p-PIC: Parallel power iteration clustering for big data

  title={p-PIC: Parallel power iteration clustering for big data},
  author={Weizhong Yan and Umang Brahmakshatriya and Ya Xue and Mark Gilder and Bowden Wise},
  journal={J. Parallel Distrib. Comput.},
Power iteration clustering (PIC) is a newly developed clustering algorithm. It performs clustering by embedding data points in a low-dimensional subspace derived from the similarity matrix. Compared to traditional clustering algorithms, PIC is simple, fast and relatively scalable. However, it requires the data and its associated similarity matrix fit into memory, which makes the algorithm infeasible for big data applications. This paper attempts to expand PIC’s data scalability by implementing… CONTINUE READING
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