Towards effective and efficient mining of arbitrary shaped clusters

@article{Huang2014TowardsEA,
  title={Towards effective and efficient mining of arbitrary shaped clusters},
  author={Hao Huang and Yunjun Gao and Kevin Chiew and Lei Chen and Qinming He},
  journal={2014 IEEE 30th International Conference on Data Engineering},
  year={2014},
  pages={28-39}
}
Mining arbitrary shaped clusters in large data sets is an open challenge in data mining. Various approaches to this problem have been proposed with high time complexity. To save computational cost, some algorithms try to shrink a data set size to a smaller amount of representative data examples. However, their user-defined shrinking ratios may significantly affect the clustering performance. In this paper, we present CLASP an effective and efficient algorithm for mining arbitrary shaped… CONTINUE READING

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