Integrated Uncertainty in Knowledge Modelling and Decision Making [electronic resource] : International Symposium, IUKM 2011, Hangzhou, China, October 28-30, 2011, Proceedings / edited by Yongchuan Tang, Van-Nam Huynh, Jonathan Lawry.
Contributor(s): Tang, Yongchuan [editor.]
| Huynh, Van-Nam [editor.] | Lawry, Jonathan [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Artificial Intelligence: 7027Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2011Edition: 1st ed. 2011.Description: XII, 272 p. 60 illus., 28 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642249181.Subject(s): Artificial intelligence | Application software | Database management | Information storage and retrieval systems | Data mining | Algorithms | Artificial Intelligence | Computer and Information Systems Applications | Database Management | Information Storage and Retrieval | Data Mining and Knowledge Discovery | AlgorithmsAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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Springer Nature eBookSummary: This book constitutes the refereed proceedings of the International Symposium on Integrated Uncertainty in Knowledge Modeling and Decision Making, IUKM 2011, held in Hangzhou, China, in October 2011. The 21 revised full papers presented together with 1 keynote lecture and 5 invited talks were carefully reviewed and selected from 55 submissions. The papers provide a wealth of new ideas and report both theoretical and applied research on integrated uncertainty modeling and management.
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This book constitutes the refereed proceedings of the International Symposium on Integrated Uncertainty in Knowledge Modeling and Decision Making, IUKM 2011, held in Hangzhou, China, in October 2011. The 21 revised full papers presented together with 1 keynote lecture and 5 invited talks were carefully reviewed and selected from 55 submissions. The papers provide a wealth of new ideas and report both theoretical and applied research on integrated uncertainty modeling and management.
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