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Discovery Science

26th International Conference, DS 2023, Porto, Portugal, October 9–11, 2023, Proceedings

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Albert Bifet

    1. Waikato University, Hamilton, New Zealand

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  2. Ana Carolina Lorena

    1. Aeronautics Institute of Technology, São José dos Campos, Brazil

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  3. Rita P. Ribeiro

    1. University of Porto, Porto, Portugal

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  4. João Gama

    1. University of Porto, Porto, Portugal

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  5. Pedro H. Abreu

    1. University of Coimbra, Coimbra, Portugal

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14276)

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

Included in the following conference series:

Conference proceedings info: DS 2023.

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Table of contents (47 papers)

  1. Front Matter

    Pages i-xxv
    Download chapter PDF

  2. Machine Learning Methods and Applications

    1. Front Matter

      Pages 1-1
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    2. Ensembles of Classifiers and Quantifiers with Data Fusion for Quantification Learning

      • Adriane B. S. Serapião, Zahra Donyavi, Gustavo Batista
      Pages 3-17

    3. Exploring the Intricacies of Neural Network Optimization

      • Rafael Teixeira, Mário Antunes, Rúben Sobral, João Martins, Diogo Gomes, Rui L. Aguiar
      Pages 18-32

    4. Exploring the Reduction of Configuration Spaces of Workflows

      • Fernando Freitas, Pavel Brazdil, Carlos Soares
      Pages 33-47

    5. iSOUP-SymRF: Symbolic Feature Ranking with Random Forests in Online Multi-target Regression

      • Aljaž Osojnik, Panče Panov, Sašo Džeroski
      Pages 48-63Open Access

    6. Knowledge-Guided Additive Modeling for Supervised Regression

      • Yann Claes, Vân Anh Huynh-Thu, Pierre Geurts
      Pages 64-78

  3. Natural Language Processing and Social Media Analysis

    1. Front Matter

      Pages 79-79
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    2. Audience Prediction for Game Streaming Channels Based on Vectorization of User Comments

      • Takayasu Fushimi, Kazuki Sakamoto
      Pages 81-95

    3. From Tweets to Stance: An Unsupervised Framework for User Stance Detection on Twitter

      • Margherita Gambini, Caterina Senette, Tiziano Fagni, Maurizio Tesconi
      Pages 96-110

    4. GLORIA: A Graph Convolutional Network-Based Approach for Review Spam Detection

      • Giuseppina Andresini, Annalisa Appice, Roberto Gasbarro, Donato Malerba
      Pages 111-125

    5. Unmasking COVID-19 False Information on Twitter: A Topic-Based Approach with BERT

      • Riccardo Cantini, Cristian Cosentino, Irene Kilanioti, Fabrizio Marozzo, Domenico Talia
      Pages 126-140

    6. Unsupervised Key-Phrase Extraction from Long Texts with Multilingual Sentence Transformers

      • Hélder Dias, Artur Guimarães, Bruno Martins, Mathieu Roche
      Pages 141-155

  4. Interpretability and Explainability in AI

    1. Front Matter

      Pages 157-157
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    2. Counterfactuals Explanations for Outliers via Subspaces Density Contrastive Loss

      • Fabrizio Angiulli, Fabio Fassetti, Simona Nisticó, Luigi Palopoli
      Pages 159-173

    3. Explainable Spatio-Temporal Graph Modeling

      • Massimiliano Altieri, Michelangelo Ceci, Roberto Corizzo
      Pages 174-188

    4. Probabilistic Scoring Lists for Interpretable Machine Learning

      • Jonas Hanselle, Johannes Fürnkranz, Eyke Hüllermeier
      Pages 189-203

    5. Refining Temporal Visualizations Using the Directional Coherence Loss

      • Pavlin G. Poličar, Blaž Zupan
      Pages 204-215Open Access

    6. Semantic Enrichment of Explanations of AI Models for Healthcare

      • Luca Corbucci, Anna Monreale, Cecilia Panigutti, Michela Natilli, Simona Smiraglio, Dino Pedreschi
      Pages 216-229

    7. Text to Time Series Representations: Towards Interpretable Predictive Models

      • Mattia Poggioli, Francesco Spinnato, Riccardo Guidotti
      Pages 230-245
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  1. Discovery Science

Keywords

About this book

This book constitutes the proceedings of the 26th International Conference on Discovery Science, DS 2023, which took place in Porto, Portugal, in October 2023. The 37 full papers and 10 short papers presented in this volume were carefully reviewed and selected from 133 submissions. They were organized in topical sections as follows: Machine learning methods and applications; natural language processing and social media analysis; interpretability and explainability in AI; data analysis and optimization; fairness, privacy and security in AI; control and spatio-temporal modeling; graph theory and network analysis; time series and forecasting; healthcare and biological data analysis; anomaly, outlier and novelty detection.

Editors and Affiliations

  • Waikato University, Hamilton, New Zealand

    Albert Bifet

  • Aeronautics Institute of Technology, São José dos Campos, Brazil

    Ana Carolina Lorena

  • University of Porto, Porto, Portugal

    Rita P. Ribeiro, João Gama

  • University of Coimbra, Coimbra, Portugal

    Pedro H. Abreu

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