术语。基于语义索引项,可以执行逻辑推断并可以获得该概念的逻辑视图。这些逻辑视图代表了该概念的扩展含义。使用逻辑视图,SIR不仅可以基于文档的语法分析,还可以基于文档中的语义关系执行信息检索和推断。 SIR可以通过语义推理显着提高信息检索的回忆性和准确性。最后,分析了SIR模型的实用性。

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