Ontological CP-Nets
Authors
Di Noia Tommaso, Lukasiewicz Thomas, Martinez Maria Vanina, Simari Gerardo Ignacio, Tifrea−Marciuska OanaAbstract
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.
DOI
https://doi.org/10.1007/978-3-319-13413-0_15BibTex references
@InProceedings{DLMST14,
author = "Di Noia, Tommaso and Lukasiewicz, Thomas and Martinez, Maria Vanina and Simari , Gerardo Ignacio and Tifrea\−Marciuska, Oana",
title = "Ontological CP-Nets",
booktitle = "Uncertainty Reasoning for the Semantic Web III",
series = "Lecture Notes in Artificial Intelligence",
year = "2014",
publisher = "Springer",
url = "http://sisinflab.poliba.it/Publications/2014/DLMST14"
}