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Lemire, Daniel (2009). Faster retrieval with a two-pass dynamic-time-warping lower bound. Pattern Recognition, 42 (9). https://doi.org/10.1016/j.patcog.2008.11.030
Fichier(s) associé(s) à ce document :| PDF - 0811.3301v2.pdf |
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| Catégorie de document : | Articles de revues |
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| Évaluation par un comité de lecture : | Oui |
| Étape de publication : | Publié |
| Résumé : | The Dynamic Time Warping (DTW) is a popular similarity measure between time series. The DTW fails to satisfy the triangle inequality and its computation requires quadratic time. Hence, to find closest neighbors quickly, we use bounding techniques. We can avoid most DTW computations with an inexpensive lower bound (LB Keogh). We compare LB Keogh with a tighter lower bound (LB Improved). We find that LB Improved-based search is faster. As an example, our approach is 2-3 times faster over random-walk and shape time series. |
| Adresse de la version officielle : | http://www.sciencedirect.com/science/article/pii/S... |
| Déposant: | Lemire, Daniel |
| Responsable : | Daniel Lemire |
| Dépôt : | 22 juill. 2014 21:51 |
| Dernière modification : | 16 juill. 2015 00:47 |
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