边缘覆盖去重的社交网络影响力最大化算法

发布时间：2018-03-22 14:28

本文选题：社交网络　切入点：影响力最大化　出处：《计算机科学与探索》2017年05期 　论文类型：期刊论文

【摘要】：影响力最大化问题是在社交网络中寻找具有最大影响范围的节点集。针对启发式算法准确度相对较差的问题,现有的研究考虑了影响范围重合,但忽略了边缘贡献导致的节点影响力过量评估。重点研究了在考虑边缘贡献的情况下,如何选取影响范围最大的节点集合。采用启发式算法的思想,首先计算节点全局和邻近影响力来评估节点信息传播影响力,通过去除已选节点影响范围并更新网络的方式,消除边缘贡献对节点影响力评估的干扰,在独立级联模型基础上提出了基于边缘去重的节点影响力最大化算法。仿真结果表明所提出算法相比其他算法,能够有效增大节点信息传播影响范围。
[Abstract]:The influence maximization problem is to find the node set with the largest influence range in the social network. For the problem of relatively poor accuracy of heuristic algorithm, the existing research has considered the coincidence of the influence range. However, the overevaluation of node influence caused by edge contribution is ignored. The emphasis is put on how to select the node set with the largest influence range under the consideration of edge contribution. The idea of heuristic algorithm is adopted. Firstly, the global and adjacent influence of the nodes is calculated to evaluate the impact of the nodes' information dissemination. By removing the influence range of the selected nodes and updating the network, the interference of the edge contribution to the evaluation of the node's influence is eliminated. Based on the independent cascade model, a node influence maximization algorithm based on edge removal is proposed. The simulation results show that the proposed algorithm can effectively increase the influence range of node information transmission compared with other algorithms.
【作者单位】：重庆邮电大学通信与信息工程学院;重庆大学计算机学院;
【基金】：国家自然科学基金No.61401051 重庆市科委基础和前沿研究项目No.cstc2014jcyj A40039 重庆市教委科学技术研究项目No.KJ1400402~~
【分类号】：TP301.6

【相似文献】