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SDM
2007
SIAM
176views Data Mining» more  SDM 2007»
15 years 8 months ago
Adaptive Concept Learning through Clustering and Aggregation of Relational Data
We introduce a new approach for Clustering and Aggregating Relational Data (CARD). We assume that data is available in a relational form, where we only have information about the ...
Hichem Frigui, Cheul Hwang
SDM
2011
SIAM
243views Data Mining» more  SDM 2011»
14 years 9 months ago
Data Integration via Constrained Clustering: An Application to Enzyme Clustering
When multiple data sources are available for clustering, an a priori data integration process is usually required. This process may be costly and may not lead to good clusterings,...
Elisa Boari de Lima, Raquel Cardoso de Melo Minard...
ICDM
2003
IEEE
100views Data Mining» more  ICDM 2003»
16 years 1 days ago
Tractable Group Detection on Large Link Data Sets
Discovering underlying structure from co-occurrence data is an important task in a variety of fields, including: insurance, intelligence, criminal investigation, epidemiology, hu...
Jeremy Kubica, Andrew W. Moore, Jeff G. Schneider
ICDM
2007
IEEE
159views Data Mining» more  ICDM 2007»
16 years 1 months ago
Incremental Subspace Clustering over Multiple Data Streams
Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
Qi Zhang, Jinze Liu, Wei Wang 0010
ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
15 years 11 months ago
Estimating the number of segments in time series data using permutation tests
Segmentation is a popular technique for discovering structure in time series data. We address the largely open problem of estimating the number of segments that can be reliably di...
Kari Vasko, Hannu Toivonen