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Integrated Uncertainty in Knowledge Modelling and Decision Making : 7th International Symposium, IUKM 2019, Nara, Japan, March 27-29, 2019, Proceedings / edited by Hirosato Seki, Canh Hao Nguyen, Van-Nam Huynh, Masahiro Inuiguchi.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 11471
- Lecture Notes in Artificial Intelligence, 2945-9141 ; 11471
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Machine theory.
- Algorithms.
- Data mining.
- Computer science-Mathematics.
- Numerical analysis.
- Artificial Intelligence.
- Formal Languages and Automata Theory.
- Data Mining and Knowledge Discovery.
- Mathematical Applications in Computer Science.
- Numerical Analysis.
- Local Subjects:
- Artificial Intelligence.
- Formal Languages and Automata Theory.
- Algorithms.
- Data Mining and Knowledge Discovery.
- Mathematical Applications in Computer Science.
- Numerical Analysis.
- Physical Description:
- 1 online resource (XX, 444 pages) : 160 illustrations, 84 illustrations in color.
- Edition:
- 1st ed. 2019.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2019.
- System Details:
- text file PDF
- Summary:
- This book constitutes the refereed proceedings of the 7th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2019, held in Nara, Japan, in March 2019. The 37 revised full papers presented were carefully reviewed and selected from 93 submissions. The papers deal with all aspects of uncertainty modelling and management and are organized in topical sections on uncertainty management and decision support; econometrics; machine learning; machine learning applications; and statistical methods.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-14815-7
- 9783030148157
- Access Restriction:
- Restricted for use by site license.
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