公私图中的公私核心维护

Dongxiao Yu;Xilian Zhang;Qi Luo;Lifang Zhang;Zhenzhen Xie;Zhipeng Cai
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引用次数: 1

摘要

开发了一个公私图(pp-graph)来模拟具有隐藏关系的社交网络,它由一个公共图(其边缘对所有用户可见)和多个私有图(其边缘仅对终端用户可见)组成。与边缘对所有用户可见的传统图相比,它缺乏准确的指标来评估pp图中顶点的重要性。在本文中,我们首先在$k$-core数的基础上提出了一个新的概念——public-private-core (pp-core)数,它综合考虑了顶点的公共图和私有图,来衡量用户的关键程度。在此基础上,我们给出了一种计算pp核数的有效算法,该算法只需要线性的时间和空间。考虑到图可以随时间不断演化,我们还提出了有效的图变化后的pp核维护算法,避免了pp核数的冗余重新计算。在现实社会网络上进行的扩展实验表明,我们的算法具有良好的效率和稳定性。与重新计算所有顶点的pp-core数相比,我们的维护算法可以将计算时间减少约6-8个数量级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Public-Private-Core Maintenance in Public-Private-Graphs
A public-private-graph (pp-graph) is developed to model social networks with hidden relationships, and it consists of one public graph in which edges are visible to all users, and multiple private graphs in which edges are only visible to its endpoint users. In contrast with conventional graphs where the edges can be visible to all users, it lacks accurate indexes to evaluate the importance of a vertex in a pp-graph. In this paper, we first propose a novel concept, public-private-core (pp-core) number based on the $k$ -core number, which integrally considers both the public graph and private graphs of vertices, to measure how critical a user is. We then give an efficient algorithm for the pp-core number computation, which takes only linear time and space. Considering that the graphs can be always evolving over time, we also present effective algorithms for pp-core maintenance after the graph changes, avoiding redundant re-computation of pp-core number. Extension experiments conducted on real-world social networks show that our algorithms achieve good efficiency and stability. Compared to recalculating the pp-core numbers of all vertices, our maintenance algorithms can reduce the computation time by about 6–8 orders of magnitude.
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