Fully distributed PageRank computation with exponential convergence
Distributed, Parallel, and Cluster Computing
2018-10-23 v2 Systems and Control
Abstract
This work studies a fully distributed algorithm for computing the PageRank vector, which is inspired by the Matching Pursuit and features: 1) a fully distributed implementation 2) convergence in expectation with exponential rate 3) low storage requirement (two scalar values per page). Illustrative experiments are conducted to verify the findings.
Cite
@article{arxiv.1705.09927,
title = {Fully distributed PageRank computation with exponential convergence},
author = {Liang Dai and Nikolaos M. Freris},
journal= {arXiv preprint arXiv:1705.09927},
year = {2018}
}