计算机科学 ›› 2020, Vol. 47 ›› Issue (12): 279-284.doi: 10.11896/jsjkx.191000199
吴勇, 王斌君, 翟一鸣, 仝鑫
WU Yong, WANG Bin-jun, ZHAI Yi-ming, TONG Xin
摘要: 网络嵌入旨在将网络节点嵌入到一个低维向量空间且最大程度地保存原有网络的拓扑结构及其属性.相比无向网络有向网络具有特殊的非对称传递性可体现在节点之间的高阶相似度量中如何较好地保存这一特性是当前有向网络嵌入研究的热点和难点.针对此问题通过引入有向网络的共引网络设计了共引信息的度量函数给出了一种有向网络高阶相似度量指标融合共引信息的统一框架提出了可以保存非对称传递性的共引增强的高阶相似保存网络嵌入模型(Co-Citation Enhancing High-Order Proximity preserved EmbeddingCCE-HOPE).在4个真实数据集上进行链路预测实验的结果表明不同高阶相似度量指标下不同比重共引信息对效果影响具有一般规律因此可以给出比重的最佳取值范围;在此范围内与现有方法相比CCE-HOPE方法可有效提高链接预测的准确度.
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