An Improved Structural-Based Ontology Matching Approach Using Similarity Spreading

Increasing number of ontologies demand the interoperability between them in order to gain accurate information. the ontology heterogeneity also makes the interoperability process even more difficult. These scenarios let the development of effective and efficient ontology matching. The existing ontology matching systems are mainly focusing with subject derivatives of the concern domain. Since ontologies are represented as data model in structured format, In this paper, a new modified model of similarity spreading for ontology mapping is proposed. In this approach the mapping mainly involves with node clustering based on edge affinity and then the graph matching is achieved by applying coefficient similarity propagation. This process is carried out by iterative manner and at the end the similarity score is calculated for iteration. This model is evaluated in terms of precision, recall and f-measure parameters and found that it outperforms well than its similar kind of systems.