基于模体结构和度信息的关键节点组识别
TP391; 为了探究具有更小规模的高阶结构对关键节点组的影响,以优化网络传播为目标,提出了一种基于模体结构和度信息的关键节点组识别算法.基于模体结构对节点影响力进行评估,挖掘模体结构的核心节点,使用多准则妥协解排序(VIKOR)法将其与度信息进行融合,并利用种子排除算法对种子节点的邻居进行排除,有效减小影响力重叠问题.在SIR传播模型的基础上,选取6 个不同的无向网络与4种基准算法进行比较,实验结果表明,所提算法在准确性和稳定性方面表现出更好的性能....
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| Published in | 通信学报 Vol. 45; no. 3; pp. 258 - 269 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
太原理工大学电气与动力工程学院,山西 太原 030024
25.03.2024
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1000-436X |
| DOI | 10.11959/j.issn.1000-436x.2024052 |
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| Abstract | TP391; 为了探究具有更小规模的高阶结构对关键节点组的影响,以优化网络传播为目标,提出了一种基于模体结构和度信息的关键节点组识别算法.基于模体结构对节点影响力进行评估,挖掘模体结构的核心节点,使用多准则妥协解排序(VIKOR)法将其与度信息进行融合,并利用种子排除算法对种子节点的邻居进行排除,有效减小影响力重叠问题.在SIR传播模型的基础上,选取6 个不同的无向网络与4种基准算法进行比较,实验结果表明,所提算法在准确性和稳定性方面表现出更好的性能. |
|---|---|
| AbstractList | TP391; 为了探究具有更小规模的高阶结构对关键节点组的影响,以优化网络传播为目标,提出了一种基于模体结构和度信息的关键节点组识别算法.基于模体结构对节点影响力进行评估,挖掘模体结构的核心节点,使用多准则妥协解排序(VIKOR)法将其与度信息进行融合,并利用种子排除算法对种子节点的邻居进行排除,有效减小影响力重叠问题.在SIR传播模型的基础上,选取6 个不同的无向网络与4种基准算法进行比较,实验结果表明,所提算法在准确性和稳定性方面表现出更好的性能. |
| Abstract_FL | In order to explore the impact of higher-order structures with smaller scales on key node group mining prob-lems and with the goal of optimizing network propagation,a key node group recognition algorithm was proposed based on motif structure and degree information.Firstly,the influence of nodes was evaluated based on the motif structure,and the core nodes of the motif structure were excavated.Then,the VIKOR method was used to fuse it with degree infor-mation.Finally,the seed exclusion algorithm was used to exclude the neighbors of the seed nodes,effectively reducing the problem of influence overlap.Based on the SIR propagation model,six different undirected networks were selected for comparison with four benchmark algorithms.The experimental results show that the proposed algorithm performs better in terms of accuracy and stability. |
| Author | 张辽 于海龙 杨云云 王力 |
| AuthorAffiliation | 太原理工大学电气与动力工程学院,山西 太原 030024 |
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| Author_FL | ZHANG Liao YANG Yunyun YU Hailong WANG Li |
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| DocumentTitle_FL | Identification of key node groups based on motif structure and degree information |
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| Keywords | 影响力最大化 influence maximization motif key node group 关键节点组 模体 |
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| Title | 基于模体结构和度信息的关键节点组识别 |
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