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» Process Diagnostics: A Method Based on Process Mining
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IFIP12
2008
15 years 8 months ago
Bayesian Networks Optimization Based on Induction Learning Techniques
Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
Paola Britos, Pablo Felgaer, Ramón Garc&iac...
IRI
2003
IEEE
15 years 11 months ago
An Information Model of Virtual Collaboration
Distributed collaboration over the Internet has become increasingly common in recent years, supported by various technologies such as virtual workspace systems. Often such collabo...
Robert P. Biuk-Aghai
CORR
2011
Springer
222views Education» more  CORR 2011»
14 years 10 months ago
A New Data Layout For Set Intersection on GPUs
Abstract—Set intersection is the core in a variety of problems, e.g. frequent itemset mining and sparse boolean matrix multiplication. It is well-known that large speed gains can...
Rasmus Resen Amossen, Rasmus Pagh
ICIP
2003
IEEE
15 years 11 months ago
Parameter estimation for spatial random trees using the EM algorithm
A new class of multiscale multidimensional stochastic processes called spatial random trees was recently introduced in [9]. The model is based on multiscale stochastic trees with ...
Ilya Pollak, Jeffrey Mark Siskind, Mary P. Harper,...
CEC
2007
IEEE
15 years 10 months ago
Mining association rules from databases with continuous attributes using genetic network programming
Most association rule mining algorithms make use of discretization algorithms for handling continuous attributes. Discretization is a process of transforming a continuous attribute...
Karla Taboada, Eloy Gonzales, Kaoru Shimada, Shing...