Robust, Complete, and Efficient Correlation Clustering

@inproceedings{Achtert2007RobustCA,
  title={Robust, Complete, and Efficient Correlation Clustering},
  author={Elke Achtert and C. B{\"o}hm and H. Kriegel and Peer Kr{\"o}ger and A. Zimek},
  booktitle={SDM},
  year={2007}
}
Correlation clustering aims at the detection of data points that appear as hyperplanes in the data space and, thus, exhibit common correlations between different subsets of features. Recently proposed methods for correlation clustering usually suffer from several severe drawbacks including poor robustness against noise or parameter settings, incomplete results (i.e. missed clusters), poor usability due to complex input parameters, and poor scalability. In this paper, we propose the novel… Expand
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