國立高雄大學圖資館 |

Language: English

Back

Information quality in information f...

Bosse, Eloi.

Information quality in information fusion and decision making

Record Type:	Electronic resources : Monograph/item
Title/Author:	Information quality in information fusion and decision makingedited by Eloi Bosse, Galina L. Rogova.
other author:	Bosse, Eloi.
Published:	Cham :Springer International Publishing :2019.
Description:	xvi, 620 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Information theory.
Online resource:	https://doi.org/10.1007/978-3-030-03643-0
ISBN:	9783030036430$q(electronic bk.)

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$q(electronic bk.)

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

183013
Information theory.

LC Class. No.: Q360

Dewey Class. No.: 003.54

Information quality in information fusion and decision making
LDR:04386nmm a2200349 a 4500 001 554395
003 DE-He213
005 20190401141759.0
006 m d
007 cr nn 008maaau
008 191118s2019 gw s 0 eng d
020 $a 9783030036430$q(electronic bk.)
020 $a 9783030036423$q(paper)
024 7 $a 10.1007/978-3-030-03643-0 $2 doi
035 $a 978-3-030-03643-0
040 $a GP $c GP
041 0 $a eng
050 4 $a Q360
072 7 $a UNF $2 bicssc
072 7 $a COM021030 $2 bisacsh
072 7 $a UNF $2 thema
072 7 $a UYQE $2 thema
082 0 4 $a 003.54 $2 23
090 $a Q360 $b .I43 2019
245 0 0 $a Information quality in information fusion and decision making $h [electronic resource] / $c edited by Eloi Bosse, Galina L. Rogova.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xvi, 620 p. : $b ill., digital ; $c 24 cm.
490 1 $a Information fusion and data science, $x 2510-1528
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.
650 0 $a Information theory. $3 183013
650 0 $a Decision making. $3 183849
650 1 4 $a Data Mining and Knowledge Discovery. $3 275288
650 2 4 $a Big Data/Analytics. $3 742047
650 2 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Operations Research/Decision Theory. $3 273963
650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Data-driven Science, Modeling and Theory Building. $3 758833
700 1 $a Bosse, Eloi. $3 836079
700 1 $a Rogova, Galina L. $3 836080
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Information fusion and data science. $3 818741
856 4 0 $u https://doi.org/10.1007/978-3-030-03643-0
950 $a Computer Science (Springer-11645)