Discovery Science 23rd International Conference, DS 2020, Thessaloniki, Greece, October 19-21, 2020, Proceedings / [electronic resource] :
edited by Annalisa Appice, Grigorios Tsoumakas, Yannis Manolopoulos, Stan Matwin.
- 1st ed. 2020.
- XXI, 706 p. 227 illus., 147 illus. in color. online resource.
- Lecture Notes in Artificial Intelligence, 12323 2945-9141 ; .
- Lecture Notes in Artificial Intelligence, 12323 .
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 andConcept-adapting Decision Tree Classifer -- Unsupervised Concept Drift Detection using a Student
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 19 short papers presented in this volume were carefully reviewed and selected from 76 submissions. The contributions were organized in topical sections named: classification; clustering; data and knowledge representation; data streams; distributed processing; ensembles; explainable and interpretable machine learning; graph and network mining; multi-target models; neural networks and deep learning; and spatial, temporal and spatiotemporal data.
9783030615277
10.1007/978-3-030-61527-7 doi
Artificial intelligence.
Application software.
Education--Data processing.
Data mining.
Information storage and retrieval systems.
Artificial Intelligence.
Computer and Information Systems Applications.
Computers and Education.
Data Mining and Knowledge Discovery.
Information Storage and Retrieval.
Computer and Information Systems Applications.
Q334-342 TA347.A78
006.3
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 andConcept-adapting Decision Tree Classifer -- Unsupervised Concept Drift Detection using a Student
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 19 short papers presented in this volume were carefully reviewed and selected from 76 submissions. The contributions were organized in topical sections named: classification; clustering; data and knowledge representation; data streams; distributed processing; ensembles; explainable and interpretable machine learning; graph and network mining; multi-target models; neural networks and deep learning; and spatial, temporal and spatiotemporal data.
9783030615277
10.1007/978-3-030-61527-7 doi
Artificial intelligence.
Application software.
Education--Data processing.
Data mining.
Information storage and retrieval systems.
Artificial Intelligence.
Computer and Information Systems Applications.
Computers and Education.
Data Mining and Knowledge Discovery.
Information Storage and Retrieval.
Computer and Information Systems Applications.
Q334-342 TA347.A78
006.3