A Comparative Study of Community Structure Based Node Scores for Network Immunization
A Comparative Study of Community Structure Based Node Scores for Network Immunization
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DOI：
10.1007/978-3-642-35236-2_33
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发表时间：
2012-12
期刊：
影响因子：
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通讯作者：
Yuu Yamada;Tetsuya Yoshida
中科院分区：
文献类型：
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作者：
Yuu Yamada;Tetsuya Yoshida
网络免疫通常通过删除具有大网络中心性的节点来进行，以便整个网络可以被分割成更小的子图。由于污染（例如，病毒）在网络中沿沿着链路的子图（社区）之间传播，除了中心性外，社区结构的利用似乎对免疫是有效的。我们已经提出了社区结构的节点分数在网络中的节点的矢量表示。在本文中，我们报告了一个比较研究，我们的节点得分在合成和真实世界的网络。通过网络的可视化，阐明了节点得分的特征。进行了大量的实验，比较节点得分与其他基于中心性的免疫策略。结果令人鼓舞，表明节点得分很有希望。
Network immunization has often been conducted by removing nodes with large network centrality so that the whole network can be fragmented into smaller subgraphs. Since contamination (e.g., virus) is propagated among subgraphs (communities) along links in a network, besides centrality, utilization of community structure seems effective for immunization. We have proposed community structure based node scores in terms of a vector representation of nodes in a network. In this paper we report a comparative study of our node scores over both synthetic and real-world networks. The characteristics of the node scores are clarified through the visualization of networks. Extensive experiments are conducted to compare the node scores with other centrality based immunization strategies. The results are encouraging and indicate that the node scores are promising.