Cleaning of Multi-Source Uncertain Time Series Data Based on PageRank

作     者：高嘉伟 孙纪舟 GAO Jiawei;SUN Jizhou

作者机构：Faculty of Computer and Software EngineeringHuaiyin Institute of TechnologyHuai’an 223003China 

出 版 物：《Journal of Donghua University(English Edition)》 (东华大学学报（英文版）)

年 卷 期：2023年第40卷第6期

页      面：695-700页

学科分类：08[工学] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China(No.62002131) Shuangchuang Ph.D Award(from World Prestigious Universities)of Jiangsu Province,China(No.JSSCBS20211179) 

主　　题：big data data cleaning time series truth discovery PageRank 

摘      要：There are errors in multi-source uncertain time series *** discovery methods for time series data are effective in finding more accurate values,but some have limitations in their *** tackle this challenge,we propose a new and convenient truth discovery method to handle time series data.A more accurate sample is closer to the truth and,consequently,to other accurate *** the mutual-confirm relationship between sensors is very similar to the mutual-quote relationship between web pages,we evaluate sensor reliability based on PageRank and then estimate the truth by sensor ***,this method does not rely on smoothness assumptions or prior knowledge of the ***,we validate the effectiveness and efficiency of the proposed method on real-world and synthetic data sets,respectively.