A highly scalable clustering scheme using boundary information

Pattern Recognition Letters, pp. 1-7, 2017.

Cited by: 11|Bibtex|Views21|DOI:https://doi.org/10.1016/j.patrec.2017.01.016
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Other Links: dblp.uni-trier.de|dl.acm.org|academic.microsoft.com

Abstract:

Many advanced clustering techniques are effective in dealing datasets in complicated situations. However, when facing large datasets, which are increasingly common in the era of big data, the time requirements of most existing techniques can quickly become intolerable. To tackle this challenge, in this paper, we propose Scalable Clusterin...More

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