Advanced Analytics and Learning on Temporal Data
5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers
Editors: Lemaire, V., Malinowski, S., Bagnall, A., Guyet, Th., Tavenard, R., Ifrim, G. (Eds.)
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- About this book
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This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Ghent, Belgium, in September 2020.
The 15 full papers presented in this book were carefully reviewed and selected from 29 submissions. The selected papers are devoted to topics such as Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Early Classification of Temporal Data; Deep Learning and Learning Representations for Temporal Data; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Space-Temporal Statistical Analysis; Functional Data Analysis Methods; Temporal Data Streams; Interpretable Time-Series Analysis Methods; Dimensionality Reduction, Sparsity, Algorithmic Complexity and Big Data Challenge; and Bio-Informatics, Medical, Energy Consumption, Temporal Data.
- Table of contents (15 chapters)
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On the Usage and Performance of the Hierarchical Vote Collective of Transformation-Based Ensembles Version 1.0 (HIVE-COTE v1.0)
Pages 3-18
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Ordinal Versus Nominal Time Series Classification
Pages 19-29
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Generalized Chronicles for Temporal Sequence Classification
Pages 30-45
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Demand Forecasting in the Presence of Privileged Information
Pages 46-62
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GANNSTER: Graph-Augmented Neural Network Spatio-Temporal Reasoner for Traffic Forecasting
Pages 63-76
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Table of contents (15 chapters)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Advanced Analytics and Learning on Temporal Data
- Book Subtitle
- 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers
- Editors
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- Vincent Lemaire
- Simon Malinowski
- Anthony Bagnall
- Thomas Guyet
- Romain Tavenard
- Georgiana Ifrim
- Series Title
- Lecture Notes in Artificial Intelligence
- Series Volume
- 12588
- Copyright
- 2020
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer Nature Switzerland AG
- eBook ISBN
- 978-3-030-65742-0
- DOI
- 10.1007/978-3-030-65742-0
- Softcover ISBN
- 978-3-030-65741-3
- Edition Number
- 1
- Number of Pages
- X, 233
- Number of Illustrations
- 21 b/w illustrations, 67 illustrations in colour
- Topics
