论文标题
使用特征向量中心性的Pagerank算法 - 新方法
PageRank Algorithm using Eigenvector Centrality -- New Approach
论文作者
论文摘要
该研究的目的是找到可以代替Pagerank使用的中心度度量，并找出可以代替Pagerank的条件。经过分析和比较使用Spearman的等级系数相关的大量节点的图形，可以明显的结论是，可以在有向网络中安全地使用Pagerank安全地使用特征向量，以在时间复杂性方面提高性能。
The purpose of the research is to find a centrality measure that can be used in place of PageRank and to find out the conditions where we can use it in place of PageRank. After analysis and comparison of graphs with a large number of nodes using Spearman's Rank Coefficient Correlation, the conclusion is evident that Eigenvector can be safely used in place of PageRank in directed networks to improve the performance in terms of the time complexity.
