AUTHOR=Zhu Jie , Yaseen Ashraf 

TITLE=A Recommender for Research Collaborators Using Graph Neural Networks

JOURNAL=Frontiers in Artificial Intelligence

VOLUME=Volume 5 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2022.881704

DOI=10.3389/frai.2022.881704

ISSN=2624-8212

ABSTRACT=As most great discoveries and advancements in science and technology invariably involve the cooperation of a group of researchers, effective collaboration is key. Nevertheless, finding suitable scholars and researchers to work with is challenging and, mostly, time-consuming for many. A recommender capable of finding and recommending collaborators would prove helpful. In this work, we utilized a life science and biomedical research database, i.e., MEDLINE, to develop a collaboration recommendation system based on novel graph neural networks, i.e. GraphSAGE and Temporal Graph Network, which can capture intrinsic, complex, and changing dependencies among researchers, including temporal user-user interactions. Baseline methods based on LightGCN and gradient boosting trees were also developed in this work for comparison. Internal automatic evaluations, as well as external evaluations through end-users’ ratings were conducted, and results revealed that our graph neural networks recommender exhibits consistently encouraging results.