Uncertainty Modeling for Data Mining_ A Label Semantics Approach [Qin & Tang 2015-02-11](2).pdf

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ADVANCED TOPICS IN SCIENCE AND TECHNOLOGY IN CHINA
Zengchang Qin
Yongchuan Tang
Uncertainty Modeling
for Data Mining
A Label Semantics Approach
ADVANCED TOPICS
IN SCIENCE AND TECHNOLOGY IN CHINA
ADVANCED TOPICS
IN SCIENCE AND TECHNOLOGY IN CHINA
Zhejiang University is one of the leading universities in China. In Advanced Topics
in Science and Technology in China, Zhejiang University Press and Springer jointly
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and editors from abroad who are outstanding experts and scholars in their fields.
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Advanced Topics in Science and Technology in China aims to present the latest and
most cutting-edge theories, techniques, and methodologies in various research areas
in China. It covers all disciplines in the fields of natural science and technology,
including but not limited to, computer science, materials science, life sciences,
engineering, environmental sciences, mathematics, and physics.
Zengchang Qin
Yongchuan Tang
Uncertainty Modeling for
Data Mining
A Label Semantics Approach
With 61 figures
Authors
Prof. Zengchang Qin
Intelligent Computing and Machine
Learning Lab, School of ASEE,
Beihang University, Beijing, China
E-mail: zengchang.qin@gmail.com
Prof. Yongchuan Tang
College of Computer Science
Zhejiang University,
Hangzhou, Zhejiang, China
E-mail: tyongchuan@gmail.com
ISSN 1995-6819
e-ISSN 1995-6827
Advanced Topics in Science and Technology in China
Zhejiang University Press, Hangzhou
ISBN 978-3-642-41250-9
ISBN 978-3-642-41251-6
(eBook)
Springer Dordrecht Heidelberg London New York
Library of Congress Control Number: 2013949181
© Zhejiang University Press, Hangzhou and Springer-Verlag Berlin Heidelberg 2014
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