Discovery Science
21st International Conference, DS 2018, Limassol, Cyprus, October 29–31, 2018, Proceedings
Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Database Management, General Computing
| Author: | ISBN: | 9783030017712 | |
| Publisher: | Springer International Publishing | Publication: | October 22, 2018 |
| Imprint: | Springer | Language: | English |
| Author: | |
| ISBN: | 9783030017712 |
| Publisher: | Springer International Publishing |
| Publication: | October 22, 2018 |
| Imprint: | Springer |
| Language: | English |
This book constitutes the proceedings of the 21st International Conference on Discovery Science, DS 2018, held in Limassol, Cyprus, in October 2018, co-located with the International Symposium on Methodologies for Intelligent Systems, ISMIS 2018.
The 30 full papers presented together with 5 abstracts of invited talks in this volume were carefully reviewed and selected from 71 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: Classification; meta-learning; reinforcement learning; streams and time series; subgroup and subgraph discovery; text mining; and applications.
This book constitutes the proceedings of the 21st International Conference on Discovery Science, DS 2018, held in Limassol, Cyprus, in October 2018, co-located with the International Symposium on Methodologies for Intelligent Systems, ISMIS 2018.
The 30 full papers presented together with 5 abstracts of invited talks in this volume were carefully reviewed and selected from 71 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: Classification; meta-learning; reinforcement learning; streams and time series; subgroup and subgraph discovery; text mining; and applications.
