中文摘要：

在语义网上不断出现的链接数据能够为社会网络分析提供大规模的数据资源。尤其是,它能够用来对特定的域结构进行社会社区结构的探索。使用基于本体的知识结构,通过从域中的链接数据来发现特定的属性,并结合提出的距离计算方法和聚类方法,能够改进域中人之间的相关性和聚类的定制,从而从链接数据中发现域中包含的社会社区结构。通过在真实的域中的链接数据上进行测试,结果证明方法能够在各个不同的域中（音乐,电影）发现可靠有价值的社会社区。

英文摘要：

Continual emergence of linked data on semantic Web can provide comprehensive data resources for social network analysis.In particular,it enables the exploration on social community structures within a special domain structure.To use ontology-based knowledge structure,to discover specific properties from linked data in domain,and to incorporate the proposed distance calculate method and a clustering method,these are able to improve the correlation of people in domain and the customisation of clustering,and then to discover the social community structures included in the domain from linked data.By testing the method on linked data in real domain,the result shows that it can find reliable and valuable social communities from different domains such as music and film.