基于特征工程的重要节点挖掘方法

复杂网络中重要节点的挖掘对分析和治理现实复杂系统有着重要的指导意义。设计能反映节点重要性的有效计算方法，是高效准确挖掘重要节点的关键。该文基于节点的邻居信息，采用特征工程中的特征提取、特征重构等方法提取能有效反映节点局部结构的特征向量。利用局部特征向量，通过回归模型建立节点局部结构和重要性的关系模型。在13个真实网络上的实验结果表明，相比于已有的重要节点挖掘基准方法，该方法具有更优的性能。

Identifying Critical Nodes Based on Feature Engineering

To mine important nodes in complex networks is very important for analyzing and governing real complex systems. Designing a good indicator that reflects the importance of nodes is a key issue on efficiently and accurately mining critical nodes. On the bases of the neighbor information of nodes, the features that can effectively reflect the local structure of nodes are extracted through feature extraction and reconstruction. The relational model between local structure and real importance of nodes is established by utilizing regression model based on the extracted features. The experimental results on 13 real networks show that the proposed method outperforms the benchmark methods of critical nodes identification.