| 基于传播影响力的重叠社区划分算法 |
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| 引用本文： | 谭文安,陈雅雯,潘义博. 基于传播影响力的重叠社区划分算法[J]. 上海第二工业大学学报, 2018, 0(2): 145-152 |
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| 作者姓名： | 谭文安 陈雅雯 潘义博 |
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| 作者单位： | 上海第二工业大学计算机与信息工程学院;南京航空航天大学计算机科学与技术学院 |
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| 基金项目： | 上海第二工业大学研究生创新项目, 国家自然科学基金项目(61672022), 上海第二工业大学校重点学科(XXKZD1604) 资助 |
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| 摘 要： | 在研究经典标签传播算法的基础上,提出了一种基于传播影响力的重叠社区划分算法COPRA-PI,可用于挖掘加权网络中的社区结构。该算法在COPRA算法的基础上从节点影响力、边影响力、历史标签影响力3个方面综合考虑传播影响力;同时针对COPRA算法中每个节点在每次迭代过程中均具有相同的最大标签数,且该最大标签数目需手动设置等不足,该算法中设计了一个自适应的最大标签数。实验结果表明,COPRA-PI算法在经典的数据集上对比现有经典算法更能挖掘出高质量的社区结构且收敛速度较快。
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| 关 键 词： | 复杂网络 加权网络 重叠社区发现 标签传播 传播影响力 |
Overlapping Community Detection Algorithm According toPropagating Influence |
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| TAN Wen-an,CHEN Ya-wen and PAN Yi-bo. Overlapping Community Detection Algorithm According toPropagating Influence[J]. Journal of Shanghai Second Polytechnic University, 2018, 0(2): 145-152 |
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| Authors: | TAN Wen-an CHEN Ya-wen PAN Yi-bo |
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| Affiliation: | 1. School of Computer and Information, Shanghai Polytechnic University, Shanghai 201209, China,2. School of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics,Nanjing 211106, China and 2. School of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics,Nanjing 211106, China |
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| Abstract: | This paper proposed an overlapping community detection algorithm according to propagating influence, called COPRA-PI,to mine community structure in weighted networks. COPRA-PI algorithm considers the influence of propagation from three aspectsbased on conventional COPRA: node influence, edge influence and historical label influence. For addressing the issues of that each nodein COPRA has the same maximum number of label which needs to be set manually at each moment, an adaptive maximum number oflabel is also designed. Experimental results show that the proposed COPRA-PI not only can detect the community division accuratelybut also has a fast convergence rate. |
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| Keywords: | complex network weighted network overlapping community detection label propagation propagating influence |
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