Overlapping Community Change-Point Detection in an Evolving Network
Overlapping Community Change-Point Detection in an Evolving Network
复制标题
不断发展的网络中的重叠社区变化点检测
DOI：
10.1109/tbdata.2018.2880780
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发表时间：
2020-03
影响因子：
7.2
通讯作者：
Liu Cong
中科院分区：
文献类型：
--
作者：
Cheng Jiujun;Chen Minjun;Zhou Mengchu;Gao Shangce;Liu Chunmei;Liu Cong
变化点检测是一项任务，它寻找网络发生根本变化的特定时刻。变化点检测是重叠社区演化分析中最重要的挑战之一，其目的是识别重叠社区演化过程中特定动态事件的变化时刻、类型和程度。与重叠社区检测相比，变点检测解决了重叠社区而不是网络拓扑的演变。在本文中，我们提出了这样一种方法，通过重新制定一个重叠的社区的形式，一个一维流的约束温和的程度波动和重叠社区的异质大小分布。根据在一个特定的变化事件中涉及的相互作用的重叠社区的数量，重叠社区变点被分为一元或二元。基于一个信号处理框架和一个基于决策函数的策略，我们所提出的方法发现了一元和二元情况下的变点。在人工数据集上的实验结果表明，该方法比传统的两阶段方法具有更高的准确率和更低的误报率。
Change-point detection is a task that looks for specific moments across which a network changes fundamentally. Change-point detection is one of the most important challenges for overlapping community evolution analysis, and its aim is to identify the moment, type, and degree of change of a specific dynamic event when an overlapping community is evolving. In contrast to overlapping community detection, change-point detection addresses the evolution of an overlapping community rather than a network topology. In this paper, we propose such a method by reformulating an overlapping community in the form of a one-dimensional stream constrained by gentle degree fluctuation and the heterogeneous size distribution of the overlapping communities. According to the number of interacting overlapping communities involved in a specific change event, overlapping community change-points are classified as unary or binary. Based on a signal processing framework and a decision function-based strategy, our proposed method finds the change-points for both unary and binary cases. The experimental results from a synthetic dataset show that our proposed approach can ensure higher accuracy and a lower false positive rate than the traditional two-stage approach.
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DOI：
10.1109/tsmc.2017.2738151
发表时间：
2019-06
期刊：
IEEE Transactions on Systems, Man, and Cybernetics: Systems
影响因子：
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作者：
Jie Zhang;Zhi Wei;Zhenyu Yan;Mengchu Zhou;Abhishek Pani
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DOI：
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期刊：
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影响因子：
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DOI：
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发表时间：
2008-11
期刊：
2008 4th International Conference on Wireless Communications, Networking and Mobile Computing
影响因子：
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通讯作者：
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DOI：
10.1109/tkde.2016.2551241
发表时间：
2016-08-01
影响因子：
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作者：
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DOI：
10.1109/tsmc.2017.2779138
发表时间：
2019
期刊：
IEEE Transactions on Systems, Man, and Cybernetics: Systems
影响因子：
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作者：
Jiujun Cheng;Xiao Wu;Mengchu Zhou;Shangce Gao;Zhenhua Huang;Cong Liu
通讯作者：
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