计算机应用研究2016，Vol.33Issue(12)：3611-3614,4.DOI:10.3969/j.issn.1001-3695.2016.12.021
社会网络中基于主题的影响力最大化算法
Topic-based influence maximization algorithm on social networks
摘要
Abstract
To solve the problem that recent researches of influence maximization haven’t fully considered that topic has an im-pact on influential nodes mining,which lead to low influence scope under specific topic,this paper proposed a topic-based in-fluence maximization algorithm (TIM).This algorithm first pretreated the initial node set according to topic sensitive thresh-old,and removed the interference nodes,then mined nodes in two stages on the new node set.In the first stage,it mined the nodes with high topic authority;in the second stage,it mined the nodes with the biggest topic influence increment.At last,it combined the two stages of the node as a result set and made an experimental verification.The experimental results indicate that the nodes set mined by the proposed algorithm improve the influence scope under specific topic and the algorithm cost less time compare to other influence maximization algorithms.关键词
社会网络/影响力最大化/主题/节点挖掘/节点集Key words
social network/influence maximization/topic/nodes mining/node set分类
信息技术与安全科学引用本文复制引用
朱玉婷,李雷,施化吉,周从华,施磊磊,徐慧..社会网络中基于主题的影响力最大化算法[J].计算机应用研究,2016,33(12):3611-3614,4.基金项目
国家自然科学基金资助项目（71271117）；江苏省科技支撑计划资助项目 （）
