Walk, Not Wait: Faster Sampling Over Online Social Networks
Abstract
In this paper, we introduce a novel, general purpose, technique for faster sampling of nodes over an online social network. Specifically, unlike traditional random walk which wait for the convergence of sampling distribution to a predetermined target distribution - a waiting process that incurs a high query cost - we develop WALK-ESTIMATE, which starts with a much shorter random walk, and then proactively estimate the sampling probability for the node taken before using acceptance-rejection sampling to adjust the sampling probability to the predetermined target distribution. We present a novel backward random walk technique which provides provably unbiased estimations for the sampling probability, and demonstrate the superiority of WALK-ESTIMATE over traditional random walks through theoretical analysis and extensive experiments over real world online social networks.
Cite
@article{arxiv.1410.7833,
title = {Walk, Not Wait: Faster Sampling Over Online Social Networks},
author = {Azade Nazi and Zhuojie Zhou and Saravanan Thirumuruganathan and Nan Zhang and Gautam Das},
journal= {arXiv preprint arXiv:1410.7833},
year = {2014}
}