Representing and reasoning about preferences is a key issue in many real-world scenarios in which personalized access to information is required. Many approaches have been proposed and studied in the literature that allow a system to work with qualitative or quantitative preferences; among the qualitative models, one of the most prominent are CP-nets. Their clear graphical structure unifies an easy representation of user preferences with good computational properties when computing the best outcome. In this paper, we show how to reason with CP-nets when the attributes modeling the knowledge domain are structured via an underlying domain ontology. We show how the computation of all undominated feasible outcomes of an ontological CP-net can be reduced to the solution of a constraint satisfaction problem, and study the computational complexity of the basic reasoning problems in ontological CP-nets.
|Titolo del libro:||Uncertainty Reasoning for the Semantic Web III : ISWC International Workshops, URSW 2011-2013. Revised Selected Papers|
|Data di pubblicazione:||2014|
|Digital Object Identifier (DOI):||10.1007/978-3-319-13413-0_15|
|Appare nelle tipologie:||2.1 Contributo in volume (Capitolo o Saggio)|