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Web information visualization method employing immune network model for finding topic stream from document-set sequence

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Abstract

A Web information visualization method based on the document set-wise processing is proposed to find the topic stream from a sequence of document sets. Although the hugeness as well as its dynamic nature of the Web is burden for the users, it will also bring them a chance for business and research if they can notice the trends or movement of the real world from the Web. A sequence of document sets found on the Web, such as online news article sets is focused on in this paper. The proposed method employs the immune network model, in which the property of memory cell is used to find the topical relation among document sets. After several types of memory cell models are proposed and evaluated, the experimental results show that the proposed method with memory cell can find more topic streams than that without memory cell.

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Author information

Authors and Affiliations

  1. Tokyo Metropolitan Institute of Technology, 6-6 Asahigaoka, Hino, 191-0065, Tokyo, Japan

    Yasufumi Takama

  2. PREST, Japan Science and Technology Corporation, Japan

    Yasufumi Takama

  3. Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, 226-8502, Yokohama, Japan

    Kaoru Hirota

Authors
  1. Yasufumi Takama
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  2. Kaoru Hirota
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Corresponding author

Correspondence to Yasufumi Takama.

Additional information

Yasufumi Takama, D.Eng.: He received his B.S., M.S. and Dr.Eng. degrees from the University of Tokyo in 1994, 1996, and 1999, respectively. From 1999 to 2002 he was with Tokyo Institute of Technology, Japan. Since 2002, he has been Associate Professor of Department of Electronic Systems and Engineering, Tokyo Metropolitan Institute of Technology, Tokyo, Japan. He has also been participating in JST (Japan Science and Technology Corporation) since October 2000. His current research interests include artificial intelligence, Web information retrieval and visualization systems, and artificial immune systems. He is a member of JSAI (Japanese Society of Artificial Intelligence), IPS J (Information Processing Society of Japan), and SOFT (Japan Society for Fuzzy Theory and Systems).

Kaoru Hirota, D.Eng.: He received his B.E., M.E. and Dr.Eng. degrees in electronics from Tokyo Institute of Technology, Tokyo, Japan, in 1974, 1976, and 1979, respectively. From 1979 to 1982 and from 1982 to 1995 he was with the Sagami Institute of Technology and Hosei University, respectively. Since 1995, he has been with the Interdisciplinary Graduate School of Science and Technology, Tokyo Institute of Technology, Yokohama, Japan. He is now a department head professor of Department of Computational Intelligence and Systems Science. Dr.Hirota is a member of IFSA (International Fuzzy Systems Association (Vice President 1991–1993), Treasurer 1997–2001), IEEE (Associate Editors of IEEE Transactions on Fuzzy Systems (1993–1995) and IEEE Transactions on Industrial Electronics (1996–2000)) and SOFT (Japan Society for Fuzzy Theory and Systems (Vice President 1995–1997, President 2001–2003)), and he is an editor in chief of Int. J. of Advanced Computational Intelligence.

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Takama, Y., Hirota, K. Web information visualization method employing immune network model for finding topic stream from document-set sequence. NGCO 21, 49–59 (2003). https://doi.org/10.1007/BF03042325

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  • DOI: https://doi.org/10.1007/BF03042325

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