| 可多边并行移出的社团发现方法 |
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| 引用本文： | 熊中敏,黄冬梅.可多边并行移出的社团发现方法[J].计算机工程,2009,35(12):29-31. |
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| 作者姓名： | 熊中敏 黄冬梅 |
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| 作者单位： | 1. 复旦大学计算机与信息技术系,上海,200433;上海海洋大学信息学院,上海,201306
2. 上海海洋大学信息学院,上海,201306 |
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| 基金项目： | 国家科技部海洋公益性行业科研专项经费基金，国家重点基础研究发展规划(973计划)，国家自然科学基金，上海海洋大学博士启动基金 |
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| 摘 要： | 针对GN算法计算效率低下的缺陷,提出一个基于边的中介值测度的发现网络潜在社团结构的新算法。该算法在完成所有边的中介值计算后,利用成分的独立性,采用并行移出各个成分中具有最大中介值的边的方法。通过理论分析,在作为实验测试平台的实际的数据集上进行实验验证,结果表明该算法是快速、有效的。
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| 关 键 词： | 社团发现 社会网络 社团结构 图挖掘 |
| 修稿时间： | |
Community Detection Method with Multi-edge Simultaneous Removal |
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| XIONG Zhong-min,HUANG Dong-mei.Community Detection Method with Multi-edge Simultaneous Removal[J].Computer Engineering,2009,35(12):29-31. |
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| Authors: | XIONG Zhong-min HUANG Dong-mei |
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| Affiliation: | 1.Department of Computing and Information Technology;Fudan University;Shanghai 200433;2.School of Information;Shanghai Ocean University;Shanghai 201306 |
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| Abstract: | To address the slow speed of GN algorithm,a new algorithm based on betweenness scores of edges is presented for detecting the underlying community structure in networks.Employing component independency,this algorithm presents a new method through which all edges with the highest betweenness score in respect of each component is simultaneously removed when all betweenness scores are computed.It is proved that this algorithm is fast and effective through theoretical analysis and experiments with several real ... |
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| Keywords: | community detection social networks community structure graph mining |
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