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An ontology search engine based on semantic analysis

机译:基于语义分析的本体搜索引擎

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摘要

Searching useful information and locating appropriate ontology from WWW or semantic Web is an important task in ontology research domain. The most difference between ontology information and common information is that ontology has semantic structure. In order to improve search precision by semantic analysis the paper proposes concepts-weights vectors matching algorithm (CWVMA). The algorithm firstly parses input messages and preliminary keywords based results into concepts sets. Then it decides matching rule according to influence of concepts set on ontology semantic and creates weight vector by matching rule. At last it obtains result vector as foundation of measure similarity between input messages and preliminary results. In addition, this paper designed and developed an ontology search engine based on the above algorithm -WI OntoSearch prototype system. The system can search about 4 billion Web pages by Google Web service. A lot of results of experiments explain the algorithm can improve precision of ontology search.
机译:搜索有用的信息并从WWW或语义Web找到适当的本体是本体研究领域的重要任务。本体信息与公共信息之间的最差异是本体结构具有语义结构。为了通过语义分析提高搜索精度,该论文提出了匹配算法(CWVMA)的概念重量向量。该算法首先将基于概念集的结果解析为概念集的输入消息和初步关键字。然后,它根据本体语义上设置的概念的影响决定匹配规则,并通过匹配规则创建权重向量。最后,它获得结果向量作为输入消息与初步结果之间的测量相似性的基础。此外,本文根据上述算法-WI OntoSearch原型系统设计和开发了一个本体搜索引擎。系统可以通过Google Web服务搜索约40亿个网页。大量的实验结果解释了该算法可以提高本体搜索的精度。

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