Belief propagation over pairwise connected Markov Random Fields has become a widely used approach, and has been successfully applied to several important computer vision problems....
Mapping ontologies with high precision on the Semantic Web is a challenging problem that needs to be addressed in various domains. One of the main problems with any mapping process...
This paper presents a framework for context-aware applications, with a particular focus on collaboration and pervasiveness. The framework relies on distributed ontologies, which ar...
We describe how a physical robot can learn about objects from its own autonomous experience in the continuous world. The robot identifies statistical regularities that allow it t...
Many algorithms have been developed to harvest lexical semantic resources, however few have linked the mined knowledge into formal knowledge repositories. In this paper, we propos...