Results 271 to 280 of about 36,481,271 (303)

Mining from Time Series Human Movement Data

2006 IEEE International Conference on Systems, Man and Cybernetics, 2006
Human motion not only contains a wealth of information about actions and intentions, but also about identity and personal attributes of the moving person. Research also indicates that there are positive relationships between the health of a person and their pattern of motion.
Chiu-Che Tseng, Diane J. Cook
openaire   +1 more source

A Data Mining Technique for Time Series Data

2022
Yoshinori Satoh, Akira Maeda
openaire   +2 more sources

On-line and dynamic time warping for time series data mining

International Journal of Machine Learning and Cybernetics, 2014
Dynamic time warping (DTW) is a robust method used to measure similarity of time series. To speed up the calculation of DTW, an on-line and dynamic time warping is proposed to the field of time series data mining. A sliding window is used to segment a long time series into several short subsequences, and an efficient DTW proposed to measure the ...
openaire   +2 more sources

Data Mining on Extremely Long Time-Series

2021 International Conference on Data Mining Workshops (ICDMW), 2021
Scott Simmons, Louis Jarvis, David Dempsey, Andreas W. Kempa-Liehr   +3 more
openaire   +2 more sources

Financial Time Series Data Mining

2009
Movement of stocks in the financial market is a typical example of financial time series data. It is generally believed that past performance of a stock can indicate its future trend and so stock trend analysis is a popular activity in the financial community.
openaire   +1 more source

OPP-Miner: Order-Preserving Sequential Pattern Mining for Time Series

IEEE Transactions on Cybernetics, 2023
Youxi Wu, Qian Hu, Xindong Wu
exaly  

Time works well: Dynamic time warping based on time weighting for time series data mining

Information Sciences, 2021
Hailin Li
exaly  

Financial Time Series Data Mining

2010
2nd ed.
Law, YK, Leung, ACM, Bose, I
openaire   +1 more source

Mining deviants in time series data streams

Proceedings. 16th International Conference on Scientific and Statistical Database Management, 2004., 2004
S. Muthukrishnan 0001, Rahul Shah 0001, Jeffrey Scott Vitter   +2 more
openaire   +2 more sources

Tracking vegetation degradation and recovery in multiple mining areas in Beijing, China, based on time-series Landsat imagery

GIScience and Remote Sensing, 2021
Yinghai Ke, Lin Zhu
exaly