Improving Semantic Matching of Grid Resources Using Refined Ontology with Complement Class

Amidst the proliferation of different resources available on the Grid, today, it is vital to optimally discover the appropriate resource from amongst a repository of the resources distributed across Grid. Conventionally, the syntactic homogeneity of the resource description in each repository is used for match making and for identification of the required resource. Of late, detecting the semantic homogeneity of the resource description is also coupled with syntactic matching for the purpose. However, detecting semantic homogeneity requires complete description of the associated resource. We propose here an approach that is based on employing complement classes to early reject those resources that lack the semantic matching, thereby yielding efficient discovery of the required resource. To the best of our knowledge, ours is the first attempt at proposing Complement Class based semantic match making algorithm for detection of the resources.