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清华大学学报(自然科学版)  2017, Vol. 57 Issue (12): 1245-1253    DOI: 10.16511/j.cnki.qhdxxb.2017.25.061
  计算机科学与技术 本期目录 | 过刊浏览 | 高级检索 |
在线社会网络中面向节点影响力的信息传播阻断模型
赵宇1,2, 黄开枝1,2, 郭云飞1, 赵星1,2
1. 国家数字交换系统工程技术研究中心, 郑州 450002;
2. 移动互联网安全技术国家工程实验室, 北京 100876
Information diffusion blocking model of node influence-oriented in online social network
ZHAO Yu1,2, HUANG Kaizhi1,2, GUO Yunfei1, ZHAO Xing1,2
1. National Digital Switching System Engineering and Technological R & D Center, Zhengzhou 450002, China;
2. National Engineering Laboratory for Mobile Network Security, Beijing 100876, China
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摘要 目前信息传播阻断模型是在网络中选择并删除l个最佳节点(边)使信息传播到的节点数量最小,该模型未考虑信息传播节点的影响力,导致选择的l个最佳节点(边)并不准确,阻断有效性较差。针对此问题,该文提出一种面向节点影响力的信息传播阻断模型,并设计了一种基于采样平均近似的求解方法。模型以网络中节点的影响力为有效性依据,通过选择并删除l个最佳节点来改变网络结构,使信息传播到的目标节点影响力之和最小;该模型为随机优化问题,首先利用采样平均近似将目标函数转化为确定性问题,其次进一步编码为混合整数规划问题,最后采用一种量子遗传算法解决该问题得到l个最佳节点并将其删除。仿真结果表明:相比于传统模型,通过本模型选择的l个最佳节点能够将信息传播的影响力控制在更小的范围,且处理时间更短。
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赵宇
黄开枝
郭云飞
赵星
关键词 在线社会网络信息传播阻断影响力最小随机优化混合整数编码    
Abstract:Information diffusion blocking maximization is used to select and delete the best l nodes (edges) to minimize the number of nodes receiving information in the network. However, the model does not take into account the node's influence which blocks the information flow and lowers the efficiency. This paper presents an information diffusion blocking model that considers the node's influence with a method based on the sampling average approximation (SAA). The model is selects and deletes the best l nodes to change the network structure which minimizing the influence of the target nodes. The model is a stochastic optimization problem which is transferred into a deterministic problem using SAA. The problem is then encoded as a mixed integer programming (MIP) problem. Finally, a quantum genetic algorithm is used to select the best l nodes and remove them. Simulations show that the best l nodes selected by this model influence the information diffusion over a smaller range and the processing time is shorter than the traditional model.
Key wordssocial network    information diffusion blocking    minimum influence    stochastic optimization    mixed integer programming (MIP)
收稿日期: 2017-04-24      出版日期: 2017-12-15
ZTFLH:  TN915.81  
通讯作者: 黄开枝,教授,E-mail:huangkaizhi@tsinghua.edu.cn     E-mail: huangkaizhi@tsinghua.edu.cn
引用本文:   
赵宇, 黄开枝, 郭云飞, 赵星. 在线社会网络中面向节点影响力的信息传播阻断模型[J]. 清华大学学报(自然科学版), 2017, 57(12): 1245-1253.
ZHAO Yu, HUANG Kaizhi, GUO Yunfei, ZHAO Xing. Information diffusion blocking model of node influence-oriented in online social network. Journal of Tsinghua University(Science and Technology), 2017, 57(12): 1245-1253.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2017.25.061  或          http://jst.tsinghuajournals.com/CN/Y2017/V57/I12/1245
  图1 独立级联模型示意图
  图2 信息阻断有效性示意图
  图3 目标函数不满足子模特征示意图
  图4 目标函数不满足子模和超模特征示意图
  表1 量子旋转门的调整策略
  表2 采用的数据集
  图5 Tw i t t e r网络中阻断影响力对比示意图
  图6 S l a s h d o t网络中阻断影响力对比示意图
  图7 E p i n i o n s网络中阻断影响力对比示意图
  图8 3种网络中不同采样数量的影响
  图9 预处理与正常计算时运算时间对比图
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