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Modeling Decisions for Artificial Intelligence [electronic resource] : 11th International Conference, MDAI 2014, Tokyo, Japan, October 29-31, 2014, Proceedings / edited by Vicenç Torra, Yasuo Narukawa, Yasunori Endo.

Contributor(s): Material type: TextSeries: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2014Edition: 1st ed. 2014Description: XVIII, 241 p. 47 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319120546
Subject(s): DDC classification:
  • 006.3 23
Online resources:
Contents:
Aggregation Operators and Decision Making -- Inference Systems Optimization -- Clustering and Similarity -- Data Mining and Data Privacy.
Summary: This book constitutes the proceedings of the 11th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2014, held in Tokyo, Japan, in October 2014. The 19 revised full papers presented together with an invited paper were carefully reviewed and selected from 38 submissions. They deal with the theory and tools for modeling decisions, as well as applications that encompass decision making processes and information fusion techniques and are organized in topical sections on aggregation operators and decision making, optimization, clustering and similarity, and data mining and data privacy.
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Aggregation Operators and Decision Making -- Inference Systems Optimization -- Clustering and Similarity -- Data Mining and Data Privacy.

This book constitutes the proceedings of the 11th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2014, held in Tokyo, Japan, in October 2014. The 19 revised full papers presented together with an invited paper were carefully reviewed and selected from 38 submissions. They deal with the theory and tools for modeling decisions, as well as applications that encompass decision making processes and information fusion techniques and are organized in topical sections on aggregation operators and decision making, optimization, clustering and similarity, and data mining and data privacy.

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