LD-BSCA: A local-density based spatial clustering algorithm

@article{Wei2009LDBSCAAL,
  title={LD-BSCA: A local-density based spatial clustering algorithm},
  author={Guiyi Wei and Haiping Liu},
  journal={2009 IEEE Symposium on Computational Intelligence and Data Mining},
  year={2009},
  pages={291-298}
}
Density-based clustering algorithms are very powerful to discover arbitrary-shaped clusters in large spatial databases. However, in many cases, varied local-density clusters exist in different regions of data space. In this paper, a new algorithm LD-BSCA is proposed with introducing the concept of local MinPts (a minimum number of points) and the new cluster expanding condition: ExpandConClId (Expanding Condition of ClId-th Cluster). We minimize the algorithm input down to only one parameter… CONTINUE READING

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