A balanced modularity maximization link prediction model in social networks
作者：
Highlights：
• We present a novel community-based link prediction method called MMLP.
• We use modularity maximization process build a bridge a bridge between link prediction and community detection.
• A trade-off technique is designed to maintain the network in balance.
• A feature aggregation method is proposed to combine information of different level.
• Experiments with synthetic and real-world data are presented.
摘要
•We present a novel community-based link prediction method called MMLP.•We use modularity maximization process build a bridge a bridge between link prediction and community detection.•A trade-off technique is designed to maintain the network in balance.•A feature aggregation method is proposed to combine information of different level.•Experiments with synthetic and real-world data are presented.
论文关键词：Link prediction,Social network,Community detection,Modularity
论文评审过程：Received 24 June 2015, Revised 30 September 2016, Accepted 5 October 2016, Available online 22 October 2016, Version of Record 23 November 2016.
论文官网地址：https://doi.org/10.1016/j.ipm.2016.10.001
