计算机科学 ›› 2017, Vol. 44 ›› Issue (12): 28-32.doi: 10.11896/j.issn.1002-137X.2017.12.005
吕文渊,周丽华,廖仁建
LV Wen-yuan, ZHOU Li-hua and LIAO Ren-jian
摘要: 网络逐渐成为了人与人之间的主要社交工具,在网络中挖掘最有影响力的用户成为了非常值得关注的问题。在传统影响力最大化算法的基础上提出了一种面向主题耦合的影响力最大化算法,该算法首先分析网络中不同主题之间的耦合相似性,在综合考虑主题之间耦合相似性与用户对不同主题偏好的基础上扩展独立级联模型,并使用经典的贪心算法挖掘最具有影响力的用户。与不考虑主题耦合的影响力最大化算法相比,所提算法考虑了传播主题之间的耦合相似性,并且能够与用户偏好进行更为有效地结合。最后,实验表明,相比于经典的影响力最大化算法,该算法能够更为有效地挖 掘在特定主题下最具有影响力的种子节点。
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