Ranking Answers to Datalog+⁄− Ontologies based on Trust and Reliability of Subjective Reports

Abstract

The use of preferences in query answering, both in traditional databases and in ontology-based data access, has recently received much attention due to its many real-world applications. In this paper, we tackle the problem of top-k query answering in Datalog+/– ontologies subject to a user’s preferences and a collection of (subjective) reports provided by other users. Here, each report consists of scores for a list of features, its author’s preferences among the features, as well as other information. These pieces of information of every report are then combined, along with the querying user’s preferences and their trust in each report, to rank the query results. We present two alternative such rankings, along with algorithms for top-k (atomic) query answering under these rankings. We also show that, under suitable assumptions, these algorithms run in polynomial time in the data complexity. We finally present more general reports, which are associated with sets of atoms rather than single atoms.