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

Authors:
Yasufumi Takama;Kaoru Hirota
Affiliations:
Tokyo Metropolitan Institute of Technology, 6-6 Asahigaoka, Hino, Tokyo 191-0065 Japan, PREST, Japan Science and Technology Corporation, Japan;Tokyo Institute of Technology, 4259, Nagatsuta, Midori-ku, Yokohama 226-8502 Japan
Venue:
New Generation Computing - Special issue on chance discovery
Year:
2003

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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.