2008
DOI: 10.1002/cplx.20238
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On the parallel complexity of hierarchical clustering and CC‐complete problems

Abstract: Complex data sets are often unmanageable unless they can be subdivided and simplified in an intelligent manner. Clustering is a technique that is used in data mining

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Cited by 11 publications
(15 citation statements)
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References 29 publications
(41 reference statements)
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“…A prescribed flipping sequence is an ordering of edges in which each succeeding edge's labels may be flipped if and only if neither of its labels has already been flipped. This problem is NC-equivalent to the Lexicographically First Maximal Matching Problem, and so CC-complete; see [10] for a list of CCcomplete problems.…”
Section: Resultsmentioning
confidence: 99%
“…A prescribed flipping sequence is an ordering of edges in which each succeeding edge's labels may be flipped if and only if neither of its labels has already been flipped. This problem is NC-equivalent to the Lexicographically First Maximal Matching Problem, and so CC-complete; see [10] for a list of CCcomplete problems.…”
Section: Resultsmentioning
confidence: 99%
“…A variety of techniques have been developed for proving lower bounds on complexity of clustering [2,22,3]. When we run our Hadoop cluster on Amazon Elastic MapReduce, we can easily expand or shrink the number of virtual servers in our cluster depending on our processing needs.…”
Section: Introductionmentioning
confidence: 99%
“…r ← get_radius_centroid(c,C u ) 14: 6 Complexity on the actual demand or the relationship between the data in the dataset. For a covering with fewer sample points, the single linkage method (using the Euclidean distance) in the hierarchical clustering algorithm [24,25] is adopted to merge them to form an ellipsoidal domain, which means combing the most similar pair of clusters into a new cluster. Then, the similarities between the new cluster and the other clusters are updated, and the two most similar clusters are again merged.…”
mentioning
confidence: 99%