A simple and fast algorithm for K-medoids clustering
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1,234 citations
Cites background from "A simple and fast algorithm for K-m..."
...K-means [7] and K-medoids [8] are the two most famous ones of this kind of clustering algorithms....
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833 citations
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Cites methods from "A simple and fast algorithm for K-m..."
...Then, they performed clustering via the K-medoids method on the calculated molecular dynamics trajectories [88] to identify MD-derived representative conformations of the investigated targets....
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659 citations
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Cites background from "A simple and fast algorithm for K-m..."
...3, apply to k-medoids as well, but it is less sensitive to outliers [84]....
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References
24,320 citations
"A simple and fast algorithm for K-m..." refers methods in this paper
...The proposed algorithm calculates the distance matrix once and uses it for finding new medoids at every iterative step....
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...K-means clustering (MacQueen, 1967) and partitioning around medoids (Kaufman & Rousseeuw, 1990) are well known techniques for performing non-hierarchical clustering....
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14,144 citations
"A simple and fast algorithm for K-m..." refers background in this paper
...Ng and Han (1994) proposed an efficient PAM-based algorithm, which updates new medoids from some neighboring objects. van der Laan, Pollard, and Bryan (2003) tried to maximize the silhouette proposed by Rousseeuw (1987) instead of minimizing the sum of distances to the closest medoid in PAM....
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10,537 citations
"A simple and fast algorithm for K-m..." refers methods in this paper
...Among many algorithms for K-medoids clustering, partitioning around medoids (PAM) proposed by Kaufman and Rousseeuw (1990) is known to be most powerful....
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...Kaufman and Rousseeuw (1990) also proposed an algorithm called CLARA, which applies the PAM to sampled objects instead of all objects....
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...K-means clustering (MacQueen, 1967) and partitioning around medoids (Kaufman & Rousseeuw, 1990) are well known techniques for performing non-hierarchical clustering....
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9,011 citations
3,106 citations