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Extracting Social Networks Among Various Entities on the Web

  • Yingzi Jin
  • Yutaka Matsuo
  • Mitsuru Ishizuka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4519)

Abstract

Social networks have recently attracted much attention for their importance to the Semantic Web. Several methods exist to extract social networks for people (particularly researchers) from the web using a search engine. Our goal is to expand existing techniques to obtain social networks among various entities. This paper proposes two improvements, i.e. relation identification and threshold tuning, which enable us to deal with complex and inhomogeneous communities. Social networks among firms and artists (of contemporary) are extracted as examples: Several evaluations emphasize the effectiveness of these methods. Our system was used at the International Triennale of Contemporary Art (Yokohama Triennale 2005) to facilitate navigation of artists’ information. This study contributes to the Semantic Web in that we increase the applicability of social network extraction for several studies.

Keywords

Social Network Search Engine Social Network Analysis Betweenness Centrality Training Corpus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Yingzi Jin
    • 1
  • Yutaka Matsuo
    • 2
  • Mitsuru Ishizuka
    • 1
  1. 1.University of Tokyo, Hongo 7–3–1, Tokyo 113-8656Japan
  2. 2.National Institute of Advanced Industrial Science and Technology 

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