A Novel Approach to Discover Ontology Alignment

Background: The rise of knowledge-rich applications has made ontologies as a common reference point to link the legacy IT systems. The interoperability and integration of two disparate systems in the same domain demand for the resolution of the heterogeneity problem. The major source of heterogeneity lies in the classical representation scheme of ontologies. Objective: Our objective is to present a novel approach to discover ontology alignment by exploiting the comprehensive knowledge structure, where every entity is represented and stored as a knowledge unit. Methods: We have created the dataset ourselves by using protégé tool because no dataset is available based on the idea of comprehensive knowledge structure. Results: The proposed approach always detects correct alignments and achieves optimal or near to optimal performance (in term of precision) in case of equivalence relationship. Conclusion: The aim of this paper is not to make a full-fledged matching/alignment tool, but to emphasize the importance of distinctive features of an entity while performing entity matching. The matchers are therefore used as black boxes and may be filled based on user’s choice.