The Internet is an important component of modern people,s daily life,and computer software is an important force to promote the development of modern internet.The computer software network is also part of the complex network,and thus it is very important to improve the invulnerability of the software network by identifying the important nodes in the computer software network.This paper proposed a node importance measurement method based on local features and global features of network nodes in large-scale software network,the aim of which was to improve the robustness of large software networks.Firstly,it studied the node importance evaluation algorithm,which is based on the node and adjacent to the node degree and degree centrality of nodes.Then,the evaluation results were used to reflect the robustness of software networks.The results of experiment show that this algorithm is effective in identifying the importance of nodes.This algorithm is applicable to measure the importance of nodes in large software network,especially suitable for application software network.%互联网是现代人们日常生活的重要组成部分,计算机软件更是推动现代互联网发展的重要力量.计算机软件网络也是复杂网络的一部分,因此通过识别计算机软件网络中的重要节点来提升软件网络的抗毁性显得尤为重要.针对大型软件网络的节点重要性进行了研究,提出了一种基于网络节点的局部特征和全局特性的节点重要性度量方法,并将节点重要性的度量方法用于大型软件网络鲁棒性的研究.该方法依据各节点重要性与节点自身及以邻接节点的度以及节点的度中心性之间的联系对节点的重要性进行评估,评估结果用于反映软件网络的鲁棒性.实验结果表明:该方法能够细致的描述网络中各节点之间存在的差异性,适用于大型软件网络的节点重要性度量,尤其适用于应用型软件网络.
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