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KDD
2007
ACM
220views Data Mining» more  KDD 2007»
14 years 8 months ago
SCAN: a structural clustering algorithm for networks
Network clustering (or graph partitioning) is an important task for the discovery of underlying structures in networks. Many algorithms find clusters by maximizing the number of i...
Xiaowei Xu, Nurcan Yuruk, Zhidan Feng, Thomas A. J...
ISMIS
2009
Springer
14 years 2 months ago
Novelty Detection from Evolving Complex Data Streams with Time Windows
Abstract. Novelty detection in data stream mining denotes the identification of new or unknown situations in a stream of data elements flowing continuously in at rapid rate. This...
Michelangelo Ceci, Annalisa Appice, Corrado Loglis...
KDD
2007
ACM
168views Data Mining» more  KDD 2007»
14 years 8 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
MIDDLEWARE
2007
Springer
14 years 1 months ago
Using checkpointing to recover from poor multi-site parallel job scheduling decisions
Recent research in multi-site parallel job scheduling leverages user-provided estimates of job communication characteristics to effectively partition the job across multiple clus...
William M. Jones
SDM
2009
SIAM
220views Data Mining» more  SDM 2009»
14 years 4 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