Information Quality in Information Fusion and Decision Making

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Information Quality in Information Fusion and Decision Making

Cybernetics and systems theory Management decision making Operational research Databases Data mining Artificial intelligence Expert systems / knowledge-based systems

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Collection: Information Fusion and Data Science

Language: English

Published by: Springer

Published on: 2nd April 2019

Format: LCP-protected ePub

Size: 59 Mb

ISBN: 9783030036430


Overview

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.

Contributions

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.

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