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Recent advancements in multi-view data analytics

Record Type:	Electronic resources : Monograph/item
Title/Author:	Recent advancements in multi-view data analyticsedited by Witold Pedrycz, Shyi-Ming Chen.
other author:	Pedrycz, Witold.
Published:	Cham :Springer International Publishing :2022.
Description:	viii, 342 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Big data.
Online resource:	https://doi.org/10.1007/978-3-030-95239-6
ISBN:	9783030952396$q(electronic bk.)

Recent advancements in multi-view data analytics
Recent advancements in multi-view data analytics[electronic resource] /edited by Witold Pedrycz, Shyi-Ming Chen. - Cham :Springer International Publishing :2022. - viii, 342 p. :ill. (some col.), digital ;24 cm. - Studies in big data,v. 1062197-6511 ;. - Studies in big data ;v.1..

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.

ISBN: 9783030952396$q(electronic bk.)

Standard No.: 10.1007/978-3-030-95239-6doiSubjects--Topical Terms:

609582
Big data.

LC Class. No.: QA76.9.B45 / R43 2022

Dewey Class. No.: 005.7

Recent advancements in multi-view data analytics
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300 $a viii, 342 p. : $b ill. (some col.), digital ; $c 24 cm.
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505 0 $a 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.
520 $a 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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650 0 $a Database management. $3 182428
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650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Artificial Intelligence. $3 212515
700 1 $a Pedrycz, Witold. $3 275548
700 1 $a Chen, Shyi-Ming. $3 379558
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856 4 0 $u https://doi.org/10.1007/978-3-030-95239-6
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)