摘要
社团划分在生物化学、社会学、生态系统等方面有广泛的应用。划分结果的可靠性和算法效率是研究的重点。Louvain算法是一个划分结果相对可靠、算法效率较高的算法。该文针对Louvain算法在处理叶节点方面进行了改进。通过研究叶节点的特性和Louvain算法的不足之处,在改进算法中基于叶节点特性进行提前剪枝,以避免多余运算。用改进算法和Louvain算法分别对18组人工数据和一组某个机构的实际邮件数据进行处理,将结果进行对比发现改进算法在保持划分结果准确度不变的情况下,有效地提高了处理速度。
Community dipartition is used in biochemistry, sociology, eco-systems, etc. The reliability of the results and the efficiency of the algorithm are the focus of the study. The Louvain algorithm is an algorithm with relatively reliable result and better efficiency. In this paper, the Louvain algorithm is improved in dealing With the leaf nodes. By studying the characteristics of the leaf nodes and the inadequacies of Louvain algorithm, the improved algorithm prunes the leaf nodes to avoid redundant computation. 18 sets of artificial data and the email data of our school are respectively processed using improved algorithm and Louvain algorithm. The comparison of results shows that the improved algorithm improves the processing speed while maintaining the result reliable.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2013年第1期105-108,共4页
Journal of University of Electronic Science and Technology of China
基金
国家863计划主题项目(2011AA010706)
国家自然科学基金(61133016)
关键词
社团
社团划分
效率
关系网络
community
community dipartition
efficiency
network of relationships
作者简介
吴祖峰（1978－）．男．博士。主要从事信息安全方面的研究．
