Like many purely data-driven machine learning methods, Support Vector Machine (SVM) classifiers are learned exclusively from the evidence presented in the training dataset; thus ...
This paper describes a novel data mining approach that employs evolutionary programming to discover knowledge represented in Bayesian networks. There are two different approaches ...
Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...
This paper explores unexpected results that lie at the intersection of two common themes in the KDD community: large datasets and the goal of building compact models. Experiments ...
In an open innovation environment, organizational learning takes place by means of dispersed teams which expand their knowledge through collaborative idea generation. Research is o...
Rory L. L. Sie, Marlies Bitter-Rijpkema, Peter B. ...