Finding generalized projected clusters in high dimensional spaces

  title={Finding generalized projected clusters in high dimensional spaces},
  author={C. Aggarwal and Philip S. Yu},
  booktitle={SIGMOD '00},
  • C. Aggarwal, Philip S. Yu
  • Published in SIGMOD '00 2000
  • Computer Science
  • High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimensional data, even the concept of proximity or clustering may not be meaningful. We discuss very general techniques for projected clustering which are able to construct clusters in arbitrarily aligned subspaces of lower dimensionality. The subspaces are specific to the clusters themselves. This definition is substantially… CONTINUE READING
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