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一种基于关键点的时间序列聚类算法
引用本文:谢福鼎,李迎,孙岩,张永.一种基于关键点的时间序列聚类算法[J].计算机科学,2012,39(3):160-162.
作者姓名:谢福鼎  李迎  孙岩  张永
作者单位:(辽宁师范大学城市与环境学院 大连116029);(辽宁师范大学计算机与信息技术学院 大连116081)
基金项目:国家自然科学基金(10771092);辽宁省博士启动基金(20081079)资助
摘    要:隐私保护数据挖掘是在不精确访问原始数据的基础上,挖掘出准确的规则和知识。针对分布式环境下聚类挖掘算法的隐私保护问题,提出了一种基于完全同态加密的分布式聚类挖掘算法(FHE-DK-MEANS算法)。理论分析和实验结果表明,FHE-DK-MEANS算法不仅具有很好的数据隐私性,而且保持了聚类精度。

关 键 词:数据挖掘  隐私保护  聚类  分布式数据

Cluster Algorithm for Time Series Based on Key Points
XIE Fu-ding,LI Ying,SUN Yan,ZHANG Yong.Cluster Algorithm for Time Series Based on Key Points[J].Computer Science,2012,39(3):160-162.
Authors:XIE Fu-ding  LI Ying  SUN Yan  ZHANG Yong
Affiliation:(School of Urban and Environmental Science,Liaoning formal University,Dalian 116029,China);(Department of Computer and Science Technology, Liaoning formal University, Dalian 116081, China)
Abstract:Based on key point technology, a new method for time series cluster was proposed. hhe key points for each time series were first found, and then the complex network was constructed by calculating the similarity between key point series after they were ectuidimensional. At last, the clustering time series were implemented by partitioning the complex network into communities. hhe experimental results show that the dimensions of time series and the consumplion of computing time can be effectively reduced by the proposal. Furthermore, the desired cluster result is obtained when applying this method to cluster some practical data.
Keywords:Time series  Reduction dimension  Key point  Complex network  Cluster
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