Sixth IEEE International Conference on Data Mining (ICDM'06)
COSMIC: Conceptually Specified Multi-Instance Clusters
Hong Kong
December 18-December 22
ISBN: 0-7695-2701-9
DOI Bookmark:
http://doi.ieeecomputersociety.org/10.1109/ICDM.2006.46
Recently, more and more applications represent data objects as sets of feature vectors or multi-instance objects. In this paper, we propose COSMIC, a method for deriving concept lattices from multi-instance data based on hierarchical density-based clustering. The found concepts correspond to groups or clusters of multi-instance objects having similar instances in common. We demonstrate that COSMIC outperforms compared methods with respect to efficiency and cluster quality and is capable to extract interesting patterns in multi-instance data sets.
Citation:
Hans-Peter Kriegel, Alexey Pryakhin, Matthias Schubert, Arthur Zimek, "COSMIC: Conceptually Specified Multi-Instance Clusters," icdm, pp.917-921, Sixth IEEE International Conference on Data Mining (ICDM'06), 2006
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