计算机科学 ›› 2018, Vol. 45 ›› Issue (11): 92-96.doi: 10.11896/j.issn.1002-137X.2018.11.013
吕亚楠, 韩华, 贾承丰, 完颜娟
LV Ya-nan, HAN Hua, JIA Cheng-feng, WAN Yan-juan
摘要: 链路预测作为复杂网络分析的一个重要分支,在不同领域中有着广泛的应用。现有的链路预测算法通常根据共同邻居节点的结构信息来度量节点对之间的相似性,忽略了节点对与其共同邻居节点之间的连接紧密程度。针对此问题,提出了一种基于节点亲密度的链路预测算法。该算法利用边聚集系数来测量节点对与其共同邻居节点之间的紧密程度,以AUC值作为链路预测的精确度评价指标。在4个真实网络上的实验结果表明,相比于其他相似性算法,所提出的算法提高了链路预测的预测精度。
中图分类号:
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