Ontology mapping-based search with multidimensional similarity and Bayesian network

Users in enterprise information systems want to efficiently search the information that they need. Although several searching approaches have been proposed so far, they still have the limitation in finding the semantically similar information that users need. To overcome the limitation, it is essential to consider the semantics of user keyword and terms (concepts) stored in the ontology repository and continuously update the ontology repository for information searching. To this end, in this study, an ontology mapping-based search methodology (OntSE) is proposed. The OntSE consists of three phases: ontology building, ontology mapping, and ontology updating. Its objective is to find the terms which have the same semantics with user's keywords, based on multidimensional similarity and Bayesian network. To show the benefits of the proposed methodology, a case study has been carried out.