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A Fuzzy Neighborhood Model for Clustering, Classification, and Approximations

  • Conference paper
Rough Sets and Current Trends in Computing (RSCTC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4259))

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Abstract

A fuzzy neighborhood model for analyzing information systems having topological structures on occurrences of keywords is proposed and algorithms of clustering, classification and approximations similar to generalized rough sets are developed. Real applications include text mining and clustering of keywords on the web. An illustrative example is given.

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© 2006 Springer-Verlag Berlin Heidelberg

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Miyamoto, S., Hayakawa, S. (2006). A Fuzzy Neighborhood Model for Clustering, Classification, and Approximations. In: Greco, S., et al. Rough Sets and Current Trends in Computing. RSCTC 2006. Lecture Notes in Computer Science(), vol 4259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11908029_91

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  • DOI: https://doi.org/10.1007/11908029_91

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-47693-1

  • Online ISBN: 978-3-540-49842-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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