ClustNails : visual analysis of subspace clusters

Subspace clustering addresses an important problem in clustering multi-dimensional data. In sparse multi-dimensional data, many dimensions are irrelevant and obscure the cluster boundaries. Subspace clustering helps by mining the clusters present in only locally relevant subsets of dimensions. However, understanding the result of subspace clustering by analysts is not trivial. In addition to the grouping information, relevant sets of dimensions and overlaps between groups, both in terms of dimensions and records, need to be analyzed. We introduce a visual subspace cluster analysis system called ClustNails. It integrates several novel visualization techniques with various user interaction facilities to support navigating and interpreting the result of subspace clustering. We demonstrate the effectiveness of the proposed system by applying it to the analysis of real world data and comparing it with existing visual subspace cluster analysis systems.

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TATU, Andrada, Leishi ZHANG, Enrico BERTINI, Tobias SCHRECK, Daniel A. KEIM, Sebastian BREMM, Tatiana VON LANDESBERGER, 2012. ClustNails : visual analysis of subspace clusters. In: Tsinghua Science and Technology. 2012, 17(4), pp. 419-428. ISSN 1007-0214. eISSN 1878-7606. Available under: doi: 10.1109/TST.2012.6297588

BibTex

@article{Tatu2012Clust-22559,
  year={2012},
  doi={10.1109/TST.2012.6297588},
  title={ClustNails : visual analysis of subspace clusters},
  number={4},
  volume={17},
  issn={1007-0214},
  journal={Tsinghua Science and Technology},
  pages={419--428},
  author={Tatu, Andrada and Zhang, Leishi and Bertini, Enrico and Schreck, Tobias and Keim, Daniel A. and Bremm, Sebastian and von Landesberger, Tatiana}
}

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