The KDD process aims at the discovery and extraction of “useful” knowledge (such as interesting patterns, classification, rules etc) from large data repositories. A widely rec...
Classification of users' whereabouts patterns is important for many emerging ubiquitous computing applications. Latent Dirichlet Allocation (LDA) is a powerful mechanism to e...
In [13] we reported the genome sequences of S. paradoxus, S. mikatae and S. bayanus and compared these three yeast species to their close relative, S. cerevisiae. Genome-wide comp...
Manolis Kamvysselis, Nick Patterson, Bruce Birren,...
A sequential pattern in data mining is a finite series of elements such as A → B → C → D where A, B, C, and D are elements of the same domain. The mining of sequential patte...
Pak Chung Wong, Wendy Cowley, Harlan Foote, Elizab...
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...