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Springer - Information Quality in Information Fusion Book

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Description

Improve your understanding of data reliability with Information Quality in Information Fusion and Decision Making. Published by Springer as part of the Information Fusion and Data Science series, this book addresses the complex challenges of managing data from diverse sources. As information fusion involves gathering and combining large amounts of data from physical sensors, human intelligence reports, and social media, the risk of low fidelity or insufficient quality is high. This text provides a formal foundation and specific implementation strategies to help you build effective fusion systems. It is designed for those needing to navigate scenarios where information may be unreliable or incomplete, ensuring better decision-making processes through improved data management. Whether you are studying data science or working in knowledge management, this book offers a contemporary view of how to handle insufficient information quality in modern fusion systems.

Key Features

Provides a formal foundation for managing insufficient information quality during the fusion process.

Covers diverse data sources including physical sensors, human intelligence, and social media reports.

Offers implementation strategies for building reliable fusion systems for decision making.

Explores the contemporary role of information quality within the field of data science.

Addresses methods for handling unreliable or low fidelity data in complex environments.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
10 April 2019
Listed Since
03 October 2018

Barcode

No barcode data available

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