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ICDE
2009
IEEE
202views Database» more  ICDE 2009»
14 years 9 months ago
Tracking High Quality Clusters over Uncertain Data Streams
Recently, data mining over uncertain data streams has attracted a lot of attentions because of the widely existed imprecise data generated from a variety of streaming applications....
Chen Zhang, Ming Gao, Aoying Zhou
ICDM
2003
IEEE
92views Data Mining» more  ICDM 2003»
14 years 29 days ago
Validating and Refining Clusters via Visual Rendering
Clustering is an important technique for understanding and analysis of large multi-dimensional datasets in many scientific applications. Most of clustering research to date has be...
Keke Chen, Ling Liu
ICDE
1997
IEEE
130views Database» more  ICDE 1997»
14 years 9 months ago
High-Dimensional Similarity Joins
Many emerging data mining applications require a similarity join between points in a high-dimensional domain. We present a new algorithm that utilizes a new index structure, calle...
Kyuseok Shim, Ramakrishnan Srikant, Rakesh Agrawal
SDM
2004
SIAM
225views Data Mining» more  SDM 2004»
13 years 9 months ago
Active Semi-Supervision for Pairwise Constrained Clustering
Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
Sugato Basu, Arindam Banerjee, Raymond J. Mooney
ICDE
2003
IEEE
146views Database» more  ICDE 2003»
14 years 9 months ago
Similarity Search in Sets and Categorical Data Using the Signature Tree
Data mining applications analyze large collections of set data and high dimensional categorical data. Search on these data types is not restricted to the classic problems of minin...
Nikos Mamoulis, David W. Cheung, Wang Lian