Introducing time series chains: a new primitive for time series data mining

Yan Zhu; Makoto Imamura; Daniel Nikovski; Eamonn Keogh

doi:10.1007/s10115-018-1224-8

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JOURNAL ARTICLE

Introducing time series chains: a new primitive for time series data mining

Yan Zhu Makoto Imamura Daniel Nikovski Eamonn Keogh

Year: 2018 Journal: Knowledge and Information Systems Vol: 60 (2)Pages: 1135-1161 Publisher: Springer Science+Business Media

DOI: 10.1007/s10115-018-1224-8

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Keywords:

Series (stratigraphy) Computer science Time series Scalability Subsequence Data mining Longest common subsequence problem Analytics Set (abstract data type) Theoretical computer science Algorithm Artificial intelligence Machine learning Mathematics Database

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Time Series Analysis and Forecasting

Physical Sciences → Computer Science → Signal Processing

Complex Systems and Time Series Analysis

Social Sciences → Economics, Econometrics and Finance → Economics and Econometrics

Data Stream Mining Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Introducing time series chains: a new primitive for time series data mining

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