Discovery Science : 23rd International Conference, DS 2020, Thessaloniki, Greece, October 19-21, 2020, Proceedings /

This book constitutes the proceedings of the 23rd International Conference on Discovery Science, DS 2020, which took place during October 19-21, 2020. The conference was planned to take place in Thessaloniki, Greece, but had to change to an online format due to the COVID-19 pandemic. The 26 full and...

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Bibliographic Details
Corporate Author:	SpringerLink (Online service)
Other Authors:	Appice, Annalisa (Editor), Tsoumakas, Grigorios (Editor), Manolopoulos, Yannis (Editor), Matwin, Stan (Editor)
Format:	eBook
Language:	English
Published:	Cham : Springer International Publishing : Imprint: Springer, 2020.
Edition:	1st ed. 2020.
Series:	Lecture Notes in Artificial Intelligence ; 12323
Subjects:	Artificial intelligence. Application software. Education-Data processing. Data mining. Information storage and retrieval. Artificial Intelligence. Computer Applications. Computers and Education. Data Mining and Knowledge Discovery. Information Storage and Retrieval. Information Systems Applications (incl. Internet). Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Classification
Evaluating Decision Makers over Selectively Labelled Data: A Causal Modelling Approach
Mitigating Discrimination in Clinical Machine Learning Decision Support using Algorithmic Processing Techniques
WeakAL: Combining Active Learning and Weak Supervision
Clustering
Constrained Clustering via Post-Processing
Deep Convolutional Embedding for Painting Clustering: Case Study on Picasso's Artworks
Dynamic Incremental Semi-Supervised Fuzzy Clustering for Bipolar Disorder Episode Prediction
Iterative Multi-Mode Discretization: Applications to Co-Clustering
Data and Knowledge Representation
COVID-19 Therapy Target Discovery with Context-aware Literature Mining
Semantic Annotation of Predictive Modelling Experiments
Semantic Description of Data Mining Datasets: An Ontology-based Annotation Schema
Data Streams
FABBOO - Online Fairness-aware Learning under Class Imbalance
FEAT: A Fairness-enhancing and Concept-adapting Decision Tree Classifer
Unsupervised Concept Drift Detection using a Student{Teacher Approach
Dimensionality Reduction and Feature Selection
Assembled Feature Selection For Credit Scoring in Micro nance With Non-Traditional Features
Learning Surrogates of a Radiative Transfer Model for the Sentinel 5P Satellite
Nets versus Trees for Feature Ranking and Gene Network Inference
Pathway Activity Score Learning Algorithm for Dimensionality Reduction of Gene Expression Data
Machine learning for Modelling and Understanding in Earth Sciences
Distributed Processing
Balancing between Scalability and Accuracy in Time-Series Classification for Stream and Batch Settings
DeCStor: A Framework for Privately and Securely Sharing Files Using a Public Blockchain
Investigating Parallelization of MAML
Ensembles
Extreme Algorithm Selection with Dyadic Feature Representation
Federated Ensemble Regression using Classification
One-Class Ensembles for Rare Genomic Sequences Identification
Explainable and Interpretable Machine Learning
Explaining Sentiment Classi cation with Synthetic Exemplars and Counter-Exemplars
Generating Explainable and Effective Data Descriptors Using Relational Learning: Application to Cancer Biology
Interpretable Machine Learning with Bitonic Generalized Additive Models and Automatic Feature Construction
Predicting and Explaining Privacy Risk Exposure in Mobility Data
Graph and Network Mining
Maximizing Network Coverage Under the Presence of Time Constraint by Injecting Most Effective k-Links
On the Utilization of Structural and Textual Information of a Scientific Knowledge Graph to Discover Future Research Collaborations: a Link Prediction Perspective
Simultaneous Process Drift Detection and Characterization with Pattern-based Change Detectors
Multi-Target Models
Extreme Gradient Boosted Multi-label Trees for Dynamic Classifier Chains
Hierarchy Decomposition Pipeline: A Toolbox for Comparison of Model Induction Algorithms on Hierarchical Multi-label Classification Problems
Missing Value Imputation with MERCS: a Faster Alternative to MissForest
Multi-Directional Rule Set Learning
On Aggregation in Ensembles of Multilabel Classifiers
Neural Networks and Deep Learning
Attention in Recurrent Neural Networks for Energy Disaggregation
Enhanced Food Safety Through Deep Learning for Food Recalls Prediction
Machine learning for Modelling and Understanding in Earth Sciences
FairNN - Conjoint Learning of Fair Representations for Fair Decisions
Improving Deep Unsupervised Anomaly Detection by Exploiting VAE Latent Space Distribution
Spatial, Temporal and Spatiotemporal Data
Detecting Temporal Anomalies in Business Processes using Distance-based Methods
Mining Constrained Regions of Interest: An Optimization Approach
Mining Disjoint Sequential Pattern Pairs from Tourist Trajectory Data
Predicting the Health Condition of mHealth App Users with Large Differences in the Amount of Recorded Observations - Where to Learn from
Spatiotemporal Traffic Anomaly Detection on Urban Road Network Using Tensor Decomposition Method
Time Series Regression in Professional Road Cycling.