POLYPHONET: An advanced social network extraction system from the Web
Web Semantics: Science, Services and Agents on the World Wide Web
ArnetMiner: extraction and mining of academic social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Topic and role discovery in social networks with experiments on enron and academic email
Journal of Artificial Intelligence Research
Clustering technique in multi-document personal name disambiguation
ACLstudent '09 Proceedings of the ACL-IJCNLP 2009 Student Research Workshop
Flink: Semantic Web technology for the extraction and analysis of social networks
Web Semantics: Science, Services and Agents on the World Wide Web
Extracting relations in social networks from the web using similarity between collective contexts
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
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Social network analysis (SNA) has become one of the main themes in the Semantic Web agenda. The use of web is steadily gaining ground in the study of social networks. Few researchers have shown the possibility of extracting social network from the Web via search engine. However to get a rich and trusted social network from such an approach proved to be difficult. In this paper we proposed an Information Retrieval (IR) driven method for dealing with the heterogeneity of features in the Web. We demontrate the possibility of exploiting features in Web snippets returned by search engines for disambiguating entities and building relations among entities during the process of extracting social networks. Our approach has shown the capacity to extract underlying strength relations which are beyond recognition using the standard co-occurrence analysis employed by many research.