Chance Discoveries from the WWW

  • Naohiro Matsumura
  • Yukio Ohsawa
Part of the Advanced Information Processing book series (AIP)


In this chapter, we introduce a method that can help understand significant and novel — i.e. emerging — topics. Here, KeyGraph is extended to be a method for the analysis and visualization of co-citations between Web pages. Communities, each having members (Web pages, their authors, and readers) with common interests are obtained as graph-based clusters, and an emerging topic is detected as a Web page relevant to multiple communities, corresponding to weak ties between strongly tied communities. An ultimate application of our method might be to understand the chances for governments and citizens, i.e. for discussing and deciding how we should deal with essential factors underlying emergent social events.


Human Genome Mobile Phone Human Genome Project Query Term Graphical Output 
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-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Naohiro Matsumura
    • 1
    • 2
  • Yukio Ohsawa
    • 1
    • 3
  1. 1.PRESTOJapan Science and Technology CorporationMiyagino-ku, Sendai, MiyagiJapan
  2. 2.Graduate School of Engineeringthe University of TokyoBunkyo-ku, TokyoJapan
  3. 3.Graduate School of Business SciencesUniversity of TokyoBunkyoku, TokyoJapan

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