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Advanced Analytics and Learning on Temporal Data

8th ECML PKDD Workshop, AALTD 2023, Turin, Italy, September 18–22, 2023, Revised Selected Papers

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Georgiana Ifrim

    1. University College Dublin, Dublin, Ireland

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  2. Romain Tavenard

    1. University of Rennes 2, Rennes, France

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  3. Anthony Bagnall

    1. University of Southampton, Southampton, UK

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  4. Patrick Schaefer

    1. Humboldt University of Berlin, Berlin, Germany

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  5. Simon Malinowski

    1. University of Rennes, Rennes, France

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  6. Thomas Guyet

    1. Claude Bernard University Lyon 1, Villeurbanne, France

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  7. Vincent Lemaire

    1. Orange Innovation, Lannion, France

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14343)

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

Included in the following conference series:

Conference proceedings info: AALTD 2023.

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Table of contents (19 papers)

  1. Front Matter

    Pages i-xiii
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  2. Human Activity Segmentation Challenge

    1. Front Matter

      Pages 1-1
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    2. Human Activity Segmentation Challenge @ ECML/PKDD’23

      • Arik Ermshaus, Patrick Schäfer, Anthony Bagnall, Thomas Guyet, Georgiana Ifrim, Vincent Lemaire et al.
      Pages 3-13

    3. Change Points Detection in Multivariate Signal Applied to Human Activity Segmentation

      • Grzegorz Harańczyk
      Pages 14-24

    4. Change Point Detection via Synthetic Signals

      • Ting-Ji Huang, Qi-Le Zhou, Han-Jia Ye, De-Chuan Zhan
      Pages 25-35

  3. Oral Presentation

    1. Front Matter

      Pages 37-37
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    2. Clustering Time Series with k-Medoids Based Algorithms

      • Christopher Holder, David Guijo-Rubio, Anthony Bagnall
      Pages 39-55

    3. Explainable Parallel RCNN with Novel Feature Representation for Time Series Forecasting

      • Jimeng Shi, Rukmangadh Myana, Vitalii Stebliankin, Azam Shirali, Giri Narasimhan
      Pages 56-75

    4. RED CoMETS: An Ensemble Classifier for Symbolically Represented Multivariate Time Series

      • Luca A. Bennett, Zahraa S. Abdallah
      Pages 76-91

    5. Deep Long Term Prediction for Semantic Segmentation in Autonomous Driving

      • Bidya Dash, Shreyas Bilagi, Jasmin Breitenstein, Volker Schomerus, Thorsten Bagdonat, Tim Fingscheidt
      Pages 92-112

    6. Extracting Features from Random Subseries: A Hybrid Pipeline for Time Series Classification and Extrinsic Regression

      • Matthew Middlehurst, Anthony Bagnall
      Pages 113-126

    7. ShapeDBA: Generating Effective Time Series Prototypes Using ShapeDTW Barycenter Averaging

      • Ali Ismail-Fawaz, Hassan Ismail Fawaz, François Petitjean, Maxime Devanne, Jonathan Weber, Stefano Berretti et al.
      Pages 127-142

  4. Poster Presentation

    1. Front Matter

      Pages 143-143
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    2. Temporal Performance Prediction for Deep Convolutional Long Short-Term Memory Networks

      • Laura Fieback, Bidya Dash, Jakob Spiegelberg, Hanno Gottschalk
      Pages 145-158

    3. Evaluating Explanation Methods for Multivariate Time Series Classification

      • Davide Italo Serramazza, Thu Trang Nguyen, Thach Le Nguyen, Georgiana Ifrim
      Pages 159-175

    4. tGLAD: A Sparse Graph Recovery Based Approach for Multivariate Time Series Segmentation

      • Shima Imani, Harsh Shrivastava
      Pages 176-189

    5. Designing a New Search Space for Multivariate Time-Series Neural Architecture Search

      • Christopher MacKinnon, Robert Atkinson
      Pages 190-204

    6. Back to Basics: A Sanity Check on Modern Time Series Classification Algorithms

      • Bhaskar Dhariyal, Thach Le Nguyen, Georgiana Ifrim
      Pages 205-229

    7. Do Cows Have Fingerprints? Using Time Series Techniques and Milk Flow Profiles to Characterise Cow Milking Performance and Detect Health Issues

      • Changhong Jin, John Upton, Brian Mac Namee
      Pages 230-242

    8. Exploiting Context and Attention Using Recurrent Neural Network for Sensor Time Series Prediction

      • Rashmi Dutta Baruah, Mario Muñoz-Organero
      Pages 243-259
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  1. Advanced Analytics and Learning on Temporal Data

Keywords

About this book

This volume LNCS 14343 constitutes the refereed proceedings of the 8th ECML PKDD Workshop, AALTD 2023, in Turin, Italy, in September 2023.  

The 20 full papers were carefully reviewed and selected from 28 submissions. They are organized in the following topical section as follows: Machine Learning; Data Mining; Pattern Analysis; Statistics to Share their Challenges and Advances in Temporal Data Analysis.

 


Editors and Affiliations

  • University College Dublin, Dublin, Ireland

    Georgiana Ifrim

  • University of Rennes 2, Rennes, France

    Romain Tavenard

  • University of Southampton, Southampton, UK

    Anthony Bagnall

  • Humboldt University of Berlin, Berlin, Germany

    Patrick Schaefer

  • University of Rennes, Rennes, France

    Simon Malinowski

  • Claude Bernard University Lyon 1, Villeurbanne, France

    Thomas Guyet

  • Orange Innovation, Lannion, France

    Vincent Lemaire

Bibliographic Information

  • Book Title: Advanced Analytics and Learning on Temporal Data

  • Book Subtitle: 8th ECML PKDD Workshop, AALTD 2023, Turin, Italy, September 18–22, 2023, Revised Selected Papers

  • Editors: Georgiana Ifrim, Romain Tavenard, Anthony Bagnall, Patrick Schaefer, Simon Malinowski, Thomas Guyet, Vincent Lemaire

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-49896-1

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

  • Softcover ISBN: 978-3-031-49895-4Published: 20 December 2023

  • eBook ISBN: 978-3-031-49896-1Published: 19 December 2023

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XIII, 308

  • Number of Illustrations: 23 b/w illustrations, 90 illustrations in colour

  • Topics: Artificial Intelligence

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