Esoogle: A Semantic-based Expert Information Service System

The existing expert information systems supply services for searching information of experts and help the users to select suitable experts to evaluate all types of projects in different fields, however, almost all of these search services use keyword match, and it is hard to gain high search efficiency. Ontology has been proved to be very useful in sharing concepts across applications in an unambiguous way and used to support information exchange based on semantics. In this paper, we design software architecture for Semantic-based expert information service system (Esoogle) to provide semantic-base information service. Expert information ontology is defined to store the information of experts, and reasoning rules are defined for semantic-based reasoning. Applications show Esoogle improves the recall and precision of searching services compared to the existing systems.