This book constitutes the refereed proceedings of the 17th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2020, held in Sant Cugat, Spain, in September 2020.*
The 24 papers presented in this volume were carefully reviewed and selected from 46 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, and data science and data mining.
* The conference was canceled due to the COVID-19 pandemic.
This book constitutes the refereed proceedings of the 17th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2020, held in Sant Cugat, Spain, in September 2020.*
The 24 papers presented in this volume were carefully reviewed and selected from 46 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, and data science and data mining.
* The conference was canceled due to the COVID-19 pandemic.
Modeling Decisions for Artificial Intelligence: 17th International Conference, MDAI 2020, Sant Cugat, Spain, September 2-4, 2020, Proceedings
Modeling Decisions for Artificial Intelligence: 17th International Conference, MDAI 2020, Sant Cugat, Spain, September 2-4, 2020, Proceedings
eBook (1st ed. 2020)
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Product Details
| ISBN-13: | 9783030575243 |
|---|---|
| Publisher: | Springer-Verlag New York, LLC |
| Publication date: | 08/26/2020 |
| Series: | Lecture Notes in Computer Science , #12256 |
| Sold by: | Barnes & Noble |
| Format: | eBook |
| File size: | 30 MB |
| Note: | This product may take a few minutes to download. |