Advanced Analysis and Learning on Temporal Data
First ECML PKDD Workshop, AALTD 2015, Porto, Portugal, September 11, 2015, Revised Selected Papers
Editors: Douzal-Chouakria, Ahlame, Vilar, José A., Marteau, Pierre-François (Eds.)
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- About this book
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This book constitutes the refereed proceedings of the First ECML PKDD Workshop, AALTD 2015, held in Porto, Portugal, in September 2016.
The 11 full papers presented were carefully reviewed and selected from 22 submissions. The first part focuses on learning new representations and embeddings for time series classification, clustering or for dimensionality reduction. The second part presents approaches on classification and clustering with challenging applications on medicine or earth observation data. These works show different ways to consider temporal dependency in clustering or classification processes. The last part of the book is dedicated to metric learning and time series comparison, it addresses the problem of speeding-up the dynamic time warping or dealing with multi-modal and multi-scale metric learning for time series classification and clustering.
- Table of contents (11 chapters)
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Symbolic Representation of Time Series: A Hierarchical Coclustering Formalization
Pages 3-16
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Dense Bag-of-Temporal-SIFT-Words for Time Series Classification
Pages 17-30
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Dimension Reduction in Dissimilarity Spaces for Time Series Classification
Pages 31-46
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Fuzzy Clustering of Series Using Quantile Autocovariances
Pages 49-64
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A Reservoir Computing Approach for Balance Assessment
Pages 65-77
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Table of contents (11 chapters)
- Download Preface 1 PDF (53 KB)
- Download Sample pages 2 PDF (617 KB)
- Download Table of contents PDF (55.8 KB)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Advanced Analysis and Learning on Temporal Data
- Book Subtitle
- First ECML PKDD Workshop, AALTD 2015, Porto, Portugal, September 11, 2015, Revised Selected Papers
- Editors
-
- Ahlame Douzal-Chouakria
- José A. Vilar
- Pierre-François Marteau
- Series Title
- Lecture Notes in Artificial Intelligence
- Series Volume
- 9785
- Copyright
- 2016
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing Switzerland
- eBook ISBN
- 978-3-319-44412-3
- DOI
- 10.1007/978-3-319-44412-3
- Softcover ISBN
- 978-3-319-44411-6
- Edition Number
- 1
- Number of Pages
- X, 173
- Number of Illustrations
- 64 b/w illustrations
- Topics
