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NIPS
2003
15 years 7 months ago
Clustering with the Connectivity Kernel
Clustering aims at extracting hidden structure in dataset. While the problem of finding compact clusters has been widely studied in the literature, extracting arbitrarily formed ...
Bernd Fischer, Volker Roth, Joachim M. Buhmann
MICAI
2007
Springer
15 years 11 months ago
Fuzzifying Clustering Algorithms: The Case Study of MajorClust
Among various document clustering algorithms that have been proposed so far, the most useful are those that automatically reveal the number of clusters and assign each target docum...
Eugene Levner, David Pinto, Paolo Rosso, David Alc...
INCDM
2007
Springer
97views Data Mining» more  INCDM 2007»
15 years 11 months ago
Clustering by Random Projections
Abstract. Clustering algorithms for multidimensional numerical data must overcome special difficulties due to the irregularities of data distribution. We present a clustering algo...
Thierry Urruty, Chabane Djeraba, Dan A. Simovici
ADBIS
2007
Springer
143views Database» more  ADBIS 2007»
15 years 11 months ago
Aggregating Multiple Instances in Relational Database Using Semi-Supervised Genetic Algorithm-based Clustering Technique
In solving the classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets sto...
Rayner Alfred, Dimitar Kazakov
ESCAPE
2007
Springer
256views Algorithms» more  ESCAPE 2007»
15 years 9 months ago
A More Effective Linear Kernelization for Cluster Editing
In the NP-hard Cluster Editing problem, we have as input an undirected graph G and an integer k 0. The question is whether we can transform G, by inserting and deleting at most k ...
Jiong Guo