Multidimensional ontology-based visual ranking

Abstract

Evangelia Triperina obtained her PhD in Computer Sciences from the University of Limoges, France in 2020. Her thesis focuses on the interdisciplinary research in multidimensional decisions support in the ranking problematic aided by visual analytics and semantic web technologies. Interactive visual analytics exploit the increased visual perceptual abilities of the decision makers creating a more efficient decision support procedure, while semantic web technologies, and more specifically ontologies, structure data, make the system dynamic and add several needed capabilities to the decision support system. Furthermore, the multidimensional decision support method relies not only on evaluating an alternative based on multiple criteria, but also on important dimensions of the domain 1 .