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Advanced Analytics and Learning on Temporal Data

5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Vincent Lemaire

    1. Orange Labs, Lannion, France

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  2. Simon Malinowski

    1. Inria, University of Rennes, Rennes, France

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  3. Anthony Bagnall

    1. University of East Anglia, Norwich, UK

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  4. Thomas Guyet

    1. Agrocampus Ouest/IRISA, Rennes, France

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  5. Romain Tavenard

    1. CNRS, LETG/IRISA, University of Rennes 2, Rennes, France

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  6. Georgiana Ifrim

    1. University College Dublin, Dublin, Ireland

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12588)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: AALTD 2020.

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Table of contents (15 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Oral Presentation

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. On the Usage and Performance of the Hierarchical Vote Collective of Transformation-Based Ensembles Version 1.0 (HIVE-COTE v1.0)

      • Anthony Bagnall, Michael Flynn, James Large, Jason Lines, Matthew Middlehurst
      Pages 3-18

    3. Ordinal Versus Nominal Time Series Classification

      • David Guijo-Rubio, Pedro Antonio Gutiérrez, Anthony Bagnall, César Hervás-Martínez
      Pages 19-29

    4. Generalized Chronicles for Temporal Sequence Classification

      • Yann Dauxais, Thomas Guyet
      Pages 30-45

    5. Demand Forecasting in the Presence of Privileged Information

      • Mozhdeh Ariannezhad, Sebastian Schelter, Maarten de Rijke
      Pages 46-62

    6. GANNSTER: Graph-Augmented Neural Network Spatio-Temporal Reasoner for Traffic Forecasting

      • Carlos Salort Sánchez, Alexander Wieder, Paolo Sottovia, Stefano Bortoli, Jan Baumbach, Cristian Axenie
      Pages 63-76

    7. A Model-Agnostic Approach to Quantifying the Informativeness of Explanation Methods for Time Series Classification

      • Thu Trang Nguyen, Thach Le Nguyen, Georgiana Ifrim
      Pages 77-94

  3. Poster Presentation

    1. Front Matter

      Pages 95-95
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    2. Temporal Exceptional Model Mining Using Dynamic Bayesian Networks

      • Marcos L. P. Bueno, Arjen Hommersom, Peter J. F. Lucas
      Pages 97-112

    3. “J’veux du Soleil” Towards a Decade of Solar Irradiation Data (La Réunion Island, SW Indian Ocean)

      • Mathieu Delsaut, Patrick Jeanty, Béatrice Morel, Dominique Gay
      Pages 113-121

    4. Visual Analytics for Extracting Trends from Spatio-temporal Data

      • Michiel Dhont, Elena Tsiporkova, Tom Tourwé, Nicolás González-Deleito
      Pages 122-137

    5. Layered Integration Approach for Multi-view Analysis of Temporal Data

      • Michiel Dhont, Elena Tsiporkova, Veselka Boeva
      Pages 138-154

    6. Real-Time Outlier Detection in Time Series Data of Water Sensors

      • L. van de Wiel, D. M. van Es, A. J. Feelders
      Pages 155-170

    7. Lightweight Temporal Self-attention for Classifying Satellite Images Time Series

      • Vivien Sainte Fare Garnot, Loic Landrieu
      Pages 171-181

    8. Creating and Characterising Electricity Load Profiles of Residential Buildings

      • James Fitzpatrick, Paula Carroll, Deepak Ajwani
      Pages 182-203

    9. Trust Assessment on Streaming Data: A Real Time Predictive Approach

      • Tao Peng, Sana Sellami, Omar Boucelma
      Pages 204-219

    10. A Feature Selection Method for Multi-dimension Time-Series Data

      • Bahavathy Kathirgamanathan, Pádraig Cunningham
      Pages 220-231

  4. Back Matter

    Pages 233-233
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Other volumes

  1. Advanced Analytics and Learning on Temporal Data

Keywords

About this book

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.

Editors and Affiliations

  • Orange Labs, Lannion, France

    Vincent Lemaire

  • Inria, University of Rennes, Rennes, France

    Simon Malinowski

  • University of East Anglia, Norwich, UK

    Anthony Bagnall

  • Agrocampus Ouest/IRISA, Rennes, France

    Thomas Guyet

  • CNRS, LETG/IRISA, University of Rennes 2, Rennes, France

    Romain Tavenard

  • University College Dublin, Dublin, Ireland

    Georgiana Ifrim

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