A parallel clustering method combined information bottleneck theory and centroid-based clustering

@article{Sun2014APC,
  title={A parallel clustering method combined information bottleneck theory and centroid-based clustering},
  author={Zhanquan Sun and Geoffrey C. Fox and Weidong Gu and Zhao Li},
  journal={The Journal of Supercomputing},
  year={2014},
  volume={69},
  pages={452-467}
}
Clustering is an important research topic of data mining. Information bottleneck theory-based clustering method is suitable for dealing with complicated clustering problems because that its information loss metric can measure arbitrary statistical relationships between samples. It has been widely applied to many kinds of areas. With the development of information technology, the electronic data scale becomes larger and larger. Classical information bottleneck theory-based clustering method is… CONTINUE READING

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