This project is funded by the European Union under Horizon2020 Research and Innovation Programme Grant Agreement n°824091
European Union

RESEARCH SEMINAR Link prediction in knowledge networks using exogenous and endogenous attributes: a machine learning approach

Presenter: Antonio Zinilli and Giovanni Cerulli, CNR-IRCRES   Discussant: Mike Thelwall, University of Wolverhampton   Abstract We propose a supervised machine learning approach to predict partnership formation between universities. We focus on successful joint R&D projects funded by Horizon 2020 programme in three research domains: Social Sciences and Humanities, Physical and Engineering Sciences, and Life Sciences. We perform two connected analyses: link formation prediction, and feature importance detection. As for link prediction, using out-of-sample cross-validated accuracy…

Read more