A novel approximation to dynamic time warping allows anytime clustering of massive time series datasets (2012)
- Authors:
- Autor USP: BATISTA, GUSTAVO ENRIQUE DE ALMEIDA PRADO ALVES - ICMC
- Unidade: ICMC
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Publisher: SIAM
- Publisher place: Philadelphia
- Date published: 2012
- ISBN: 9781611972320
- Source:
- Título: Proceedings
- Conference titles: SIAM International Conference on Data Mining
-
ABNT
QIANG, Zhu et al. A novel approximation to dynamic time warping allows anytime clustering of massive time series datasets. 2012, Anais.. Philadelphia: SIAM, 2012. Disponível em: http://siam.omnibooksonline.com/2012datamining/. Acesso em: 24 fev. 2026. -
APA
Qiang, Z., Batista, G. E. de A. P. A., Rakthanmanon, T., & Keogh, E. (2012). A novel approximation to dynamic time warping allows anytime clustering of massive time series datasets. In Proceedings. Philadelphia: SIAM. Recuperado de http://siam.omnibooksonline.com/2012datamining/ -
NLM
Qiang Z, Batista GE de APA, Rakthanmanon T, Keogh E. A novel approximation to dynamic time warping allows anytime clustering of massive time series datasets [Internet]. Proceedings. 2012 ;[citado 2026 fev. 24 ] Available from: http://siam.omnibooksonline.com/2012datamining/ -
Vancouver
Qiang Z, Batista GE de APA, Rakthanmanon T, Keogh E. A novel approximation to dynamic time warping allows anytime clustering of massive time series datasets [Internet]. Proceedings. 2012 ;[citado 2026 fev. 24 ] Available from: http://siam.omnibooksonline.com/2012datamining/ - Time series classification with motifs and characteristics
- Uma avaliação sobre a identificação de Motifs em séries temporais
- A fuzzy classifier for data streams with infinitely delayed labels
- Fast unsupervised online drift detection using incremental Kolmogorov-Smirnov test
- A complexity-invariant measure based on fractal dimension for time series classification
- Towards automatic classification on flying insects using inexpensive sensors
- Data mining a trillion time series subsequences under dynamic time warping
- Distância invariante à complexidade baseada em dimensão fractal para classificação de séries temporais
- Unsupervised context switch for classification tasks on data streams with recurrent concepts
- On the need of class ratio insensitive drift tests for data streams
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