Abstract
Collaboration within the international scientific community has steadily increased over the years especially in the presence of complex interdisciplinary problems being investigated. At the same time the amount of research artifacts produced by the research community has grown exponentially making it difficult for individual researchers to filter and search through such information. In the presence of a vast amount of research information the problem of identifying potential project partners or collaborators with specific profiles can become extremely difficult. This paper presents a semantic multi-agent architecture (called SemoRA) aimed at tackling such a problem. The architecture combines agent and Semantic Web technologies in order to develop a framework capable of efficiently acquiring researcher information, making sense of it and giving meaning to it. The architecture ultimately enables the retrieval and matching of scored profiles aimed at enhancing collaborations among researchers – collaborations that can transcend both institutional and national boundaries.
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Adnan, S., Tahir, A., Basharat, A., de Cesare, S. (2010). An Agent-Oriented Architecture for Researcher Profiling and Association Using Semantic Web Technologies. In: Soro, A., Vargiu, E., Armano, G., Paddeu, G. (eds) Information Retrieval and Mining in Distributed Environments. Studies in Computational Intelligence, vol 324. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16089-9_5
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DOI: https://doi.org/10.1007/978-3-642-16089-9_5
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