F. Murtagh. A survey of recent hierarchical clustering algorithms. The Computer Journal, 1983. Home/Search Document Not in Database Summary Related Articles Check |
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Clustering Large Datasets in Arbitrary Metric Spaces - Ganti, Ramakrishnan.. (1998) (27 citations) (Correct)
....2. Related Work and Initial Approaches In this section, we discuss related work on clustering, and three important issues that arise when clustering data in a distance space vis a vis clustering data in a coordinate space. Data clustering has been extensively studied in the Statistics [20], Machine Learning [12, 13] and Pattern Recognition literature [6, 7] These algorithms assume that all the data fits into main memory, and typically have running times super linear in the size of the dataset. Therefore, they do not scale to large databases. Recently, clustering has received ....
....in the dataset merely as objects. The distance between any two objects is returned by the Euclidean distance function. We now describe the evaluation methodology. The clustroids of the sub clusters returned by BUBBLE and BUBBLE FM are further clustered using a hierarchical clustering algorithm [20] to obtain the required number of clusters. To minimize the effect of hierarchical clustering on the final results, the amount of memory allocated to the algorithm was adjusted so that the number of sub clusters returned by BUBBLE or BUBBLE FM is very close (not exceeding the actual number of ....
F. Murtagh. A survey of recent hierarchical clustering algorithms. The Computer Journal, 1983.
Clustering Large Datasets in Arbitrary Metric Spaces - Venkatesh Ganti Raghu (1999) (27 citations) (Correct)
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F. Murtagh. A survey of recent hierarchical clustering algorithms. The Computer Journal, 1983.
Flexible Clustering by Tendency in High Dimensional Space - Liu, Wang (2003) (Correct)
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F. Murtagh. A survey of recent hierarchical clustering algorithms. In The Computer Journal, 1983.
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