Complexity Analysis of Ontology Integration Methodologies: a Comparative Study

Abstract

Most previous research on ontology integration has focused on similarity measurements between ontological entities, e.g., lexicons, instances, schemas and taxonomies, resulting in high computational costs of considering all possible pairs between two given ontologies. In this paper, we propose a novel approach to reducing computational complexity in ontology integration. Thereby, we address the importance and types of concepts, for priority matching and direct matching between concepts, respectively. Identity-based similarity is computed, to avoid comparisons of all properties related to each concept, while matching between concepts. The problem of conflict in ontology integration has initially been explored on the instance-level and concept-level. This is useful to avoid many cases of mismatching.