Abstract
Information resources on the Internet, including Web pages and news articles, constitute a huge, ill-structured, and continuously growing information space. Knowledge discovery from the Internet is a challenge. It includes useful knowledge that is difficult to be automatically exploited by the following reasons
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The Internet is full of junk pages and articles. Conventional techniques rarely tolerate so noisy information as often found on the Internet
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A single page or an article on the net is often too fine-grained as a unit of knowledge. We need techniques to extract a cluster of inter-related finegrained pages and/or articles with semantic relationships among them
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© 1998 Springer-Verlag Berlin Heidelberg
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Shibayama, E., Yabe, J., Takahashi, S., Matsuda, M. (1998). Visualizing Semantic Clusters in the Internet Information Space. In: Arikawa, S., Motoda, H. (eds) Discovey Science. DS 1998. Lecture Notes in Computer Science(), vol 1532. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49292-5_45
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DOI: https://doi.org/10.1007/3-540-49292-5_45
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