Authors: Iraklis Varlamis; George Tsatsaronis
Addresses: Department of Informatics and Telematics, Harokopio University of Athens, 89, Harokopou St., Athens 17671, Greece. ' Bioinformatics Group, Biotechnology Center (BIOTEC), Technical University of Dresden, Tatzberg 47/49, Dresden 01307, Germany
Abstract: Bibliographic databases are a prosperous field for data mining research and social network analysis. They contain rich information, which can be analysed across different dimensions (e.g., author, year, venue, and topic) and can be exploited in multiple ways. The representation and visualisation of bibliographic databases as graphs and the application of data mining techniques can help us uncover interesting knowledge concerning potential synergies between researchers, possible matchings between researchers and venues, candidate reviewers for a paper or even the ideal venue for presenting a research work. In this paper, we propose a novel representation model for bibliographic data, which combines co-authorship and content similarity information, and allows for the formation of scientific networks. Using a graph visualisation tool from the biological domain, we are able to provide comprehensive visualisations that help us uncover hidden relations between authors and suggest potential synergies between researchers or groups.
Keywords: bibliographic databases; co-authorship graphs; graph analysis; similarity metrics; graph mining; graph-based recommendations; research synergies; data mining; content similarity; scientific networks; graph visualisation; authors; researchers; research groups.
International Journal of Web Engineering and Technology, 2012 Vol.7 No.3, pp.250 - 272
Published online: 16 Aug 2014 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article