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» A Method for Dynamic Clustering of Data
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ICPR
2008
IEEE
15 years 6 months ago
An extended version of the k-means method for overlapping clustering
This paper deals with overlapping clustering, a trade off between crisp and fuzzy clustering. It has been motivated by recent applications in various domains such as information r...
Guillaume Cleuziou
DMKD
1997
ACM
308views Data Mining» more  DMKD 1997»
15 years 4 months ago
A Fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining
Partitioning a large set of objects into homogeneous clusters is a fundamental operation in data mining. The k-means algorithm is best suited for implementing this operation becau...
Zhexue Huang
PR
2010
156views more  PR 2010»
14 years 10 months ago
Semi-supervised clustering with metric learning: An adaptive kernel method
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
Xuesong Yin, Songcan Chen, Enliang Hu, Daoqiang Zh...
ICDM
2010
IEEE
198views Data Mining» more  ICDM 2010»
14 years 9 months ago
Hierarchical Ensemble Clustering
Ensemble clustering has emerged as an important elaboration of the classical clustering problems. Ensemble clustering refers to the situation in which a number of different (input)...
Li Zheng, Tao Li, Chris H. Q. Ding
CSDA
2007
142views more  CSDA 2007»
14 years 11 months ago
DIVCLUS-T: A monothetic divisive hierarchical clustering method
DIVCLUS-T is a divisive hierarchical clustering algorithm based on a monothetic bipartitional approach allowing the dendrogram of the hierarchy to be read as a decision tree. It i...
Marie Chavent, Yves Lechevallier, Olivier Briant