iweightings: Enhancing Structure-based Ontology Alignment by Enriching Models with Importance Weighting

Abstract

Structural ontology matching methods analyze mainly two factors: entity labels and relationships among entities. We propose to additionally consider an importance and relevance factor, which is determined by two indicators automatically calculated by a (simple) weighting method. This weighting factor represents the importance of a concept based on its information significance in the modeling context and, additionally, its relevance for structure-based alignment depending on the number of relationships this concept participates in quantified by the rweighting indicator. The method starts via a manually weighting annotation of relationships among concepts conducted by ontology engineers during the ontology development process. Our approach is an assistance mechanism to improve the ontology alignment process and to enhance the cognitive support for users. Thus, ontology alignment becomes already important ex ante when the ontology development process starts, unlike other alignment techniques, which consider only ex post knowledge.