改进的加权复杂网络节点重要度评估的收缩方法

Improved evaluation method for node importance based on node contraction in weighted complex networks

分析了加权复杂网络的结构特点,综合考虑了边权对节点重要度评估的影响,给出了加权节点重要度的新定义,并提出了改进的适用于加权网络的节点收缩方法。该方法认为最重要的节点就是收缩后加权网络凝聚度最大的节点,其算法的时间复杂度为O(n3)。该方法有助于更准确地发现复杂网络中的关键节点。最后的实验分析验证了方法的有效性和可行性。

The structure characters of weighted complex networks are analysed. The effect of the edgeweight on estimation of node importance is calculated. A new definition of weighted node importance is proposed, and an improved node contraction method in weighted networks is given based on the evaluation criterion, i.e. the most important node is the one whose contraction results are the largest increase of the weighted networks agglomeration. The time complexity of this algorithm is O（n^3） , and the improved evaluation method can help exactly to find some critical nodes in complex networks. Final experiments verify the efficiency and feasibility of the proposed method.