LOMPT: An efficient and Scalable Ontology Matching Algorithm

Abstract

Ontology matching is an effective way to handle semantic heterogeneity among the ontologies. An ontology matching system with good efficiency and scalability is a challenge because of the monolithic nature and size of real world domain ontologies. In this paper, an efficient and scalable ontology matching algorithm called LOMPT (Large Ontology Matching using Partitioning Technique) is proposed. LOMPT consist of structure-based bottom up partitioning algorithm which decomposes the large ontology into a set of small partitions. Then the partition pairs across the ontologies are discovered based on the anchor distribution, where anchor is indentified by the proposed light weight string matcher SI-SUB. Finally the linguistic matcher V-DOC and structural matcher GMO process the partition pairs to find match results from the partition pairs. The example and experimental results depicts the efficiency and scalability of the proposed LOMPT system.