ACRec

摘要: Recent academic procedures have depicted that work involving scientific research tends to be more prolific through collaboration and cooperation among researchers groups. On the other hand, discovering new collaborators who are smart enough conduct joint-research is accompanied with both difficulties opportunities. One notable difficulty as well opportunity big scholarly data. In this paper, we satisfy demand of recommendation co-authorship in an network. We propose a random walk model using three metrics basics for recommending collaborations. Each metric studied mutual paper co-authoring information serves compute link importance such walker likely visit valuable nodes. Our experiments on DBLP dataset show our approach can improve precision, recall rate coverage recommendation, compared state-of-the-art approaches.