Co-authorship prediction in academic social network - Maruyama, William Takahiro; Digiampietri, Luciano Antonio (Anais do Brazilian Workshop on Social Network Analysis and Mining (BraSNAM), 2016)
The prediction of relationships in a social network is a complex and extremely useful task to enhance or maximize collaborations by indicating the most promising partnerships. In academic social networks, prediction of relationships is typically used to try to identify potential partners in the development of a project and/or co-authors for publishing papers. This paper presents an approach to predict coauthorships combining artificial intelligence techniques with the state-of-the-art metrics for link predicting in social networks.