A Novel Approach for Ontology Focused Inter- Domain Personalized Search based on Semantic Set Expansion

The Web is overloaded with information and its exploration and retrieval is quite tedious is a cumbersome task. In the era of Semantic Web, there is a requisite of Semantic strategies for recommending webpages. In this paper, a strategic semantic paradigm for Ontology Driven Semantic search has been proposed. The proposed scheme incorporates a set expansion mechanism for interdomain exploratory semantic search. The proposed scheme for searching semantically computes concept similarity between concepts from most similar domains, and the set expansion is based on these concepts. The ontologies are visualized using a triple store and personalization has been imbibed into the proposed scheme. The initial step requires determination of the domains and scope of the ontologies, followed by identification of classes, defining instances of each class and the relationship among them. Multiple user profiles will be created to personalize the search results according to the search history of each user. Through this model, the problem of irrelevant search results is reduced, and in the process, reduces the probability of going through numerous results as in case of a normal search engine. Also, the search engine is made scalable to any dataset irrespective of its content. An overall F-measure of 96.64% has been achieved.