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Discovery Science [E-Book] : 24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021, Proceedings / edited by Carlos Soares, Luis Torgo.

This book constitutes the proceedings of the 24th International Conference on Discovery Science, DS 2021, which took place virtually during October 11-13, 2021. The 36 papers presented in this volume were carefully reviewed and selected from 76 submissions. The contributions were organized in topica...

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Soares, Carlos, editor
Torgo, Luis, editor
1st edition 2021.
Cham : Springer, 2021
XII, 474 pages 26 illustrations (online resource)
englisch
9783030889425
10.1007/978-3-030-88942-5
Lecture Notes in Artificial Intelligence ; 12986
Lecture Notes in Computer Science
Application software.
Artificial intelligence.
Computer communication systems.
Data mining.
Education-Data processing.



  • Applications
  • Automated Grading of Exam Responses: An Extensive Classification Benchmark
  • Automatic human-like detection of code smells
  • HTML-LSTM: Information Extraction from HTML Tables in Web Pages using Tree-Structured LSTM
  • Predicting reach to find persuadable customers: improving uplift models for churn prevention
  • Classification
  • A Semi-Supervised Framework for Misinformation Detection
  • An Analysis of Performance Metrics for Imbalanced Classification
  • Combining Predictions under Uncertainty: The Case of Random Decision Trees
  • Shapley-Value Data Valuation for Semi-Supervised Learning
  • Data streams
  • A Network Intrusion Detection System for Concept Drifting Network Traffic Data
  • Incremental k-Nearest Neighbors Using Reservoir Sampling for Data Streams
  • Statistical Analysis of Pairwise Connectivity
  • Graph and Network Mining
  • FHA: Fast Heuristic Attack against Graph Convolutional Networks
  • Ranking Structured Objects with Graph Neural Networks
  • Machine Learning for COVID-19
  • Knowledge discovery of the delays experienced in reporting covid19 confirmed positive cases using time to event models
  • Multi-Scale Sentiment Analysis of Location-Enriched COVID-19 Arabic Social Data
  • Prioritization of COVID-19 literature via unsupervised keyphrase extraction and document representation learning
  • Sentiment Nowcasting during the COVID-19 Pandemic
  • Neural Networks and Deep Learning
  • A Sentence-level Hierarchical BERT Model for Document Classification with Limited Labelled Data
  • Calibrated Resampling for Imbalance and Long-Tails in Deep learning
  • Consensus Based Vertically Partitioned Multi-Layer Perceptrons for Edge Computing
  • Controlling BigGAN Image Generation with a Segmentation Network
  • GANs for tabular healthcare data generation: a review on utility and privacy
  • Preferences and Recommender Systems
  • An Ensemble Hypergraph Learning framework for Recommendation
  • KATRec: Knowledge Aware aTtentive Sequential Recommendations
  • Representation Learning and Feature Selection
  • Elliptical Ordinal Embedding
  • Unsupervised Feature Ranking via Attribute Networks
  • Responsible Artificial Intelligence
  • Deriving a Single Interpretable Model by Merging Tree-based Classifiers
  • Ensemble of Counterfactual Explainers. Riccardo Guidotti and Salvatore Ruggieri
  • Learning Time Series Counterfactuals via Latent Space Representations
  • Leveraging Grad-CAM to Improve the Accuracy of Network Intrusion Detection Systems
  • Local Interpretable Classifier Explanations with Self-generated Semantic Features
  • Privacy risk assessment of individual psychometric profiles
  • The Case for Latent Variable vs Deep Learning Methods in Misinformation Detection: An Application to COVID-19
  • Spatial, Temporal and Spatiotemporal Data
  • Local Exceptionality Detection in Time Series Using Subgroup Discovery
  • Neural Additive Vector Autoregression Models for Causal Discovery in Time Series
  • Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data.