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中国物理学会期刊

复杂网络链路可预测性: 基于特征谱视角

CSTR: 32037.14.aps.69.20191817

Link predictability of complex network from spectrum perspective

CSTR: 32037.14.aps.69.20191817
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  • 近年来链路预测的理论和实证研究发展迅速, 大部分工作关注于提出更精确的预测算法. 事实上, 链路预测的前提是网络的结构本身能够被预测, 这种“可被预测的程度”可以看作是网络自身的基本属性. 本文拟从特征谱的视角去解释网络的链路可预测性, 并刻画网络的拓扑结构信息, 通过对网络特征谱进行分析, 构造了复杂网络链路可预测性评价指标. 通过该指标计算和分析不同网络的链路可预测性, 能够在选择算法前获取目标网络能够被预测的难易程度, 解决到底是网络本身难以预测还是预测算法不合适的问题, 为复杂网络与链路预测算法的选择和匹配问题提供帮助.

     

    Link prediction in complex networks has attracted much attention in recent years and most of work focuses on proposing more accurate prediction algorithms. In fact, “how difficultly the target network can be predicted” can be regarded as an important attribute of the network itself. In this paper it is intended to explain and characterize the link predictability of the network from the perspective of spectrum. By analyzing the characteristic spectrum of the network, we propose the network link predictability index. Through calculating the index, it is possible to learn how difficultly the target network can be predicted before choosing algorithm, and to solve the problem whether the network is unpredictable or the algorithm is inappropriate. The results are useful for the selecting and matching the complex network and link prediction algorithms.

     

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