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浙江大学学报(工学版)
计算机技术、信息工程     
基于两级过滤的时间序列近似查询
蔡青林,陈岭,梅寒蕾,孙建伶
浙江大学 计算机科学与技术学院,浙江 杭州 310027
Two-step filtering based time series similarity search
CAI Qing lin, CHEN Ling, MEI Han lei, SUN Jian ling
College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
 全文: PDF(926 KB)   HTML
摘要:

针对现有的近似查询模型对查询精度的可控性较差,后续处理效率较低的问题,提出基于两级过滤的查询模型.通过采用不同粒度的SAX表示方法提取时间序列的字符型特征向量,可以将高维的时间序列映射到低维的特征空间;将不同粒度的特征向量以向量近似文件(VA-File)的结构进行存储,有效引入了倒排索引.在查询过程中,设计了启发式的查询过滤算法,根据粗粒度特征向量查询细粒度特征向量,实现第一级过滤;针对VA-File设计了高效的边界剪枝算法,实现第二级过滤.模型基于多粒度的SAX特征向量进行构建,可以对查询精度进行有效控制;在第二级过滤中采用的边界剪枝算法可以有效地提高后续处理的执行效率.实验结果表明,提出的查询模型具有较高的性能,对时间序列长度、kNN查询规模及数据集规模具有稳定的扩展性.

Abstract:

A two-step filtering based search model was proposed in order to solve the problms that existing approximated search models have the poor controllability on the accuracy and have the low efficiency at the post-processing step. The symbolic aggregate approximation (SAX) method was employed to extract the symbolic feature vectors from time series. The high-dimensional time series was projected into the low-dimensional feature space. The symbolic feature vectors were saved as the form of vector approximation file (VA-File), and the efficient inverted index was introduced. A heuristic query and filtering algorithm was proposed at the procedure of searching in order to perform the first filtering, and an efficient boundary pruning method was proposed over the VA-File to reach the second filtering. The model can effectively control the search accuracy by the SAX feature vectors with multiple precision. Experimental results show that the proposed model has the efficient performance and the robust scalability on the series length, the kNN query scale and the dataset size.

出版日期: 2016-07-23
:  TP 39  
基金资助:

中国工业和信息化部“核高基”重大专项基金资助项目(2010ZX01042-002-003-001);中国工程科技知识中心基金资助项目(CKCEST-2014-1-5);国家自然科学基金资助项目(61332017).

通讯作者: 陈岭,男,副教授. ORCID:0000-0003-1934-5992.     E-mail: lingchen@zju.edu.cn
作者简介: 蔡青林(1987-),男,博士生,从事数据挖掘、信息检索、模式识别的研究. ORCID:0000-0001-5219-7771. E-mail: qlcai@zju.edu.cn
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引用本文:

蔡青林,陈岭,梅寒蕾,孙建伶. 基于两级过滤的时间序列近似查询[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008-973X.2016.07.010.

CAI Qing lin, CHEN Ling, MEI Han lei, SUN Jian ling. Two-step filtering based time series similarity search. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008-973X.2016.07.010.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2016.07.010        http://www.zjujournals.com/eng/CN/Y2016/V50/I7/1290

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