In this article a neural network architecture is presented that is able to build a soft segmentation of a two-dimensional input. This network architecture is applied to position ev...
This paper proposes a method for dealing with numerical attributes in inductive concept learning systems based on genetic algorithms. The method uses constraints for restricting th...
The main purpose of this paper is to compare the support vector machine (SVM) developed by Vapnik with other techniques such as Backpropagation and Radial Basis Function (RBF) Net...
This paper describes ActionStreams, a system for inducing task models from observations of user activity. The model can represent several task structures: hierarchy, variable sequ...
Abstract. The paper argues that a promising way to improve the success rate of preference-based anaphora resolution algorithms is the use of machine learning. The paper outlines MA...