A Hybrid Layered Approach for Ontology Matching

Abstract

Ontologies act as a key technology for the visualization of the semantic web and their existence in different domains produces a heterogeneity problem for information integration. The process of ontology matching solves the heterogeneity problem by identifying the semantically related identical entities available from different ontologies. Finding similarity between the class names across the input ontologies is the major step performed in every ontology matching process. Most of the existing methods compare the class names only based on their similarity irrespective of their real meaning. This paper suggests a hybrid layered approach for matching the ontology classes. This approach calculates syntactic, semantic and structural similarity between the classes from input ontologies in successive layers. Finally, the alignment layer generates the final matching results by combining the results obtained from the previous layers and generates semantic mappings between them. This approach can also be applied to match other entities of the ontology. The results obtained prove that the proposed approach overtakes the other existing methods, thereby improving the accuracy of the results achieved.