Recent developments in clustering algorithms

In this paper, we give a short review of recent developments in clustering. We shortly summarize important clustering paradigms before addressing important topics including metric adaptation in clustering, dealing with non-Euclidean data or large data sets, clustering evaluation, and learning theoretical foundations.

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