Fonte: ACM Transactions on Knowledge Discovery from Data - TKDD. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
ABNT
RAKTHANMANON, Thanawin et al. Addressing big data time series: mining trillions of time series subsequences under dynamic time warping. ACM Transactions on Knowledge Discovery from Data - TKDD, v. 7, n. 3, p. 10:1-10:31, 2013Tradução . . Disponível em: https://doi.org/10.1145/2500489. Acesso em: 30 set. 2024.APA
Rakthanmanon, T., Campana, B., Mueen, A., Batista, G. E. de A. P. A., Westover, B., Zhu, Q., et al. (2013). Addressing big data time series: mining trillions of time series subsequences under dynamic time warping. ACM Transactions on Knowledge Discovery from Data - TKDD, 7( 3), 10:1-10:31. doi:10.1145/2500489NLM
Rakthanmanon T, Campana B, Mueen A, Batista GE de APA, Westover B, Zhu Q, Zakaria J, Keogh E. Addressing big data time series: mining trillions of time series subsequences under dynamic time warping [Internet]. ACM Transactions on Knowledge Discovery from Data - TKDD. 2013 ; 7( 3): 10:1-10:31.[citado 2024 set. 30 ] Available from: https://doi.org/10.1145/2500489Vancouver
Rakthanmanon T, Campana B, Mueen A, Batista GE de APA, Westover B, Zhu Q, Zakaria J, Keogh E. Addressing big data time series: mining trillions of time series subsequences under dynamic time warping [Internet]. ACM Transactions on Knowledge Discovery from Data - TKDD. 2013 ; 7( 3): 10:1-10:31.[citado 2024 set. 30 ] Available from: https://doi.org/10.1145/2500489