東華大學圖書館 |

Information quality in information fusion and decision making

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Information quality in information fusion and decision making/ edited by Eloi Bosse, Galina L. Rogova.
其他作者:	Bosse, Eloi.
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	xvi, 620 p. :ill., digital ;24 cm.
內容註:	PartI: Information Quality: Concepts, Models and Dimensions -- Chapter1: Information Quality in Fusion Driven Human-Machine Environments -- Chapter2: Quality of Information Sources in Information Fusion -- Chapter3: Using Quality Measures in the Intelligent Fusion of Probabilistic Information -- Chapter4: Conﬂict management in information fusion with belief functions -- Chapter5: Requirements for total uncertainty measures in the theory of evidence -- Chapter6: Uncertainty Characterization and Fusion of Information from Unreliable Sources -- Chapter7: Assessing the usefulness of information in the context of coalition operations -- Chapter8: Fact, Conjecture, Hearsay and Lies: Issues of Uncertainty in Natural Language Communications -- Chapter9: Fake or Fact? Theoretical and Practical Aspects of Fake News -- Chapter10: Information quality and social networks -- Chapter11: Quality, Context, and Information Fusion -- Chapter12: Analyzing Uncertain Tabular Data. Chapter13: Evaluation of information in the context of decision-making -- Chapter14: Evaluating and Improving Data Fusion Accuracy -- PartII: Aspects of Information Quality in various domains of application -- Chapter15: Decision-Aid Methods based on Belief Function Theory with Application to Torrent Protection -- Chapter16: An Epistemological Model for a Data Analysis Process in Support of Verification and Validation -- Chapter17: Data and Information Quality in Remote Sensing -- Chapter18: Reliability-Aware and Robust Multi-Sensor Fusion Towards Ego-Lane Estimation Using Artiﬁcial Neural Networks -- Chapter19: Analytics and Quality in Medical Encoding Systems -- Chapter20: Information Quality: The Nexus of Actionable Intelligence -- Chapter21: Ranking Algorithms: Application for Patent Citation Network -- Chapter22: Conﬂict Measures and Importance Weighting for Information Fusion applied to Industry 4.0 -- Chapter23: Quantify: An Information Fusion Model based on Syntactic and Semantic Analysis and Quality Assessments to Enhance Situation Awareness -- Chapter24: Adaptive fusion.
Contained By:	Springer eBooks
標題:	Information theory. -
電子資源:	https://doi.org/10.1007/978-3-030-03643-0
ISBN:	9783030036430

Information quality in information fusion and decision making
Information quality in information fusion and decision making[electronic resource] /edited by Eloi Bosse, Galina L. Rogova. - Cham :Springer International Publishing :2019. - xvi, 620 p. :ill., digital ;24 cm. - Information fusion and data science,2510-1528. - Information fusion and data science..

PartI: Information Quality: Concepts, Models and Dimensions -- Chapter1: Information Quality in Fusion Driven Human-Machine Environments -- Chapter2: Quality of Information Sources in Information Fusion -- Chapter3: Using Quality Measures in the Intelligent Fusion of Probabilistic Information -- Chapter4: Conﬂict management in information fusion with belief functions -- Chapter5: Requirements for total uncertainty measures in the theory of evidence -- Chapter6: Uncertainty Characterization and Fusion of Information from Unreliable Sources -- Chapter7: Assessing the usefulness of information in the context of coalition operations -- Chapter8: Fact, Conjecture, Hearsay and Lies: Issues of Uncertainty in Natural Language Communications -- Chapter9: Fake or Fact? Theoretical and Practical Aspects of Fake News -- Chapter10: Information quality and social networks -- Chapter11: Quality, Context, and Information Fusion -- Chapter12: Analyzing Uncertain Tabular Data. Chapter13: Evaluation of information in the context of decision-making -- Chapter14: Evaluating and Improving Data Fusion Accuracy -- PartII: Aspects of Information Quality in various domains of application -- Chapter15: Decision-Aid Methods based on Belief Function Theory with Application to Torrent Protection -- Chapter16: An Epistemological Model for a Data Analysis Process in Support of Verification and Validation -- Chapter17: Data and Information Quality in Remote Sensing -- Chapter18: Reliability-Aware and Robust Multi-Sensor Fusion Towards Ego-Lane Estimation Using Artiﬁcial Neural Networks -- Chapter19: Analytics and Quality in Medical Encoding Systems -- Chapter20: Information Quality: The Nexus of Actionable Intelligence -- Chapter21: Ranking Algorithms: Application for Patent Citation Network -- Chapter22: Conﬂict Measures and Importance Weighting for Information Fusion applied to Industry 4.0 -- Chapter23: Quantify: An Information Fusion Model based on Syntactic and Semantic Analysis and Quality Assessments to Enhance Situation Awareness -- Chapter24: Adaptive fusion.

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.

ISBN: 9783030036430

Standard No.: 10.1007/978-3-030-03643-0doiSubjects--Topical Terms:

542527
Information theory.

LC Class. No.: Q360

Dewey Class. No.: 003.54

Information quality in information fusion and decision making
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505 0 $a PartI: Information Quality: Concepts, Models and Dimensions -- Chapter1: Information Quality in Fusion Driven Human-Machine Environments -- Chapter2: Quality of Information Sources in Information Fusion -- Chapter3: Using Quality Measures in the Intelligent Fusion of Probabilistic Information -- Chapter4: Conﬂict management in information fusion with belief functions -- Chapter5: Requirements for total uncertainty measures in the theory of evidence -- Chapter6: Uncertainty Characterization and Fusion of Information from Unreliable Sources -- Chapter7: Assessing the usefulness of information in the context of coalition operations -- Chapter8: Fact, Conjecture, Hearsay and Lies: Issues of Uncertainty in Natural Language Communications -- Chapter9: Fake or Fact? Theoretical and Practical Aspects of Fake News -- Chapter10: Information quality and social networks -- Chapter11: Quality, Context, and Information Fusion -- Chapter12: Analyzing Uncertain Tabular Data. Chapter13: Evaluation of information in the context of decision-making -- Chapter14: Evaluating and Improving Data Fusion Accuracy -- PartII: Aspects of Information Quality in various domains of application -- Chapter15: Decision-Aid Methods based on Belief Function Theory with Application to Torrent Protection -- Chapter16: An Epistemological Model for a Data Analysis Process in Support of Verification and Validation -- Chapter17: Data and Information Quality in Remote Sensing -- Chapter18: Reliability-Aware and Robust Multi-Sensor Fusion Towards Ego-Lane Estimation Using Artiﬁcial Neural Networks -- Chapter19: Analytics and Quality in Medical Encoding Systems -- Chapter20: Information Quality: The Nexus of Actionable Intelligence -- Chapter21: Ranking Algorithms: Application for Patent Citation Network -- Chapter22: Conﬂict Measures and Importance Weighting for Information Fusion applied to Industry 4.0 -- Chapter23: Quantify: An Information Fusion Model based on Syntactic and Semantic Analysis and Quality Assessments to Enhance Situation Awareness -- Chapter24: Adaptive fusion.
520 $a 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.
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