| 基于社区的关键节点挖掘算法 |
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| 引用本文： | 陆晓野,陈玮. 基于社区的关键节点挖掘算法[J]. 计算机系统应用, 2012, 21(4): 250-253,197 |
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| 作者姓名： | 陆晓野 陈玮 |
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| 作者单位： | 上海理工大学光电信息与计算机工程学院,上海200093 |
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| 摘 要： | 在对大型网络进行关键节点挖掘方面,传统方法效率低下。针对这一缺陷,提出了一种基于社区的关键节点挖掘算法,首先对社区发现算法进行改进,然后提出基于节点频度中心度的挖掘算法。实验结果表明,新算法对社区进行关键节点挖掘时,不仅挖掘的影响度得到保证,而且效率显著提高。
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| 关 键 词： | 关键节点 社区发现 社会网络 频度中心度 影响度 |
| 收稿时间： | 2011-06-07 |
| 修稿时间： | 2011-07-16 |
Key-Nodes Mining Algorithm Based on Communities |
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| LU Xiao-Ye and CHEN Wei. Key-Nodes Mining Algorithm Based on Communities[J]. Computer Systems& Applications, 2012, 21(4): 250-253,197 |
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| Authors: | LU Xiao-Ye and CHEN Wei |
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| Affiliation: | (School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China) |
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| Abstract: | When mining the key-nodes from large-scale networks, the traditional methods are poor efficiency. To address this defect, a new algorithm, which based on communities, is presented for mining the key-nodes. First, it improved the community detection algorithms, and then put forward an algorithm based on degree centrality of the node for mining the key-nodes. The experimental results show that when applying the new algorithm to mine the key-nodes from communities, not only the influence degree of mining is guaranteed, but also the efficiency is improved significantly. |
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| Keywords: | key-nodes community detection social networks degree centrality influence degree |
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