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» A Framework for Multi-Objective Clustering and Its Applicati...
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KDD
2007
ACM
168views Data Mining» more  KDD 2007»
14 years 4 months ago
A probabilistic framework for relational clustering
Relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu
SDM
2009
SIAM
220views Data Mining» more  SDM 2009»
14 years 1 months ago
Bayesian Cluster Ensembles.
Cluster ensembles provide a framework for combining multiple base clusterings of a dataset to generate a stable and robust consensus clustering. There are important variants of th...
Hongjun Wang, Hanhuai Shan, Arindam Banerjee
PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
14 years 1 months ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
SDM
2007
SIAM
122views Data Mining» more  SDM 2007»
13 years 5 months ago
Incremental Spectral Clustering With Application to Monitoring of Evolving Blog Communities
In recent years, spectral clustering method has gained attentions because of its superior performance compared to other traditional clustering algorithms such as K-means algorithm...
Huazhong Ning, Wei Xu, Yun Chi, Yihong Gong, Thoma...
TKDE
2012
270views Formal Methods» more  TKDE 2012»
11 years 6 months ago
Low-Rank Kernel Matrix Factorization for Large-Scale Evolutionary Clustering
—Traditional clustering techniques are inapplicable to problems where the relationships between data points evolve over time. Not only is it important for the clustering algorith...
Lijun Wang, Manjeet Rege, Ming Dong, Yongsheng Din...