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ICDM
2009
IEEE
133views Data Mining» more  ICDM 2009»
15 years 8 months ago
On K-Means Cluster Preservation Using Quantization Schemes
This work examines under what conditions compression methodologies can retain the outcome of clustering operations. We focus on the popular k-Means clustering algorithm and we dem...
Deepak S. Turaga, Michail Vlachos, Olivier Versche...
ICDM
2007
IEEE
137views Data Mining» more  ICDM 2007»
15 years 8 months ago
Locally Constrained Support Vector Clustering
Support vector clustering transforms the data into a high dimensional feature space, where a decision function is computed. In the original space, the function outlines the bounda...
Dragomir Yankov, Eamonn J. Keogh, Kin Fai Kan
KDD
1998
ACM
123views Data Mining» more  KDD 1998»
15 years 6 months ago
Scaling Clustering Algorithms to Large Databases
Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
Paul S. Bradley, Usama M. Fayyad, Cory Reina
PAKDD
2007
ACM
184views Data Mining» more  PAKDD 2007»
15 years 7 months ago
Exploring Group Moving Pattern for an Energy-Constrained Object Tracking Sensor Network
In this paper, we investigate and utilize the characteristic of the group movement of objects to achieve energy conservation in the inherently resource-constrained wireless object ...
Hsiao-Ping Tsai, De-Nian Yang, Wen-Chih Peng, Ming...
ICDM
2010
IEEE
217views Data Mining» more  ICDM 2010»
14 years 11 months ago
Discovering Temporal Features and Relations of Activity Patterns
An important problem that arises during the data mining process in many new emerging application domains is mining data with temporal dependencies. One such application domain is a...
Ehsan Nazerfard, Parisa Rashidi, Diane J. Cook