首页> 外文会议>International Conference on Social Computing >Faster Clustering Coefficient Using Vertex Covers
【24h】

Faster Clustering Coefficient Using Vertex Covers

机译:使用顶点封面更快的聚类系数

获取原文

摘要

Clustering coefficients, also called triangle counting, is a widely-used graph analytic for measuring the closeness in which vertices cluster together. Intuitively, clustering coefficients can be thought of as the ratio of common friends versus all possible connections a person might have in a social network. The best known time complexity for computing clustering coefficients uses adjacency list intersection and is O(V . d~(2max)), where d_(ma)x is the size of the largest adjacency list of all the vertices in the graph. In this work, we show a novel approach for computing the clustering coefficients in an undirected and unweighted graphs by exploiting the use of a vertex cover, V ? V. This new approach reduces the number of times that a triangle is counted by as many as 3 times per triangle. The complexity of the new algorithm is O(V . d~2_max + t_(VC)) where d_(max) is the size of the largest adjacency list in the vertex cover and t_(VC) is the time needed for finding the vertex cover. Even for a simple vertex cover algorithm this can reduce the execution time 10% - 30% while counting the exact number of triangles (3-circuits). We extend the use of the vertex cover to support counting squares (4-circuits) and clustering coefficients for dynamic graphs.
机译:聚类系数,也称为三角形计数,是一种广泛使用的图形分析,用于测量顶点集群在一起的近距离的分析。直观地,群集系数可以被认为是常见朋友与所有可能在社交网络中可能拥有的所有可能连接的比率。用于计算聚类系数的最佳已知时间复杂度使用邻接列表交叉点,并且是O(v。 d〜(2max)),其中d_(ma)x是图表中所有顶点的最大邻接列表的大小。在这项工作中,我们通过利用顶点覆盖物(V)显示了一种用于计算无向和未加权的图表中的聚类系数的新方法。 V.这种新方法减少了三角形按照每个三角形计算的三次数量的次数。新算法的复杂性是O(v。d〜2_max + t_(vc)),其中d_(max)是顶点封面中最大邻接列表的大小,并且t_(vc)是查找顶点所需的时间覆盖。即使对于简单的顶点覆盖算法,这也可以减少执行时间10%-30%,同时计算三角形的确切数量(3电路)。我们扩展了顶点盖的使用,以支持计数正方形(4电路)和动态图形的聚类系数。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号