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Dynamic Sub-Sequence Warping: A Representation-Based Similarity Measure for Long Time Series
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Zhou Zhou1, Gang Huang2, Laura Dawkins3
Data Science and Engineering | 2026, 11(1) : 260 - 274
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Data Science and Engineering | 2026, 11(1): 260-274
RESEARCH PAPERS
Dynamic Sub-Sequence Warping: A Representation-Based Similarity Measure for Long Time Series
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Zhou Zhou1, Gang Huang2, Laura Dawkins3
Affiliations
  • 1Department of Engineering, University of Exeter, Exeter EX4 4QF, UK
  • 2College of Electrical Engineering, Zhejiang University, Hangzhou 310027, People's Republic of China
  • 3Met Office, Fitzroy Road, Exeter EX1 3PB, UK
Published: 2026-03-01 doi: 10.1007/s41019-025-00331-9
Outline
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Dynamic time warping (DTW), a typical elastic similarity measure that compares one-to-many points, has been proven effective for various time-series data mining tasks. However, it requires a quadratic time complexity O(n2) proportional to the length of time-series data, which undermines its applications involving long time series. In this paper, a representation-based similarity measure called Dynamic Sub-Sequence Warping (DSSW) is proposed. Instead of working on the raw data directly, we perform data representation to extract the distributional features of time series. Then, the similarity between two time series is measured by aligning the corresponding sub-sequences composed of the extracted features. We evaluate the proposed method through a supervised learning task on extensive real-world datasets. The results show that DSSW outperforms the prevalent DTW-based methods in terms of precision, and achieves one order of magnitude faster execution time on average compared with DTW.

Time series  /  Similarity measure  /  Representation  /  Dynamic time warping
Zhou Zhou, Gang Huang, Laura Dawkins. Dynamic Sub-Sequence Warping: A Representation-Based Similarity Measure for Long Time Series[J]. Data Science and Engineering, 2026 , 11 (1) : 260 -274 . DOI: 10.1007/s41019-025-00331-9
  • Youth Talent Program of Sci-Tech Think Tank(XMSB20240710087)
  • National Key Research and Development Program of China(2023YFB3107603)
Year 2026 volume 11 Issue 1
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Article Info
doi: 10.1007/s41019-025-00331-9
  • Receive Date:2025-04-23
  • Online Date:2026-08-06
  • Published:2026-03-01
Article Data
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History
  • Received:2025-04-23
  • Revised:2025-11-03
  • Accepted:2025-11-25
Funding
Youth Talent Program of Sci-Tech Think Tank(XMSB20240710087)
National Key Research and Development Program of China(2023YFB3107603)
Affiliations
    1Department of Engineering, University of Exeter, Exeter EX4 4QF, UK
    2College of Electrical Engineering, Zhejiang University, Hangzhou 310027, People's Republic of China
    3Met Office, Fitzroy Road, Exeter EX1 3PB, UK

Corresponding:

Gang Huang 
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