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Semantic Clustering Approach Based Multi-agent System for Information Retrieval on Web

机译:基于语义聚类的多代理Web信息检索系统

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Document clustering is an important technology which helps users to organize the large amount of online information, especially after the rapid growth of the Web. This paper focuses on semantic document clustering method and its application in search engine. We proposed a multi-agent based information retrieval system to enhance the search process. The agents retrieve the results of Web search engine and organize the results by clustering them into different categories for a given query. We utilized WordNet ontology and several approaches to cluster results in appropriate category according to WordNet synsets. The experiment shows that semantic clustering work better than original clustering.
机译:文档集群是一项重要的技术,可帮助用户组织大量的在线信息,尤其是在Web快速发展之后。本文重点研究语义文档聚类方法及其在搜索引擎中的应用。我们提出了一种基于多主体的信息检索系统,以增强搜索过程。代理检索Web搜索引擎的结果,并通过将结果聚类到给定查询的不同类别中来组织结果。我们利用WordNet本体和几种方法根据WordNet同义词集将结果聚类在适当的类别中。实验表明,语义聚类比原始聚类更好。

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