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Information Quality in Information Fusion and Decision Making 2019 ed. [Kõva köide]

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  • Formaat: Hardback, 620 pages, kõrgus x laius: 235x155 mm, kaal: 1112 g, 127 Illustrations, color; 40 Illustrations, black and white; XVI, 620 p. 167 illus., 127 illus. in color., 1 Hardback
  • Sari: Information Fusion and Data Science
  • Ilmumisaeg: 10-Apr-2019
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030036421
  • ISBN-13: 9783030036423
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  • Formaat: Hardback, 620 pages, kõrgus x laius: 235x155 mm, kaal: 1112 g, 127 Illustrations, color; 40 Illustrations, black and white; XVI, 620 p. 167 illus., 127 illus. in color., 1 Hardback
  • Sari: Information Fusion and Data Science
  • Ilmumisaeg: 10-Apr-2019
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030036421
  • ISBN-13: 9783030036423
Teised raamatud teemal:
This book presents a contemporary view of the role of information quality in information fusion and decision making, and provides a formal foundation and the implementation strategies required for dealing with insufficient information quality in building fusion systems for decision making. Information fusion is the process of gathering, processing, and combining large amounts of information from multiple and diverse sources, including physical sensors to human intelligence reports and social media. That data and information may be unreliable, of low fidelity, insufficient resolution, contradictory, fake and/or redundant. Sources may provide unverified reports obtained from other sources resulting in correlations and biases. The success of the fusion processing depends on how well knowledge produced by the processing chain represents reality, which in turn depends on how adequate data are, how good and adequate are the models used, and how accurate, appropriate or applicable prior and contextual knowledge is.





By offering contributions by leading experts, this book provides an unparalleled understanding of the problem of information quality in information fusion and decision-making for researchers and professionals in the field.
Part I Information Quality: Concepts, Models and Dimensions
1 Information Quality in Fusion-Driven Human-Machine Environments
3(28)
Galina L. Rogova
2 Quality of Information Sources in Information Fusion
31(20)
Frederic Pichon
Didier Dubois
Thierry Denceux
3 Using Quality Measures in the Intelligent Fusion of Probabilistic Information
51(28)
Ronald R. Yager
Frederick E. Petry
4 Conflict Management in Information Fusion with Belief Functions
79(20)
Amaud Martin
5 Basic Properties for Total Uncertainty Measures in the Theory of Evidence
99(10)
Joaquin Abellan
Carlos J. Mantas
Eloi Bosse
6 Uncertainty Characterization and Fusion of Information from Unreliable Sources
109(26)
Lance Kaplan
Murat Sensoy
7 Assessing the Usefulness of Information in the Context of Coalition Operations
135(20)
Claire Saurel
Olivier Poitou
Laurence Cholvy
8 Fact, Conjecture, Hearsay and Lies: Issues of Uncertainty in Natural Language Communications
155(26)
Kellyn Rein
9 Fake or Fact? Theoretical and Practical Aspects of Fake News
181(26)
George Bara
Gerhard Backfried
Dorothea Thomas-Aniola
10 Information Quality and Social Networks
207(12)
Pontus Svenson
11 Quality, Context, and Information Fusion
219(24)
Galina L. Rogova
Lauro Snidaro
12 Analyzing Uncertain Tabular Data
243(36)
Oliver Kennedy
Boris Glavic
13 Evaluation of Information in the Context of Decision-Making
279(16)
Mark Burgin
14 Evaluating and Improving Data Fusion Accuracy
295(34)
John R. Talburt
Daniel Pullen
Melody Penning
Part II Aspects of Information Quality in Various Domains of Application
15 Decision-Aid Methods Based on Belief Function Theory with Application to Torrent Protection
329(30)
Simon Carladous
Jean-Marc Tacnet
Jean Dezert
Mireille Batton-Hubert
16 An Epistemological Model for a Data Analysis Process in Support of Verification and Validation
359(42)
Alicia Ruvinsky
LaKenya Walker
Warith Abdullah
Maria Seale
William G. Bond
Leslie Leonard
Janet Wedgwood
Michael Krein
Timothy Siedlecki
17 Data and Information Quality in Remote Sensing
401(22)
John Puentes
Laurent Lecornu
Basel Solaiman
18 Reliability-Aware and Robust Multi-sensor Fusion Toward Ego-Lane Estimation Using Artificial Neural Networks
423(32)
Tran Tuan Nguyen
Jan-Ole Perschewski
Fabian Engel
Jonas Kruesemann
Jonas Sitzmann
Jens Spehr
Sebastian Zug
Rudolf Kruse
19 Analytics and Quality in Medical Encoding Systems
455(16)
John Puentes
Laurent Lecornu
Clara Le Guillou
Jean-Michel Cauvin
20 Information Quality: The Nexus of Actionable Intelligence
471(48)
Marco Antonio Solano
21 Ranking Algorithms: Application for Patent Citation Network
519(20)
Hayley Beltz
Timothy Rutledge
Raoul R. Wadhwa
Peter Brack
Jan Tobochnik
Aniko Fiilop
Gyorgy Fenyvesi
Peter Erdi
22 Conflict Measures and Importance Weighting for Information Fusion Applied to Industry 4.0
539(24)
Uwe Monks
Volker Lohweg
Helene Dorksen
23 Quantify: An Information Fusion Model Based on Syntactic and Semantic Analysis and Quality Assessments to Enhance Situation Awareness
563(24)
Leonardo Castro Botega
Allan Cesar Moreira de Oliveira
Valdir Amancio Pereira Junior
Jordan Ferreira Saran
Lucas Zanco Ladeira
Gustavo Marttos Caceres Pereira
Seiji Isotani
24 Adaptive Fusion
587(20)
Vincent Nimier
Kaouthar Benameur
Index 607
Éloi Bossé received the B.A.Sc., M.Sc., and Ph.D. degrees from Université Laval, Québec City, QC, Canada, in 1979, 1981, and 1990, respectively, all in electrical engineering. In 1981, he joined the Communications Research Centre, Ottawa, ON, Canada, doing research on signal processing and high-resolution spectral analysis. In 1988, he was transferred to the Defence Research Establishment, Ottawa, to research radar target tracking in multipath. In 1992, he moved to Defence Research and Development Canada Valcartier (DRDC Valcartier), Courcelette, QC, Canada, to lead a group of 45 Defence Scientists on information fusion and decision support. Since 1993, he has held Adjunct Professor positions with several universities, such as Université Laval (Québec, CA), the University of Calgary (Alberta, CA), Canada, and McMaster University, (Ontario, CA). He headed the Command & Control Decision Support Systems Section at DRDC Valcartier, from 1998 to his retirement in 2011. Dr. Bossé represented Canada (as a DRDC Member) in numerous international research fora under the various cooperation research programs (NATO, TTCP, and bi and bi- and trilaterals) in his area of expertise. Since 2011, he has been conducting some research activities under NATO Peace and Security Programme, as a Researcher with the Mathematics and Industrial Engineering Department, Polytechnic of Montreal, Montreal, QC, Canada, with the Department of Computer and Electrical Engineering Department at McMaster University and finally, as an Associate Researcher with IMT-Atlantique, Plouzané, France (since 2010). In 2015, he founded  Expertise Parafuse Inc., in Québec city, a consultant rm on Analytics and Information Fusion Technologies. He has published over 200 papers in journals, book chapters, conference proceedings, and technical reports. He has coauthored and coedited 45 books on information fusion.

Galina Rogova received her MSc and PhD in Moscow, Russia. She is a research professor atthe State University of New York at Buffalo. She is recognized internationally as an expert in information fusion, machine learning, decision making under uncertainty, and information quality, and has lectured extensively on these topics. Dr. Rogova has worked on a wide range of defense and non-defense applications such as situation and threat assessment, understanding of volcanic eruption patterns, computer-aided diagnosis, and intelligent transportation system, among others. Her research was funded by multiple government agencies as well as commercial companies. She has published numerous papers and co-edited 7 books on information fusion and decision making.