%0 Journal Article
%1 citeulike:1144308
%A Borgelt, Christian
%A Nurnberger, Andreas
%B PKDD Workshop on Statistical Approaches for Web Mining
%C Pisa, Italy
%D 2004
%K clustering feature fuzzy selection
%T Fast Fuzzy Clustering of Web Page Collections
%X We study an extension of learning vector quantization that
draws on ideas from fuzzy clustering, enabling us to find fuzzy clusters of
ellipsoidal shape with a competitive learning scheme. This approach may
be seen as a kind of online fuzzy clustering, which can have advantages
w.r.t. the execution time of the clustering algorithm. We demonstrate the
usefulness of our approach by applying it to web page collections, which
are, in general, difficult to cluster due to the high number of dimensions
and the special distribution characteristics of the data.