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JMLR
2010
134views more  JMLR 2010»
13 years 3 months ago
Bayesian Algorithms for Causal Data Mining
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...
ALMOB
2006
102views more  ALMOB 2006»
13 years 9 months ago
Mining, compressing and classifying with extensible motifs
Background: Motif patterns of maximal saturation emerged originally in contexts of pattern discovery in biomolecular sequences and have recently proven a valuable notion also in t...
Alberto Apostolico, Matteo Comin, Laxmi Parida
WEBI
2004
Springer
14 years 2 months ago
An Integrated Approach to Discovery in Complex Information Spaces
As the amount of available data continues to increase, more and more effective means for discovering important patterns and relationships within that data are required. Although t...
Daryl H. Hepting, Cory J. Butz
APCCM
2006
13 years 10 months ago
Network data mining: methods and techniques for discovering deep linkage between attributes
Network Data Mining identifies emergent networks between myriads of individual data items and utilises special algorithms that aid visualisation of `emergent' patterns and tre...
John Galloway, Simeon J. Simoff
HIPC
2003
Springer
14 years 2 months ago
Parallel and Distributed Frequent Itemset Mining on Dynamic Datasets
Traditional methods for data mining typically make the assumption that data is centralized and static. This assumption is no longer tenable. Such methods waste computational and I/...
Adriano Veloso, Matthew Eric Otey, Srinivasan Part...