Community detection and influential node identification in complex networks using mathematical programming
作者：
Highlights：
• Studied the structure of complex relational networks.
• Proposed mathematical model for finding community structures and influential nodes.
• Evaluated proposed model by testing it on various real-life network datasets.
• Results indicate promising performance compared to existing approaches.
• Provides faster coverage and better call for response when applied to networks.
摘要
•Studied the structure of complex relational networks.•Proposed mathematical model for finding community structures and influential nodes.•Evaluated proposed model by testing it on various real-life network datasets.•Results indicate promising performance compared to existing approaches.•Provides faster coverage and better call for response when applied to networks.
论文关键词：Clustering,Networks,Community detection,Influential nodes,Integer linear programming
论文评审过程：Received 6 January 2019, Revised 8 May 2019, Accepted 31 May 2019, Available online 1 June 2019, Version of Record 15 June 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.05.059
