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hierarchical overlapping clustering; computational complexity; approximation of a given dissimilarity measure; $k$-ultrametric; Robinson dissimilarity measure; decision problems; NP-complete
In this paper the computational complexity of the problem of the approximation of a given dissimilarity measure on a finite set $X$ by a $k$-ultrametric on $X$ and by a Robinson dissimilarity measure on $X$ is investigared. It is shown that the underlying decision problems are NP-complete.
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