计算机与现代化Issue(5)：46-54,9.DOI:10.3969/j.issn.1006-2475.2024.05.009
基于标签传播的轨迹兴趣点挖掘及隐私保护
Trajectory Interest Points Mining Based on Label Propagation and Privacy Protection
摘要
Abstract
With the popularization of global positioning systems and mobile data collection devices,a large amount of trajectory data has been generated.Mining potential information in trajectory data has important practical significance,but there is a risk of privacy information leakage during the mining process.Therefore,we propose a trajectory interest point mining and data privacy protection mechanism based on label propagation.This mechanism preprocesses the original trajectory dataset,performs density based initial clustering,and then uses an improved label propagation algorithm for clustering.This algorithm incorporates multi-dimensional information of trajectory data in the mining process,improving data utilization and accuracy of interest points.At the same time,a differential privacy protection algorithm based on an improved exponential mechanism is proposed,which can effec-tively protect users'privacy information from being leaked.The comparative experimental results show that the proposed method has better performance advantages compared to existing methods,and effectively solves the problem of user privacy information leakage.关键词
数据挖掘/兴趣点/轨迹聚类/差分隐私Key words
data mining/points of interest/trajectory clustering/differential privacy分类
信息技术与安全科学引用本文复制引用
袁红伟,常利军,郝家欢,樊娜,王超,罗闯,张泽辉..基于标签传播的轨迹兴趣点挖掘及隐私保护[J].计算机与现代化,2024,(5):46-54,9.基金项目
陕西省重点研发计划项目(2022GY-039,2022GY-030) （2022GY-039,2022GY-030）
