Preferences‚ Links‚ and Probabilities for Ranking Objects in Ontologies
Thomas Lukasiewicz and Jörg Schellhase
In previous work, we have introduced variable-strength conditional preferences for ranking objects in ontologies. In this paper, we continue this line of research. We propose a new ranking of objects, which integrates this user-defined preference ranking of objects with Google's importance ranking (called PageRank) based on the link structure between the objects. We also propose to use probabilistic description logics based on Bayesian networks and the description logic DL-Lite to compute the ranking of incompletely specified objects.