Description

Book Synopsis

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.



Table of Contents

Advanced Machine Learning.- Applications.- Data and Knowledge Representation.- Feature Importance.- Interpretable Machine Learning.- Networks.- Pattern Discovery.- Time Series.

Discovery Science: 22nd International Conference, DS 2019, Split, Croatia, October 28–30, 2019, Proceedings

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    A Paperback by Petra Kralj Novak, Tomislav Šmuc, Sašo Džeroski

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      View other formats and editions of Discovery Science: 22nd International Conference, DS 2019, Split, Croatia, October 28–30, 2019, Proceedings by Petra Kralj Novak

      Book details

      Publisher Springer Nature Switzerland AG
      Published 19 October 2019
      ISBN-13 9783030337773
      978-3030337773
      ISBN-10 3030337774
      Also in:
      Computing Artificial intelligence (AI) Data mining Expert systems / knowledge-based systems

      Description

      Book Synopsis

      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.



      Table of Contents

      Advanced Machine Learning.- Applications.- Data and Knowledge Representation.- Feature Importance.- Interpretable Machine Learning.- Networks.- Pattern Discovery.- Time Series.

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