Abstract
Experts finding is an important issue for finding potential contributors or expertise in a specific field. In scientific research, researchers often try to find an experts list related to their interest areas to acquire the knowledge about state arts of current research and novices can get benefit to find new ideas for research. In this paper, we proposed an ontological model to find and rank the experts in a particular domain. First, an Academic Knowledge Base(AKB) is built for a particular domain and then an academic social network (ASN) is constructed based on the information provided by the knowledge base for a given topic. In our approach, we proposed a cohesive modeling approach to investigate academic information considering heterogeneous relationship. Our proposed model provides a novel approach to organize and manage the real world academic information in a structural way which can share and reuse by others. Based on this structured academic information an academic social network is built to find the experts for a particular topic. Moreover, the academic social network ranks the experts with a ranking scores depending upon relationships among expert candidates. Finally, we verify the experimental evaluations of our model which improve precision of finding experts compare to baseline methods.
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Uddin, M.N., Duong, T.H., Oh, Kj., Jo, GS. (2011). An Ontology Based Model for Experts Search and Ranking. In: Nguyen, N.T., Kim, CG., Janiak, A. (eds) Intelligent Information and Database Systems. ACIIDS 2011. Lecture Notes in Computer Science(), vol 6592. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20042-7_16
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DOI: https://doi.org/10.1007/978-3-642-20042-7_16
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