计算机科学 ›› 2016, Vol. 43 ›› Issue (Z6): 314-318.doi: 10.11896/j.issn.1002-137X.2016.6A.075
张岩庆,陆余良,杨国正
ZHANG Yan-qing, LU Yu-liang and YANG Guo-zheng
摘要： 目前大多数链路预测方法都是针对丢失链路的结构性预测,缺乏针对未来时刻网络链路的时序性预测,为此提出了一种基于频繁闭图关联规则的链路预测方法。将形式化后的动态网络划分为训练集和测试集,基于Apriori思想从训练集中提取频繁闭图,并根据频繁闭图的时间间隔建立时延分布矩阵,用于表征频繁闭图之间的时序关联规则,在此基础上预测测试集中的网络结构。将该方法运用于不同时间尺度下的AS级Internet动态网络中,结果表明,该方法能够以很高的精确率预测波动型动态网络的链路。
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