Sampling algorithms for stochastic graphs: A learning automata approach

作者：

Highlights：

• Stochastic graph as a graph model for complex social networks.

• Four sampling algorithms for stochastic graphs in which edge weights are random variables.

• Analyze complex networks using stochastic network measures and sampling algorithms.

• Study the performance of the sampling algorithms on the stochastic networks.

摘要

•Stochastic graph as a graph model for complex social networks.•Four sampling algorithms for stochastic graphs in which edge weights are random variables.•Analyze complex networks using stochastic network measures and sampling algorithms.•Study the performance of the sampling algorithms on the stochastic networks.

论文关键词：Stochastic graphs,Network sampling,Network measures,Complex networks,Learning automata

论文评审过程：Received 1 November 2016, Revised 22 April 2017, Accepted 24 April 2017, Available online 25 April 2017, Version of Record 12 May 2017.

论文官网地址：https://doi.org/10.1016/j.knosys.2017.04.012