Ontological query answering under many-valued group preferences in Datalog+/–

https://doi.org/10.1016/j.ijar.2017.11.008Get rights and content
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Highlights

  • Top-k QA with quant. preferences in Datalog+/– for unions of CQs with safe negation.

  • Generalize the RankJoin algorithm allowing computation of answers in poly. time.

  • Generalize the framework for computing answer to queries for groups of users.

  • Empirical results on performance and quality of our algorithms on real-world data.

Abstract

The Web has recently been changing more and more to what is called the Social Semantic Web. As a consequence, the ranking of search results no longer depends solely on the structure of the interconnections among Web pages. In this paper, we argue that such rankings can be based on user preferences from the Social Web and on ontological background knowledge from the Semantic Web. We propose an approach to top-k query answering under user preferences in Datalog+/– ontologies, where the queries are unions of conjunctive queries with safe negation, and the preferences are defined via numerical values. To this end, we also generalize the previous RankJoin algorithm to our framework. Furthermore, we explore the generalization to the preferences of a group of users. Finally, we provide experimental results on the performance and quality of our algorithms.

Keywords

Top-k query answering
Preferences
Social choice
Ontological query answering
Datalog+/–
Existential rules

Cited by (0)

This paper is part of the Virtual special issue on Uncertainty Reasoning for the Web, Edited by Fernando Bobillo, Kenneth J. Laskey, Trevor Martin, Matthias Nickles.