Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
Abstract. Dealing with heterogeneous ontologies by means of semantic mappings has become an important area of research and a number of systems for discovering mappings between onto...
We propose a multi-sensor affect recognition system and evaluate it on the challenging task of classifying interest (or disinterest) in children trying to solve an educational pu...
Predicting items a user would like on the basis of other users' ratings for these items has become a well-established strategy adopted by many recommendation services on the ...
The great majority of genetic programming (GP) algorithms that deal with the classification problem follow a supervised approach, i.e., they consider that all fitness cases availab...
Junio de Freitas, Gisele L. Pappa, Altigran Soares...