计算机工程2017，Vol.43Issue(4)：200-206,7.DOI:10.3969/j.issn.1000-3428.2017.04.034
在线社交网络的自适应UNI采样方法
Adaptive UNI Sampling Method for Online Social Network
摘要
Abstract
Online Social Network(OSN)sampling method is usually used as the benchmark to evaluate other sampling methods.However,the poor performance of UNI limits its application.In this paper,a sampling method called adaptive UNI is proposed.In this method,the whole space of user ID system is divided into intervals.The probability of sampling is adaptively adjusted in each interval according to the real hit rate of the interval.In this process,a threshold is set as the lower limit to solve the cold start problem,while the sampling rate of the interval is used to avoid local optimum.The validity of the method is proved by applying it to real sampling from Weibo.Experimental results show that the method can improve the sampling efficiency and hit rate.关键词
在线社交网络/采样方法/UNI方法/自适应方法/区间划分Key words
Online Social Network(OSN)/sampling method/UNI method/adaptive method/interval partition分类
信息技术与安全科学引用本文复制引用
尤枫,曹天亮,卢罡..在线社交网络的自适应UNI采样方法[J].计算机工程,2017,43(4):200-206,7.基金项目
北京高等学校青年英才计划项目(YETP0506). （YETP0506）
