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TopRank(k)算法与PageRank算法的比较研究 被引量:2

Comparative Study of Top Rank Algorithm and Page Rank Algorithm
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摘要 介绍了一种新的基于接近中心度的排名算法Top Rank(k),并将其与已有的Page Rank算法进行分析比较,说明了它们各自的特点。通过实证分析,论证了在确定条件下,Top Rank(k)算法比Page Rank算法更有效,突出表现为节省大量时间。 The paper introduces a new closeness centrality-based ranking algorithm TopRank(k), and compares it with PageRank algorithm, describes their respective features. Through empirical analysis it demonstrates that TopRank (k) algorithm is more effective than PageRank algorithm under certain conditions, with outstanding performance in significant time saving.
作者 尹莉
机构地区 长安大学图书馆
出处 《情报探索》 2014年第11期13-15,19,共4页 Information Research
基金 中央高校基本科研业务费专项资金资助项目"2001-2013年长安大学科研合作网络及科研影响力实证分析"(项目编号:2014G6504033)的研究成果
关键词 接近中心度 TOP Rank(k)算法 PAGE Rank算法 社会网络分析 closeness centrality algorithm PageRank algorithm social network analysis
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参考文献9

  • 1Brins S,Page L. The Anatomy of a Large-scale Hy- pertextual Web Search Engine [J]. Computer Networks and IS- DN Systems, 1998 (30) : 107-117.
  • 2Langville A,Meyer C. Google's PageRank and Be- yond:The Science of Search Engine Rankings [M]. Princeton University Press, 2006.
  • 3Beanchamp M A. An Improved Index of Centrality [J]. Behavioral Science, 1965(10) : 161-163.
  • 4Dijkstra E W. A Note on Two Problems in Connexion with Graphs[J]. Numerische Mathematik, 1959(1 ) :269-271.
  • 5Eppstein D,Wang J. Fast Approximation of Centrality [J]. Journal of Graph Algorithms and Applications,2004 (1): 39-45.
  • 6Fredman M L,Tarjan R E. Fibonaeci Heaps and Their Uses in Improved Network Optimization Algorithms [J]. Journal of the ACM, 1987 (3) :596-615.
  • 7Hoeffding W. Probability Inequalities for Sums of Bounded Random Variables [J ]. Journal of the ACM, 1963 (1) : 13-30.
  • 8Johnson D B. Efficient Algorithms for Shortest Paths in Sparse Networks[J]. Journal of the ACM, 1977(1):1-13.
  • 9斯科特.社会网分析方法[M].刘军,译.重庆:重庆文艺出版社,2010.

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