语义网站点的发现与排序

发布时间：2018-08-30 08:00

【摘要】：随着语义网中RDF数据的大量涌现,语义搜索引擎为用户搜索RDF数据带来了便利.但是,如何自动地发现包含语义网信息资源的站点,并高效地在语义网站点中收集语义网信息资源,一直是语义搜索引擎所面临的问题.首先介绍了语义网站点的链接模型.该模型刻画了语义网站点、语义网信息资源、RDF模型和语义网实体之间的关系.基于该模型讨论了语义网实体的归属问题,并进一步定义了语义网站点的发现规则;另外,从站点链接模型出发,定义了语义网站点依赖图,并给出了对语义网站点进行排序的算法.将相关算法在一个真实的语义搜索引擎中进行了初步测试.实验结果表明,所提出的方法可以有效地发现语义网站点并对站点进行排序.
[Abstract]:With the emergence of a large number of RDF data in the semantic web, semantic search engines have brought convenience for users to search for RDF data. However, how to automatically find sites containing semantic web information resources and efficiently collect semantic web information resources in semantic web sites is always a problem for semantic search engines. Firstly, the link model of semantic site points is introduced. The model describes the relationship among semantic Web sites, semantic Web information resources, RDF models and semantic Web entities. Based on this model, this paper discusses the problem of semantic web entities' attribution, and further defines the discovery rules of semantic site points, and defines the semantic site point dependency graph based on the site link model. An algorithm for sorting semantic site points is also presented. The related algorithms are tested in a real semantic search engine. The experimental results show that the proposed method can effectively find the semantic sites and sort the sites.
【作者单位】：东南大学计算机科学与工程学院;
【基金】：国家自然科学基金No.60773106 国家重点基础研究发展计划(973)No.2003CB317004~~
【分类号】：TP393.092

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