Affiliation of Author(s):计算机科学与技术学院/人工智能学院/软件学院

Journal:2017 17TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2017)

Key Words:similarity measure time series data mining time series representation

Abstract: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 No.:2375-9232

Translation or Not:no

Date of Publication:2017-01-01

Co-author:张苗苗

Correspondence Author:Pi Dechang