Efficient Parallel Computation of PageRank

@inproceedings{Kohlschtter2006EfficientPC,
  title={Efficient Parallel Computation of PageRank},
  author={Christian Kohlsch{\"u}tter and Paul-Alexandru Chirita and Wolfgang Nejdl},
  booktitle={ECIR},
  year={2006}
}
PageRank inherently is massively parallelizable and distributable, as a result of web’s strict host-based link locality. In this paper we show that the Gauß-Seidel iterative method for solving linear systems can be successfully applied in such a parallel ranking scenario in order to improve convergence. By introducing a two-dimensional web model and by adapting the PageRank to this environment, we present and evaluate efficient methods to compute the exact rank vector even for large-scale web… CONTINUE READING
Highly Cited
This paper has 53 citations. REVIEW CITATIONS
32 Citations
24 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 32 extracted citations

54 Citations

051015'09'12'15'18
Citations per Year
Semantic Scholar estimates that this publication has 54 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.

Similar Papers

Loading similar papers…