Context Search Based on Inconsistent Ontology Reasoning

In our previous work [1], to improve search quality and user satisfaction by using the user´s context of search we have developed a FOCS Model. In this Model, a context ontology is developed to record user´s relevant context information and to help the semantic expansion of keywords. To make search results more relevant and personalized, similarity flooding algorithm is used to match context ontology with a faceted ontology, an ontology for annotating the target documents. However, similarity flooding algorithm cannot be used to calculate semantic data, so it is not a desirable method to solve the problem of context search well. Hence, we implemented a new Context Search in the model of IORCS. In this model, we integrate an inconsistent ontology reasoning method into our context search model to improve the accuracy of ontology matching step. First, we consider the ontologies we use in context search model as inconsistent ontologies. Second, to filter sub-ontology which the most similar to Search Ontology from related faceted ontologies, context reasoning function (CRF) is introduced to filter these inconsistent ontologies. Finally, context reasoning algorithm is used to implement ontology matching. The experimental results show the integration of inconsistent ontology reasoning into context search model can tackle the issue of Semantic Similarity Calculation better.