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计算机系统应用英文版:2020,29(11):163-167
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基于Node2Vec的重叠社区发现算法
(青岛科技大学 信息科学技术学院, 青岛 266061)
Overlapping Community Discovery Algorithm Based on Node2Vec
(College of Information Science and Technology, Qingdao University of Science and Technology, Qingdao 266061, China)
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Received:March 12, 2020    Revised:April 12, 2020
中文摘要: 针对目前基于种子节点选择的社区发现算法在准确性和复杂度等方面存在的不足, 提出了一种基于Node2Vec的重叠社区发现算法. 首先, 使用Node2Vec算法学习到网络中每个节点的向量表示, 用以计算节点间的相似度, 其次, 利用节点影响力函数计算节点影响力并找出种子节点, 然后基于每个种子节点进行社区的扩展优化, 最终挖掘出高质量的重叠社区结构. 本文选取多个真实网络进行了对比实验, 结果表明, 本文所提出的算法能够在保证良好稳定性的前提下发现高质量的社区结构.
Abstract:In view of the shortcomings in accuracy and complexity of community discovery algorithm based on seed node selection, a Node2Vec overlapping community discovery algorithm is proposed. First, the vector representation of each node in the network is learned by using Node2Vec algorithm to calculate the similarity between nodes. Second, the node influence function is used to calculate the node influence and find out the seed node. Then the community extension optimization is carried out based on each seed node. Finally the high quality overlapping community structure is excavated. In this study, several real networks are selected for comparative experiments, and the results show that the proposed algorithm can find high quality community structures under the premise of ensuring sound stability.
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基金项目:国家自然科学基金(F030810); 山东省重点研发计划(2018GGX101052)
引用文本:
陈卓,姜鹏,袁玺明.基于Node2Vec的重叠社区发现算法.计算机系统应用,2020,29(11):163-167
CHEN Zhuo,JIANG Peng,YUAN Xi-Ming.Overlapping Community Discovery Algorithm Based on Node2Vec.COMPUTER SYSTEMS APPLICATIONS,2020,29(11):163-167