Subgroup Discovery among Personal Homepages

  • Toyohisa Nakada
  • Susumu Kunifuji
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2843)


This paper discusses our algorithm for finding subgroups among personal homepages. Assuming that personal homepages usually carry personal information, we have developed an algorithm that allows us to automatically find potential patterns from them. For example, when the algorithm is applied to personal homepages at some school, we can approximate the ratio between the number of students interested in information science and that of students interested in social science. In the experiment, we successfully created subgroups that showed characteristics of the school. Also, we found relations between subgroups that are important for enhancing human activity.


Word Content Subgroup Discovery Seed Content Large Rectangle Unsupervised Learning Algorithm 
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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  1. 1.
    Donath, J.S.: Visual Who: Animating the affinities and activities of an electronic community. ACM Multimedia 95 (1995)Google Scholar
  2. 2.
    Ishida, T.: Towards Communityware. New Generation Computing 16(1), 5–22 (1998)CrossRefGoogle Scholar
  3. 3.
    Kauts, H., Selman, B., Shah, M.: The Hidden Web. AI Magazine 18(2), 27–36 (1997)Google Scholar
  4. 4.
    Murata, T.: Discovery of the Structures ofWeb Communities. JSAI SIG-KBSA002- 2, 7–12 (2000) (in Japanese)Google Scholar
  5. 5.
    Nakada, T., Ho, T.B., Kunifuji, S.: Finding Potential Human Communities From Personal Homepages. In: Proceedings of the IASTED International Conference ACI 2002, pp. 191–196 (2002)Google Scholar
  6. 6.
    Salton, G.: Automatic Text Processing. Addison-Wesley Publishing Company, Reading (1989)Google Scholar
  7. 7.
    Spiliopoulou, M., Faulstich, L.C., Winkler, K.: A Data Miner analyzing the Navigational Behavior of Web. In: Proceedings of the Workshop on Machine Learning in User Modeling of the ACAI 1999 (1999)Google Scholar
  8. 8.
    Sumi, Y., Mase, K.: Supporting Awareness of Shared Interests and Experiences in Community. In: Proceedings of the International Workshop on Awareness and the WWW, held at the ACM CSCW 2000 Conference (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Toyohisa Nakada
    • 1
  • Susumu Kunifuji
    • 1
  1. 1.Japan Advanced Institute of Science and TechnologyTatsunokuchi, IshikawaJapan

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