In this paper we introduce several new improvements to the bottom-up model generation (BUMG) paradigm. Our techniques are based on non-trivial transformations of first-order probl...
Enabling machines to understand emotions and feelings of the human users in their natural language textual input during interaction is a challenging issue in Human Computing. Our w...
Li Zhang, Marco Gillies, John A. Barnden, Robert J...
In this paper we present a new approach for the automated mapping of formal descriptions into activity thread implementations. Our approach resolves semantic conflicts by reorderi...
In this work a framework for constructing object detection classifiers using weakly annotated social data is proposed. Social information is combined with computer vision techniq...
It is not unusual for a software development organization to expend 40 percent of total project effort on testing, which can be a very laborious and time-consuming process. Thus, ...