We address the problem of nding useful regions for two-dimensional association rules and decision trees. In a previous paper we presented ecient algorithms for computing optimiz...
Current knowledge bases suffer from either low coverage or low accuracy. The underlying hypothesis of this work is that user feedback can greatly improve the quality of automatica...
Gjergji Kasneci, Jurgen Van Gael, Ralf Herbrich, T...
Abstract. In this paper we present a novel and general framework based on concepts of relational algebra for kernel-based learning over relational schema. We exploit the notion of ...
Adam Woznica, Alexandros Kalousis, Melanie Hilario
A problem of association rules discovery in a multivariate time series is considered in this paper. A method for finding interpretable association rules between frequent qualitati...
Abstract. Gaussian processes have successfully been used to learn preferences among entities as they provide nonparametric Bayesian approaches for model selection and probabilistic...