OPR-Miner: Order-Preserving Rule Mining for Time Series

Author:

Wu Youxi1ORCID,Zhao Xiaoqian1ORCID,Li Yan2ORCID,Guo Lei3,Zhu Xingquan4ORCID,Fournier-Viger Philippe5ORCID,Wu Xindong6ORCID

Affiliation:

1. School of Artifical Intelligence, Hebei University of Technology, Tianjin, China

2. School of Economics and Management, Hebei University of Technology, Tianjin, China

3. State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, China

4. Department of Computer & Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA

5. Shenzhen University, Shenzhen, Guangdong Province, China

6. Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education), Hefei University of Technology, Hefei, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Natural Science Foundation of Hebei Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

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1. POCKET: Pruning random convolution kernels for time series classification from a feature selection perspective;Knowledge-Based Systems;2024-09

2. Co-occurrence Order-preserving Pattern Mining with Keypoint Alignment for Time Series;ACM Transactions on Management Information Systems;2024-06-12

3. RNP-Miner: Repetitive Nonoverlapping Sequential Pattern Mining;IEEE Transactions on Knowledge and Data Engineering;2024

4. Early Time Series Anomaly Prediction With Multi-Objective Optimization;IEEE Transactions on Emerging Topics in Computational Intelligence;2024

5. Targeted Mining Precise-Positioning Episode Rules;IEEE Transactions on Emerging Topics in Computational Intelligence;2024

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