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Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank
oleh: LI Lan-yin, ZHOU Qiu-Li, KONG Yin, DONG Yi-ming
Format: | Article |
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Diterbitkan: | Harbin University of Science and Technology Publications 2017-04-01 |
Deskripsi
The traditional PageRank algorithm can not efficiently perform large data Webpage scheduling problem. This paper proposes an accelerated algorithm named topK-Rank,which is based on PageRank on the MapReduce platform. It can find top k nodes efficiently for a given graph without sacrificing accuracy. In order to identify top k nodes,topK-Rank algorithm prunes unnecessary nodes and edges in each iteration to dynamically construct 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 algorithm can find k nodes much faster than the existing approaches.