Parallel Simrank Computing on Large Scale Dataset on Mapreduce

  • Lina LiEmail author
  • Cuiping Li
  • Hong Chen
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 387)


Many fields need computing the similarity between objects, such as recommendation system, search engine etc. Simrank is one of the simple and intuitive algorithms. It is rigidly based on the random walk theorem. There are three existing iterative ways to compute simrank, however, all of them have one problem, that is time consuming; moreover, with the rapidly growing data on the Internet, we need a novel parallel method to compute simrank on large scale dataset. Hadoop is one of the popular distributed platforms. This paper combines the features of the Hadoop and computes the simrank parallel with different methods, and compars them in the performance.


Simrank Parallel Mapreduce Hadoop 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Renmin University of ChinaBeijingChina

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