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Information Quality in Information Fusion and Decision Making

  • Éloi Bossé
  • Galina L. Rogova

Part of the Information Fusion and Data Science book series (IFDS)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Information Quality: Concepts, Models and Dimensions

    1. Front Matter
      Pages 1-1
    2. Frédéric Pichon, Didier Dubois, Thierry Denœux
      Pages 31-49
    3. Joaquín Abellán, Carlos J. Mantas, Éloi Bossé
      Pages 99-108
    4. Claire Saurel, Olivier Poitou, Laurence Cholvy
      Pages 135-154
    5. George Bara, Gerhard Backfried, Dorothea Thomas-Aniola
      Pages 181-206
    6. Pontus Svenson
      Pages 207-218
    7. Galina L. Rogova, Lauro Snidaro
      Pages 219-242
    8. Oliver Kennedy, Boris Glavic
      Pages 243-277
    9. John R. Talburt, Daniel Pullen, Melody Penning
      Pages 295-326
  3. Aspects of Information Quality in Various Domains of Application

    1. Front Matter
      Pages 327-327
    2. Simon Carladous, Jean-Marc Tacnet, Jean Dezert, Mireille Batton-Hubert
      Pages 329-357
    3. Alicia Ruvinsky, LaKenya Walker, Warith Abdullah, Maria Seale, William G. Bond, Leslie Leonard et al.
      Pages 359-399
    4. John Puentes, Laurent Lecornu, Basel Solaiman
      Pages 401-421
    5. Tran Tuan Nguyen, Jan-Ole Perschewski, Fabian Engel, Jonas Kruesemann, Jonas Sitzmann, Jens Spehr et al.
      Pages 423-454
    6. John Puentes, Laurent Lecornu, Clara Le Guillou, Jean-Michel Cauvin
      Pages 455-470
    7. Hayley Beltz, Timothy Rutledge, Raoul R. Wadhwa, Péter Bruck, Jan Tobochnik, Anikó Fülöp et al.
      Pages 519-538
    8. Leonardo Castro Botega, Allan Cesar Moreira de Oliveira, Valdir Amancio Pereira Junior, Jordan Ferreira Saran, Lucas Zanco Ladeira, Gustavo Marttos Cáceres Pereira et al.
      Pages 563-586
    9. Vincent Nimier, Kaouthar Benameur
      Pages 587-606
  4. Back Matter
    Pages 607-620

About this book

Introduction

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.



Keywords

uncertainty characterization recognizing unreliable data QoI measurement Belief Function Theory intelligent information quality assessment Information quality assurance information quality in security

Editors and affiliations

  • Éloi Bossé
    • 1
  • Galina L. Rogova
    • 2
  1. 1.IMT-AtlantiqueBrestFrance
  2. 2.The State University of New York at BuffaloBuffaloUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-03643-0
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-030-03642-3
  • Online ISBN 978-3-030-03643-0
  • Series Print ISSN 2510-1528
  • Series Online ISSN 2510-1536
  • Buy this book on publisher's site
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