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KDD
2009
ACM
207views Data Mining» more  KDD 2009»
16 years 6 months ago
DynaMMo: mining and summarization of coevolving sequences with missing values
Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discover hidden variables and learn ...
Lei Li, James McCann, Nancy S. Pollard, Christos F...
KDD
2007
ACM
184views Data Mining» more  KDD 2007»
16 years 6 months ago
GraphScope: parameter-free mining of large time-evolving graphs
How can we find communities in dynamic networks of social interactions, such as who calls whom, who emails whom, or who sells to whom? How can we spot discontinuity timepoints in ...
Jimeng Sun, Christos Faloutsos, Spiros Papadimitri...
KDD
2006
ACM
142views Data Mining» more  KDD 2006»
16 years 6 months ago
Automatic mining of fruit fly embryo images
We present FEMine, an automatic system for image-based gene expression analysis. We perform experiments on the largest publicly available collection of Drosophila ISH (in situ hyb...
Jia-Yu Pan, André G. R. Balan, Eric P. Xing...
186
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CIKM
2010
Springer
15 years 1 months ago
Mining networks with shared items
Recent advances in data processing have enabled the generation of large and complex graphs. Many researchers have developed techniques to investigate informative structures within...
Jun Sese, Mio Seki, Mutsumi Fukuzaki
SDM
2009
SIAM
111views Data Mining» more  SDM 2009»
16 years 3 months ago
A New Constraint for Mining Sets in Sequences.
Discovering interesting patterns in event sequences is a popular task in the field of data mining. Most existing methods try to do this based on some measure of cohesion to deter...
Bart Goethals, Boris Cule, Céline Robardet