Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
This paper describes the motivations, methods, and solution concepts for the use of ontologies for simulation model integration. Ontological analysis has been shown to be an effec...
With this work we aim to make a three-fold contribution. We first address the issue of supporting efficiently queries over string-attributes involving prefix, suffix, containmen...
Data mining is frequently obstructed by privacy concerns. In many cases data is distributed, and bringing the data together in one place for analysis is not possible due to privac...
This paper aims at pushing the clear relationship between software service composition and chemical dynamics a step forward. We developed a coordination model where services and c...