Mining potential research synergies from co-authorship graphs using power graph analysis Online publication date: Sat, 16-Aug-2014
by Iraklis Varlamis; George Tsatsaronis
International Journal of Web Engineering and Technology (IJWET), Vol. 7, No. 3, 2012
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Web Engineering and Technology (IJWET):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook