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» A Set Correlation Model for Partitional Clustering
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GFKL
2007
Springer
123views Data Mining» more  GFKL 2007»
14 years 1 months ago
Projecting Dialect Distances to Geography: Bootstrap Clustering vs. Noisy Clustering
Abstract. Dialectometry produces aggregate distance matrices in which a distance is specified for each pair of sites. By projecting groups obtained by clustering onto geography on...
John Nerbonne, Peter Kleiweg, Wilbert Heeringa, Fr...
ICPR
2004
IEEE
14 years 8 months ago
Landscape of Clustering Algorithms
Numerous clustering algorithms, their taxonomies and evaluation studies are available in the literature. Despite the diversity of different clustering algorithms, solutions delive...
Anil K. Jain, Alexander P. Topchy, Martin H. C. La...
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
14 years 1 months ago
Combining partitions by probabilistic label aggregation
Data clustering represents an important tool in exploratory data analysis. The lack of objective criteria render model selection as well as the identification of robust solutions...
Tilman Lange, Joachim M. Buhmann
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 8 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
PODS
2005
ACM
115views Database» more  PODS 2005»
14 years 7 months ago
A divide-and-merge methodology for clustering
We present a divide-and-merge methodology for clustering a set of objects that combines a top-down "divide" phase with a bottom-up "merge" phase. In contrast, ...
David Cheng, Santosh Vempala, Ravi Kannan, Grant W...