Exploring Pattern Mining for Solving the Ontology Matching Problem

This paper deals with the ontology matching problem, and proposes a pattern mining approach that exploits the different correlation and dependencies between the different properties to select the most appropriate features for the matching process. The proposed method first discovers the frequent patterns from the ontology database, and then find out the most relevant features using the patterns derived. To demonstrate the usefulness of the suggested method, several experiments have been carried out on the DBpedia ontology databases. The results show that our proposal outperforms the state-of-the-art ontology matching approaches in terms of both execution time and quality of the matching process.