社交网络中多渠道影响最大化方法

被引:5
作者
李小康
张茜
孙昊
孙广中
机构
[1] 安徽省高性能计算重点实验室(中国科学技术大学计算机学院)
[2] 国防科学技术大学高性能计算协同创新中心
关键词
社交网络; 影响最大化; 多渠道; NP难; 近似方法;
D O I
暂无
中图分类号
O157.5 [图论];
学科分类号
070104 ;
摘要
社交网络因为其流行性,近些年得到学术界的广泛关注,社交网络影响最大化是社交网络领域中最流行的问题之一.经典的影响最大化问题是从网络中选取k个初始用户,作为种子用户,让其在网络中传播影响,使得最终受影响的用户数最大化.以往的绝大部分工作针对于单个网络的传播,真实情况下信息是借助多个网络传播的.考虑到信息在多个网络中的传播,提出社交网络中多渠道影响最大化问题,从多个网络中选取k个种子用户,让其同时在多个网络中传播影响,使最终受种子用户影响的用户量最大化.将该问题规约为社交网络影响最大化问题,证明其在独立级联模型下是NP难的.根据问题的特性,提出3种有效的近似解决方法,并在4个真实的社交网络数据中进行实验.实验表明3种的方法能够有效地解决多渠道下的影响力最大化问题.
引用
收藏
页码:1709 / 1718
页数:10
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