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182
Voted
KDD
2005
ACM
16 years 8 months ago
2005
ACM
While the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. Several approaches to finding overlapping clusters...
207
Voted
KDD
2005
ACM
16 years 8 months ago
2005
ACM
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
205
Voted
KDD
2005
ACM
16 years 8 months ago
2005
ACM
Many classification tasks, such as spam filtering, intrusion detection, and terrorism detection, are complicated by an adversary who wishes to avoid detection. Previous work on ad...
204
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KDD
2005
ACM
16 years 8 months ago
2005
ACM
Redescription mining is a newly introduced data mining problem that seeks to find subsets of data that afford multiple definitions. It can be viewed as a generalization of associa...
245
click to vote
KDD
2004
ACM
16 years 8 months ago
2004
ACM
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...