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» Approximate data mining in very large relational data
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EDBT
2004
ACM
142views Database» more  EDBT 2004»
16 years 4 months ago
Iterative Incremental Clustering of Time Series
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dim...
ESA
2004
Springer
105views Algorithms» more  ESA 2004»
15 years 9 months ago
Time Dependent Multi Scheduling of Multicast
Many network applications that need to distribute content and data to a large number of clients use a hybrid scheme in which one (or more) multicast channel is used in parallel to...
Rami Cohen, Dror Rawitz, Danny Raz
ADMA
2009
Springer
212views Data Mining» more  ADMA 2009»
15 years 11 months ago
Automating Gene Expression Annotation for Mouse Embryo
It is of high biomedical interest to identify gene interactions and networks that are associated with developmental and physiological functions in the mouse embryo. There are now v...
Liangxiu Han, Jano I. van Hemert, Richard A. Baldo...
SDM
2009
SIAM
185views Data Mining» more  SDM 2009»
16 years 1 months ago
Understanding Importance of Collaborations in Co-authorship Networks: A Supportiveness Analysis Approach.
Co-authorship networks, an important type of social networks, have been studied extensively from various angles such as degree distribution analysis, social community extraction a...
Bin Zhou 0002, Jian Pei, Yan Jia, Yi Han
PODS
1999
ACM
121views Database» more  PODS 1999»
15 years 8 months ago
Tracking Join and Self-Join Sizes in Limited Storage
Query optimizers rely on fast, high-quality estimates of result sizes in order to select between various join plans. Selfjoin sizes of relations provide bounds on the join size of...
Noga Alon, Phillip B. Gibbons, Yossi Matias, Mario...