基于层次化社区结构的影响最大化算法

Hierarchical community structure based algorithm for influence maximization

针对贪心算法时间复杂度过高,不适用于大型社会网络问题,提出基于层次化社区结构的影响最大化算法HCSA(hierarchical community structure algorithm)。对社会网络进行层次化社区划分,启发式地选择覆盖率最大的社区层级并按比例分配初始节点,综合节点度数,得出初始节点集合。实验结果表明,与现有启发式算法相比,HCSA算法取得了更广的传播范围和更少的运行时间。

Since the time complexity of the greedy algorithm is too high,and the algorithm does not apply to large social network,hierarchical community structure based algorithm（HCSA）was proposed for influence maximization.The social network was divided into hierarchical communities,community-level with the largest coverage rate was chosen and initial nodes were allocated heuristically.The degree was considered and initial nodes set was obtained.Experimental results show that wider scope of spread and less running time were gained using HCSA.