的个人主页 http://faculty.nuaa.edu.cn/pdc/zh_CN/index.htm
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所属单位:计算机科学与技术学院/人工智能学院/软件学院
发表刊物:2017 17TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2017)
关键字:similarity measure time series data mining time series representation
摘要:Similarity measure is a central problem in time series data mining. Although most approaches to this problem have been developed, with the rapid growth of the amount of data, we believe there is a challenging demand for supporting similarity measure in a fast and accurate way. In this paper, we propose a new time series representation model and a corresponding similarity measure, which is able to capture the main trends of time series and fulfill fast similarity detection. We compare the new method with state-of-the-art time series similarity methods and dimension-reduction techniques to indicate its superiority. Experiment results demonstrate the new method is able to support both fast and accurate similarity measure.
ISSN号:2375-9232
是否译文:否
发表时间:2017-01-01
合写作者:张苗苗
通讯作者:皮德常