ISWC 2006 5th International Semantic Web Conference
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Extracting Relations in Social Networks from Web using Similarity between Collective Contexts
Junichiro Mori University of Tokyo
Takumi Tsujishita University of Tokyo
Yutaka Matsuo National Institute of Advanced Industrial Science and Technology, Japan
Mitsuru Ishizuka University of Tokyo

Social networks have recently garnered considerable interest. With the intention of utilizing social networks for the SemanticWeb, several studies have examined automatic extraction of social networks. However, most methods have addressed extracting the strength of relations. Our goal is extracting underlying relations between entities embedded in social networks. To this end, we propose a method that automatically extracts labels that describe relations between entities. The fundamental idea is to cluster similar entity pairs according to their collective contexts in Web documents. The descriptive labels for relations are obtained from results of clustering. The proposed method is entirely unsupervised and is easily incorporated with existing social network extraction methods. Our method also contributes to ontology population by find relations between intances in social network. Our experiments conducted on entities in political social networks achieved clustering with high precision and recall. We were able to extract appropriate relation labels to represent the entities.


5th International Semantic Web Conference, Athens, GA, USA, November 5-9, 2006, LNCS 4273




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