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Discovery and fusion of uncertain kn...
~
Yue, Kun.
Discovery and fusion of uncertain knowledge in data
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Discovery and fusion of uncertain knowledge in data/ Kun Yue...[et al.]
other author:
Yue, Kun.
Published:
Singapore :World Scientific, : c2018.,
Description:
1 online resource (224 p.) :ill. :
Notes:
Title from PDF title page (viewed September 26, 2017)
Subject:
Data mining. -
Online resource:
http://www.worldscientific.com/worldscibooks/10.1142/10628#t=toc
ISBN:
9789813227149
Discovery and fusion of uncertain knowledge in data
Discovery and fusion of uncertain knowledge in data
[electronic resource] /Kun Yue...[et al.] - 1st ed. - Singapore :World Scientific,c2018. - 1 online resource (224 p.) :ill. - East China Normal University scientific reports,62382-5715 ;. - East China Normal University scientific reports ;6..
Title from PDF title page (viewed September 26, 2017)
Includes bibliographical references and index.
"As one of the popular and important probabilistic graphical models, Bayesian network (BN) is the effective framework for representing and inferring uncertain knowledge by means of qualitative and quantitative manners. In this book, adopting BN as the framework of knowledge representation and inferences, we consider the following issues: Learning BN from massive data using MapReduce; Inferences of large-scale BN using MapReduce; BN-based lineage representation and analysis over uncertain data; Lineage-driven and BN-based error detection in uncertain data; Fusion of uncertain knowledge in dynamic data."--Preface.
Electronic reproduction.
Singapore :
World Scientific,
[2017]
Mode of access: World Wide Web.
ISBN: 9789813227149Subjects--Topical Terms:
528622
Data mining.
LC Class. No.: QA76.9.D343 / Y84 2018
Dewey Class. No.: 006.312
Discovery and fusion of uncertain knowledge in data
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World Scientific,
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ill.
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Title from PDF title page (viewed September 26, 2017)
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Includes bibliographical references and index.
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"As one of the popular and important probabilistic graphical models, Bayesian network (BN) is the effective framework for representing and inferring uncertain knowledge by means of qualitative and quantitative manners. In this book, adopting BN as the framework of knowledge representation and inferences, we consider the following issues: Learning BN from massive data using MapReduce; Inferences of large-scale BN using MapReduce; BN-based lineage representation and analysis over uncertain data; Lineage-driven and BN-based error detection in uncertain data; Fusion of uncertain knowledge in dynamic data."--Preface.
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Mode of access: World Wide Web.
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Data mining.
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http://www.worldscientific.com/worldscibooks/10.1142/10628#t=toc
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