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Recent Advancements in Multi-View Data Analytics / edited by Witold Pedrycz, Shyi-Ming Chen

Contributor(s): Pedrycz, Witold (1953-), editor literario | Chen, Shyi-Ming, editor literario
Material type: materialTypeLabelE-bookSeries: (Studies in Big Data, 2197-6511; 106).Publisher: Cham : Springer International Publishing, 2022Edition: First edition 2022.Description: 1 recurso en línea (VIII, 342 páginas) : 74 ilustraciones, 47 ilustraciones a color.ISBN: 9783030952396.Subject: Datos masivosOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
The Psychology of Conflictive Uncertainty -- How Multi-View Techniques Can Help in Processing Uncertainty -- Multi-View Clustering and Multi-View Models -- Rethinking Collaborative Clustering: A Practical and Theoretical Study within the Realm of Multi-View Clustering -- An Optimal Transport Framework for Collaborative Multi-View Clustering -- Data Anonymization through Multi-Modular Clustering.
In: Springer Nature eBookSummary: This book provides timely studies on multi-view facets of data analytics by covering recent trends in processing and reasoning about data originating from an array of local sources. A multi-view nature of data analytics is encountered when working with a variety of real-world scenarios including clustering, consensus building in decision processes, computer vision, knowledge representation, big data, data streaming, among others. The chapters demonstrate recent pursuits in the methodology, theory, advanced algorithms, and applications of multi-view data analytics and bring new perspectives of data interpretation. The timely book will appeal to a broad readership including both researchers and practitioners interested in gaining exposure to the rapidly growing trend of multi-view data analytics and intelligent systems.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería QA76.9.B45 2022 EB (Browse shelf(Opens below)) Acceso electrónico
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The Psychology of Conflictive Uncertainty -- How Multi-View Techniques Can Help in Processing Uncertainty -- Multi-View Clustering and Multi-View Models -- Rethinking Collaborative Clustering: A Practical and Theoretical Study within the Realm of Multi-View Clustering -- An Optimal Transport Framework for Collaborative Multi-View Clustering -- Data Anonymization through Multi-Modular Clustering.

This book provides timely studies on multi-view facets of data analytics by covering recent trends in processing and reasoning about data originating from an array of local sources. A multi-view nature of data analytics is encountered when working with a variety of real-world scenarios including clustering, consensus building in decision processes, computer vision, knowledge representation, big data, data streaming, among others. The chapters demonstrate recent pursuits in the methodology, theory, advanced algorithms, and applications of multi-view data analytics and bring new perspectives of data interpretation. The timely book will appeal to a broad readership including both researchers and practitioners interested in gaining exposure to the rapidly growing trend of multi-view data analytics and intelligent systems.

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