标题： 通过矩阵方程和广义随机游走进行角色提取 显示英文标题

标题： Role extraction by matrix equations and generalized random walks

摘要： 网络中的节点可以根据相似的连接模式分组为“角色”。 这通常是通过定义一个成对节点相似性矩阵，然后对这个矩阵的行和列进行聚类来实现的。 本文提出了一种新的相似性矩阵，用于解决有向网络中的角色提取问题，该矩阵定义为一个矩阵方程的解，并基于可以沿链接方向和相反方向进行的随机游走计算节点相似性。 这种得到的节点相似性度量在具有异构节点度分布的有向网络的角色提取任务中表现非常出色。 显示英文摘要

摘要： The nodes in a network can be grouped into 'roles' based on similar connection patterns. This is usually achieved by defining a pairwise node similarity matrix and then clustering rows and columns of this matrix. This paper presents a new similarity matrix for solving role extraction problems in directed networks, which is defined as the solution of a matrix equation and computes node similarities based on random walks that can proceed along the link direction and in the opposite direction. The resulting node similarity measure performs remarkably in role extraction tasks on directed networks with heterogeneous node degree distributions.