This book constitutes the proceedings of the 22nd International Conference on Discovery Science, DS 2019, held in Split, Coratia, in October 2019.
The 21 full and 19 short papers presented together with 3 abstracts of invited talks in this volume were carefully reviewed and selected from 63 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: Advanced Machine Learning; Applications; Data and Knowledge Representation; Feature Importance; Interpretable Machine Learning; Networks; Pattern Discovery; and Time Series.
Advanced Machine Learning.- Applications.- Data and Knowledge Representation.- Feature Importance.- Interpretable Machine Learning.- Networks.- Pattern Discovery.- Time Series.
Advanced Machine Learning.- Applications.- Data and Knowledge Representation.- Feature Importance.- Interpretable Machine Learning.- Networks.- Pattern Discovery.- Time Series.
Inhaltsverzeichnis
Advanced Machine Learning.- Applications.- Data and Knowledge Representation.- Feature Importance.- Interpretable Machine Learning.- Networks.- Pattern Discovery.- Time Series.
Klappentext
This book constitutes the proceedings of the 22nd International Conference on Discovery Science, DS 2019, held in Split, Coratia, in October 2019.
The 21 full and 19 short papers presented together with 3 abstracts of invited talks in this volume were carefully reviewed and selected from 63 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: Advanced Machine Learning; Applications; Data and Knowledge Representation; Feature Importance; Interpretable Machine Learning; Networks; Pattern Discovery; and Time Series.
