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 ...
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...
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...
Network Data Mining identifies emergent networks between myriads of individual data items and utilises special algorithms that aid visualisation of `emergent' patterns and tre...
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...