Abstract
Modern bibliographic databases contain significant amount of information on publication activities of research communities. Researchers regularly encounter challenging task of selecting a co-author for joint research publication or searching for authors, whose papers are worth reading. We propose a new recommender system for finding possible collaborator with respect to research interests. The recommendation problem is formulated as a link prediction within the co-authorship network. The network is derived from the bibliographic database and enriched by the information on research papers obtained from Scopus and other publication ranking systems.
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Acknowledgements
I. Makarov was supported within the framework of the Basic Research Program at National Research University Higher School of Economics and within the framework of a subsidy by the Russian Academic Excellence Project ‘5-100’
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Makarov, I., Bulanov, O., Zhukov, L.E. (2017). Co-author Recommender System. In: Kalyagin, V., Nikolaev, A., Pardalos, P., Prokopyev, O. (eds) Models, Algorithms, and Technologies for Network Analysis. NET 2016. Springer Proceedings in Mathematics & Statistics, vol 197. Springer, Cham. https://doi.org/10.1007/978-3-319-56829-4_18
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DOI: https://doi.org/10.1007/978-3-319-56829-4_18
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