K-medoids clustering based on MapReduce and optimal search of medoids

@article{Zhu2014KmedoidsCB,
  title={K-medoids clustering based on MapReduce and optimal search of medoids},
  author={Ying-ting Zhu and Fu-zhang Wang and Xing-hua Shan and Xiao-yan Lv},
  journal={2014 9th International Conference on Computer Science & Education},
  year={2014},
  pages={573-577}
}
When there are noises and outliers in the data, the traditional k-medoids algorithm has good robustness, however, that algorithm is only suitable for medium and small data set for its complex calculation. MapReduce is a programming model for processing mass data and suitable for parallel computing of big data. Therefore, this paper proposed an improved algorithm based on MapReduce and optimal search of medoids to cluster big data. Firstly, according to the basic properties of triangular… CONTINUE READING
6 Citations
13 References
Similar Papers

References

Publications referenced by this paper.
Showing 1-10 of 13 references

Parallel implementing k­ means clustering algorithm using MapReduce programming mode[J].J

  • JIANG Xiao-ping, 11 Cheng-hua, XIANG Wen
  • Huazhong Univ. of Sci.&Tech.(Natural Science…
  • 2012

Research on parallelization of clustering algorithm based on MapReduce[O

  • LI Ying-an
  • Sun Vat-Sen University,
  • 2010

A simple and fast algorithm for kmedoids clustering [ l ]

  • H.-S. Park, C. H. Iun
  • Expert Systems with Applications
  • 2009

Hadoop: the definitive guide [M]. the United States of America: O'Reilly Media, Inc.

  • Tom White
  • 2009

Iun, C.H..A simple and fast algorithm for k-medoids clustering[l

  • Park, H.-S
  • Expert Systems with Applications36
  • 2009

A New and et1icient k-medoidsalgorithm for spatial clustering[R].ComputationaIScience and Its Applications.Springer,2005

  • Q.lhang, Couloigner
  • 2005

Parallel implementing k ­ means clustering algorithm using MapReduce programming mode [ J ]

  • XIANG Wen
  • ComputationaIScience and Its Applications
  • 2005

Similar Papers

Loading similar papers…