Domain agnostic online semantic segmentation for multi-dimensional time series
Unsupervised semantic segmentation in the time series domain is a much studied problem due to its potential to detect unexpected regularities and regimes in poorly understood data. However, the current techniques have several shortcomings, which have limited the adoption of time series semantic segm...
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Détails bibliographiques
| Publié dans: | Data mining and knowledge discovery. - 2003. - 33(2019), 1 vom: 02., Seite 96-130
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| Auteur principal: |
Gharghabi, Shaghayegh
(Auteur) |
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| Autres auteurs: |
Yeh, Chin-Chia Michael,
Ding, Yifei,
Ding, Wei,
Hibbing, Paul,
LaMunion, Samuel,
Kaplan, Andrew,
Crouter, Scott E,
Keogh, Eamonn |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2019
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| Accès à la collection: | Data mining and knowledge discovery
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| Sujets: | Journal Article
Online algorithms
Semantic segmentation
Time series |
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