计算机科学 ›› 2022, Vol. 49 ›› Issue (2): 216-222.doi: 10.11896/jsjkx.210100107
赵学磊, 季新生, 刘树新, 李英乐, 李海涛
ZHAO Xue-lei, JI Xin-sheng, LIU Shu-xin, LI Ying-le, LI Hai-tao
摘要: 链路预测旨在利用可获得的网络拓扑信息预测未知的连接关系。基于路径联系的预测方法在无向网络中取得了较好的效果。然而,在有向网络下,相同长度的路径因路径中连边方向不同会造成节点连接强度不同,传统预测方法难以区分路径异构造成的差异。鉴于此,首先以边权矩阵量化各类有向边连接强度的差异,进而为节点间不同异构的多类路径计算其连接强度,然后区分同一长度路径下各类路径的作用大小,最后综合多阶不同长度路径贡献,提出了一种基于路径连接强度的有向网络链路预测方法。在9个真实网络数据集上进行了实验,结果表明,考虑路径连接强度差异有效提高了在AUC及Precision衡量标准下的预测性能。
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