CONDORCKD is a system implementing a novel approach to discovering knowledge from data. It addresses the issue of relevance of the learned rules by algebraic means and explicitly ...
Jens Fisseler, Gabriele Kern-Isberner, Christoph B...
We present an approach to integrating rules and ontologies on the basis of the first-order stable model semantics defined by Ferraris, Lee and Lifschitz. We show that a few exist...
Discovering association rules is one of the important tasks in data mining. While most of the existing algorithms are developed for efficient mining of frequent patterns, it has be...
We have been investigating ways in which the performance of model elimination based systems can be improved and in this paper we present some of our results. Firstly, we have inve...
Abstract. This article underlines the learning and discrimination capabilities of a model of associative memory based on artificial networks of spiking neurons. Inspired from neuro...