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KDD
2007
ACM
182views Data Mining» more  KDD 2007»
14 years 8 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
KDD
2005
ACM
140views Data Mining» more  KDD 2005»
14 years 8 months ago
Graphs over time: densification laws, shrinking diameters and possible explanations
How do real graphs evolve over time? What are "normal" growth patterns in social, technological, and information networks? Many studies have discovered patterns in stati...
Jure Leskovec, Jon M. Kleinberg, Christos Faloutso...
KDD
2005
ACM
127views Data Mining» more  KDD 2005»
14 years 8 months ago
Detection of emerging space-time clusters
We propose a new class of spatio-temporal cluster detection methods designed for the rapid detection of emerging space-time clusters. We focus on the motivating application of pro...
Daniel B. Neill, Andrew W. Moore, Maheshkumar Sabh...
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
14 years 8 months ago
Efficient closed pattern mining in the presence of tough block constraints
In recent years, various constrained frequent pattern mining problem formulations and associated algorithms have been developed that enable the user to specify various itemsetbase...
Krishna Gade, Jianyong Wang, George Karypis
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 8 months ago
Visually mining and monitoring massive time series
Moments before the launch of every space vehicle, engineering discipline specialists must make a critical go/no-go decision. The cost of a false positive, allowing a launch in spi...
Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Jef...