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Modeling Decisions for Artificial Intelligence : 16th International Conference, MDAI 2019, Milan, Italy, September 4-6, 2019, Proceedings / edited by Vicenç Torra, Yasuo Narukawa, Gabriella Pasi, Marco Viviani.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 11676
- Lecture Notes in Artificial Intelligence, 2945-9141 ; 11676
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Data mining.
- Machine theory.
- Information storage and retrieval systems.
- Computer science-Mathematics.
- Mathematical statistics.
- Artificial Intelligence.
- Data Mining and Knowledge Discovery.
- Formal Languages and Automata Theory.
- Information Storage and Retrieval.
- Probability and Statistics in Computer Science.
- Local Subjects:
- Artificial Intelligence.
- Data Mining and Knowledge Discovery.
- Formal Languages and Automata Theory.
- Information Storage and Retrieval.
- Probability and Statistics in Computer Science.
- Physical Description:
- 1 online resource (XIX, 357 pages) : 201 illustrations, 43 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 16th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2019, held in Milan, Italy, in September 2019. The 30 papers presented in this volume were carefully reviewed and selected from 50 submissions. They discuss different facets of decision processes in a broad sense and present research in data science, data privacy, aggregation functions, human decision making, graphs and social networks, and recommendation and search. The papers are organized in the following topical sections: aggregation operators and decision making; data science and data mining; and data privacy and security. .
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-26773-5
- 9783030267735
- Access Restriction:
- Restricted for use by site license.
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