Springer, 2019. — 619 p. — (Information Fusion and Data Science). — ISBN: 3030036421.
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. Introduces a comprehensive ontology of information quality
Outlines methods of incorporating information quality in fusion processes
Provides a discussion on the relationships between information fusion, information quality and context
Includes real-life scenarios and applications in eHealth, intelligent transportation, smart power grids, defense and security
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.
Information Quality: Concepts, Models and DimensionsInformation Quality in Fusion-Driven Human-Machine Environments
Quality of Information Sources in Information Fusion
Using Quality Measures in the Intelligent Fusion of Probabilistic Information
Conflict Management in Information Fusion with Belief Functions
Basic Properties for Total Uncertainty Measures in the Theory of Evidence
Uncertainty Characterization and Fusion of Information from Unreliable Sources
Assessing the Usefulness of Information in the Context of Coalition Operations
Fact, Conjecture, Hearsay and Lies: Issues of Uncertainty in Natural Language Communications
Fake or Fact? Theoretical and Practical Aspects of Fake News
Information Quality and Social Networks
Quality, Context, and Information Fusion
Analyzing Uncertain Tabular Data
Evaluation of Information in the Context of Decision-Making
Evaluating and Improving Data Fusion Accuracy
Aspects of Information Quality in Various Domains of ApplicationDecision-Aid Methods Based on Belief Function Theory with
Application to Torrent Protection
An Epistemological Model for a Data Analysis Process in Support of Verification and Validation
Data and Information Quality in Remote Sensing
Reliability-Aware and Robust Multi-sensor Fusion Toward Ego-Lane Estimation Using Artificial Neural Networks
Analytics and Quality in Medical Encoding Systems
Information Quality: The Nexus of Actionable Intelligence
Ranking Algorithms: Application for Patent Citation Network
Conflict Measures and Importance Weighting for Information Fusion Applied to Industry
Quantify: An Information Fusion Model Based on Syntactic and Semantic Analysis and Quality Assessments to Enhance Situation Awareness
Adaptive Fusion