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Discovery Science

21st International Conference, DS 2018, Limassol, Cyprus, October 29–31, 2018, Proceedings

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Larisa Soldatova

    1. Goldsmiths University of London, London, UK

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  2. Joaquin Vanschoren

    1. Eindhoven University of Technology, Eindhoven, The Netherlands

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  3. George Papadopoulos

    1. University of Cyprus, Nicosia, Cyprus

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  4. Michelangelo Ceci

    1. Università degli Studi di Bari Aldo Moro, Bari, Italy

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11198)

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

Included in the following conference series:

Conference proceedings info: DS 2018.

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Table of contents (30 papers)

  1. Front Matter

    Pages I-XXI
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  2. Classification

    1. Front Matter

      Pages 1-1
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    2. Addressing Local Class Imbalance in Balanced Datasets with Dynamic Impurity Decision Trees

      • Andriy Mulyar, Bartosz Krawczyk
      Pages 3-17

    3. Barricaded Boundary Minority Oversampling LS-SVM for a Biased Binary Classification

      • Hmayag Partamian, Yara Rizk, Mariette Awad
      Pages 18-32

    4. Dynamic Classifier Chain with Random Decision Trees

      • Moritz Kulessa, Eneldo Loza Mencía
      Pages 33-50

    5. Feature Ranking with Relief for Multi-label Classification: Does Distance Matter?

      • Matej Petković, Dragi Kocev, Sašo Džeroski
      Pages 51-65

    6. Finding Probabilistic Rule Lists using the Minimum Description Length Principle

      • John O. R. Aoga, Tias Guns, Siegfried Nijssen, Pierre Schaus
      Pages 66-82

    7. Leveraging Reproduction-Error Representations for Multi-Instance Classification

      • Sebastian Kauschke, Max Mühlhäuser, Johannes Fürnkranz
      Pages 83-95

  3. Meta-Learning

    1. Front Matter

      Pages 97-97
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    2. Class Balanced Similarity-Based Instance Transfer Learning for Botnet Family Classification

      • Basil Alothman, Helge Janicke, Suleiman Y. Yerima
      Pages 99-113

    3. CF4CF-META: Hybrid Collaborative Filtering Algorithm Selection Framework

      • Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho
      Pages 114-128

    4. MetaUtil: Meta Learning for Utility Maximization in Regression

      • Paula Branco, Luís Torgo, Rita P. Ribeiro
      Pages 129-143

    5. Predicting Rice Phenotypes with Meta-learning

      • Oghenejokpeme I. Orhobor, Nickolai N. Alexandrov, Ross D. King
      Pages 144-158

  4. Reinforcement Learning

    1. Front Matter

      Pages 159-159
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    2. Preference-Based Reinforcement Learning Using Dyad Ranking

      • Dirk Schäfer, Eyke Hüllermeier
      Pages 161-175

  5. Streams and Time Series

    1. Front Matter

      Pages 177-177
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    2. COBRASTS: A New Approach to Semi-supervised Clustering of Time Series

      • Toon Van Craenendonck, Wannes Meert, Sebastijan Dumančić, Hendrik Blockeel
      Pages 179-193

    3. Exploiting the Web for Semantic Change Detection

      • Pierpaolo Basile, Barbara McGillivray
      Pages 194-208

    4. Online Gradient Boosting for Incremental Recommender Systems

      • João Vinagre, Alípio Mário Jorge, João Gama
      Pages 209-223

    5. Selection of Relevant and Non-Redundant Multivariate Ordinal Patterns for Time Series Classification

      • Arvind Kumar Shekar, Marcus Pappik, Patricia Iglesias Sánchez, Emmanuel Müller
      Pages 224-240
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Other volumes

  1. Discovery Science

Keywords

About this book

This book constitutes the proceedings of the 21st International Conference on Discovery Science, DS 2018, held in Limassol, Cyprus, in October 2018, co-located with the International Symposium on Methodologies for Intelligent Systems, ISMIS 2018.

The 30 full papers presented together with 5 abstracts of invited talks in this volume were carefully reviewed and selected from 71 submissions. The scope of the conference includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, big data analysis as well as their application in various scientific domains. The papers are organized in the following topical sections: Classification; meta-learning; reinforcement learning; streams and time series; subgroup and subgraph discovery; text mining; and applications.

Editors and Affiliations

  • Goldsmiths University of London, London, UK

    Larisa Soldatova

  • Eindhoven University of Technology, Eindhoven, The Netherlands

    Joaquin Vanschoren

  • University of Cyprus, Nicosia, Cyprus

    George Papadopoulos

  • Università degli Studi di Bari Aldo Moro, Bari, Italy

    Michelangelo Ceci

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