Discovering All-chain Set with Direction and Graduality Characteristics over Streaming Time Series-Reference-Cited by-同舟云学术

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Discovering All-chain Set with Direction and Graduality Characteristics over Streaming Time Series

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Smartworld, Ubiquitous Intelligence & Computing, Scalable Computing & Communications, Digital Twin, Privacy Computing, Metaverse, Autonomous & Trusted Vehicles (SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta)
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Author:

Wang Shaopeng¹,Feng Chunkai¹

Affiliation:

1. Inner Mongolia University,Engineering Research Center of Ecological Big Data Ministry of Education, Inner Mongolia Engineering Laboratory for Cloud Computing and Service, Inner Mongolia discipline inspection and supervision big data laboratory,Department of Software Engineering,Hohhot,China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Inner Mongolia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10189429/10189430/10189489.pdf?arnumber=10189489

Reference17 articles.

1. Discovering All-Chain Set in Streaming Time Series

2. Time Series Chains: A Novel Tool for Time Series Data Mining

3. Joint Time Series Chain: Detecting Unusual Evolving Trend across Time Series

4. Matrix Profile XXI: A Geometric Approach to Time Series Chains Improves Robustness

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

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