Dec. 18, 2006 to Dec. 22, 2006
Hans-Peter Kriegel , Ludwig-Maximilians-Universitat, Germany
Alexey Pryakhin , Ludwig-Maximilians-Universitat, Germany
Matthias Schubert , Ludwig-Maximilians-Universitat, Germany
Arthur Zimek , Ludwig-Maximilians-Universitat, Germany
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.
Hans-Peter Kriegel, Alexey Pryakhin, Matthias Schubert, Arthur Zimek, "COSMIC: Conceptually Specified Multi-Instance Clusters", ICDM, 2006, Sixth International Conference on Data Mining (ICDM'06), Sixth International Conference on Data Mining (ICDM'06) 2006, pp. 917-921, doi:10.1109/ICDM.2006.46