Distance-Based Approaches to Repair Semantics in Ontology-based Data Access

TL;DR

This paper introduces a framework that uses syntactic distance between repairs to cluster similar repairs, enabling more personalized query answering in ontology-based data access despite inconsistencies.

Contribution

It proposes a novel generic framework leveraging repair clustering based on syntactic distance to improve query answering in inconsistent ontologies.

Findings

Clustering repairs based on syntactic distance enhances query personalization.

The framework effectively manages large sets of repairs in inconsistent data.

It offers a new perspective on handling inconsistencies in ontology-based data access.

Abstract

In the presence of inconsistencies, repair techniques thrive to restore consistency by reasoning with several repairs. However, since the number of repairs can be large, standard inconsistent tolerant semantics usually yield few answers. In this paper, we use the notion of syntactic distance between repairs following the intuition that it can allow us to cluster some repairs "close" to each other. In this way, we propose a generic framework to answer queries in a more personalise fashion.