Data mining a trillion time series subsequences under dynamic time warping (2013)
- Authors:
- Rakthanmanon, Thanawin
- Campana, Bilson - University of California (UC)
- Mueen, Abdullah - University of California (UC)
- Batista, Gustavo Enrique de Almeida Prado Alves
- Westover, Brandon
- Qiang, Zhu - University of California (UC)
- Zakaria, Jesin - University of California (UC)
- Keogh, Eamonn - University of California (UC)
- Autor USP: BATISTA, GUSTAVO ENRIQUE DE ALMEIDA PRADO ALVES - ICMC
- Unidade: ICMC
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Publisher: AAAI Press
- Publisher place: Menlo Park
- Date published: 2013
- ISBN: 9781577356332
- Source:
- Título: Proceedings
- Conference titles: International Joint Conference on Artificial Intelligence - IJCAI
-
ABNT
RAKTHANMANON, Thanawin et al. Data mining a trillion time series subsequences under dynamic time warping. 2013, Anais.. Menlo Park: AAAI Press, 2013. Disponível em: http://ijcai.org/papers13/Papers/IJCAI13-454.pdf. Acesso em: 27 dez. 2025. -
APA
Rakthanmanon, T., Campana, B., Mueen, A., Batista, G. E. de A. P. A., Westover, B., Qiang, Z., et al. (2013). Data mining a trillion time series subsequences under dynamic time warping. In Proceedings. Menlo Park: AAAI Press. Recuperado de http://ijcai.org/papers13/Papers/IJCAI13-454.pdf -
NLM
Rakthanmanon T, Campana B, Mueen A, Batista GE de APA, Westover B, Qiang Z, Zakaria J, Keogh E. Data mining a trillion time series subsequences under dynamic time warping [Internet]. Proceedings. 2013 ;[citado 2025 dez. 27 ] Available from: http://ijcai.org/papers13/Papers/IJCAI13-454.pdf -
Vancouver
Rakthanmanon T, Campana B, Mueen A, Batista GE de APA, Westover B, Qiang Z, Zakaria J, Keogh E. Data mining a trillion time series subsequences under dynamic time warping [Internet]. Proceedings. 2013 ;[citado 2025 dez. 27 ] Available from: http://ijcai.org/papers13/Papers/IJCAI13-454.pdf - Contribuições em mineração de dados temporais e classes desbalanceadas
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- Distância invariante à complexidade baseada em dimensão fractal para classificação de séries temporais
- A novel approximation to dynamic time warping allows anytime clustering of massive time series datasets
- An empirical comparison of dissimilarity measures for time series classification
- Evaluation of statistical and machine learning models for time series prediction: identifying the state-of-the-art and the best conditions for the use of each model
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