Research collaboration model in academic social networks

This paper proposes a hybrid collaboration recommendation method that accounts for research similarities and the previous research cooperation network. Research cooperation is measured by combining the collaboration time and the number of co-authors who already collaborated with at least one scientist. Research similarity is based on authors' previous publications and academic events they attended. A weighted directed graph is built to discover new collaborators by using direct and indirect connections between scientists. Moreover, a consensus-based system is built to integrate bibliography data from different sources. The experimental results show that our method improves the recommendation performances over other methods.