Combining RDF and SPARQL with CP-theories to reason about preferences in a Linked Data setting

Combining RDF and SPARQL with CP-theories to reason about preferences in a Linked Data setting

Semantic Web Journal - -2018

Authors

Anelli Vito Walter, De Leone Renato, Di Noia Tommaso, Lukasiewicz Thomas, Rosati Jessica

Abstract

Preference representation and reasoning play a central role in supporting users with complex and multi-factorial decision processes. In fact, user tastes can be used to filter information and data in a personalized way, thus maximizing their expected utility. Over the years, many frameworks and languages have been proposed to deal with user preferences. Among them, one of the most prominent formalism to represent and reason with (qualitative) conditional preferences (CPs) are conditional preference theories (CP-theories). In this paper, we show how to combine them with Semantic Web technologies in order to encode in a standard SPARQL 1.1 query the semantics of a set of CP statements representing user preferences by means of RDF triples that refer to a “preference” OWL ontology. In particular, here we focus on context-uniform conditional (cuc) acyclic CP-theories [44]. The framework that we propose allows a standard SPARQL client to query Linked Data datasets, and to order the results of such queries relative to a set of user preferences.

Download: Combining RDF and SPARQL with CP-theories to reason about preferences in a Linked Data setting.pdf

DOI

https://doi.org/10.3233/sw-180339

BibTex references

@Article{ADDLR18,
  author       = "Anelli, Vito Walter and De Leone, Renato and Di Noia, Tommaso and Lukasiewicz, Thomas and Rosati, Jessica",
  title        = "Combining RDF and SPARQL with CP-theories to reason about preferences in a Linked Data setting",
  journal      = "Semantic Web Journal",
  year         = "2018",
  note         = "in press",
  url          = "http://sisinflab.poliba.it/Publications/2018/ADDLR18"

}