LI Lau-协uR-, ZHOU口iu-Li, KONG Yin DONG Yi-miuR-. Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank[J]. 2017, 22(2): 117-123.
DOI:
LI Lau-协uR-, ZHOU口iu-Li, KONG Yin DONG Yi-miuR-. Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank[J]. 2017, 22(2): 117-123.DOI: 10.15938/j.jhust.2017.02.022.
Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank
The traditional PageRank algorithm can not efficiently perform large data Webpage schedulingproblem. This paper proposes an accelerated algorithm named topK-Rank,which is based on PageRank on theMapReduce platform. It can find top k nodes efficiently for a given graph without sacrificing accuracy. In order toidentify top k nodes,topK-Rank algorithm prunes unnecessary nodes and edges in each iteration to dynamicallyconstruct subgraphs,and iteratively estimates lower/upper bounds of PageRank scores through subgraphs.Theoretical analysis shows that this method guarantees result exactness. Experiments show that topK-Rank algorithmcan find k nodes much faster than the existing approaches.