计算机科学 ›› 2021, Vol. 48 ›› Issue (12): 226-230.doi: 10.11896/jsjkx.200800026
龚追飞, 魏传佳
GONG Zhui-fei, WEI Chuan-jia
摘要: 为了提高复杂网络链路预测的性能,采用拓扑相似和XGBoost算法来完成复杂网络链路预测。利用复杂网络拓扑结构建立邻接矩阵,求解共同邻居集合,然后根据拓扑相似理论计算复杂网络相似得分函数,将各个时间窗的得分函数和权重参数作为输入,采用XGBoost算法实现复杂网络的链路预测。通过差异化设置XGBoost算法的两个正则化系数,测试其对链路预测准确率的影响,获取最优正则化系数,从而得到稳定的XGBoost链路预测模型。实验证明,时间窗数量设置合理的情况下,相比常用网络链路预测算法,基于拓扑相似和XGBoost算法的预测准确率优势明显,且预测时间性能和其他算法的差距较小,尤其适用于大规模的复杂网络链路预测。
中图分类号:
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