山东农业大学学报（自然科学版）2017，Vol.48Issue(4)：521-524,4.DOI:10.3969/j.issn.1000-2324.2017.04.008
基于非参数估计与随机模拟的不确定数据流相似性度量方法
An Uncertain Data Stream Similarity Measurement Method Based on Nonparametric Estimation and Stochastic Simulation
迟荣华 1黄少滨 1李熔盛1
作者信息
- 1. 哈尔滨工程大学 计算机科学与技术学院, 黑龙江 哈尔滨 150001
- 折叠
摘要
Abstract
To solve the problem that the current uncertain data stream is difficult to measure the similarity, this paper proposes a method combining non-parametric estimation with stochastic simulation. The method used the non-parametric estimation to model the uncertain data stream objects, and then used stochastic simulation to calculate the error similarity between objects, judged the similarity by relative distance and absolute distance. Simulation experiment verified this method can not only measure the similarity between the uncertain objects accurately, but also can obtain fast and stable results when the object scale is large.关键词
不确定数据流/非参数估计/随机模拟/相似性Key words
Uncertain data stream/non-parametric estimation/stochastic simulation/similarity分类
信息技术与安全科学引用本文复制引用
迟荣华,黄少滨,李熔盛..基于非参数估计与随机模拟的不确定数据流相似性度量方法[J].山东农业大学学报（自然科学版）,2017,48(4):521-524,4.
