Advanced Analysis and Learning on Temporal Data

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.

• dimensionality reduction
• machine learning
• temporal data mining
• time series analysis
• time series representation
• classification
• fuzzy clustering
• graphical model
• kernel methods
• metric learning
• multivariate time series
• structure learning
• supervised classification
• SVM
• temporal data analysis
• temporal kernel
• temporal metrics
• time series classification
• time series clustering
• unsupervised classification

• Lab. d'Informatique de Grenoble, Université Grenoble, Grenoble, France

  Ahlame Douzal-Chouakria

• Universidade da Coruna, Coruna, Spain

  José A. Vilar

• IRISA, Université de Bretagne-Sud, Vannes, France

  Pierre-François Marteau

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