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Table of contents (17 papers)
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Front Matter
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Reliable Knowledge Discovery Methods
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Front Matter
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Reliability Analysis
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Front Matter
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Reliability Improvement Methods
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Front Matter
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About this book
Reliable Knowledge Discovery focuses on theory, methods, and techniques for RKDD, a new sub-field of KDD. It studies the theory and methods to assure the reliability and trustworthiness of discovered knowledge and to maintain the stability and consistency of knowledge discovery processes. RKDD has a broad spectrum of applications, especially in critical domains like medicine, finance, and military.
Reliable Knowledge Discovery also presents methods and techniques for designing robust knowledge-discovery processes. Approaches to assessing the reliability of the discovered knowledge are introduced. Particular attention is paid to methods for reliable feature selection, reliable graph discovery, reliable classification, and stream mining. Estimating the data trustworthiness is covered in this volume as well. Case studies are provided in many chapters.
Reliable Knowledge Discovery is designed for researchers and advanced-level students focused on computer science and electrical engineering as a secondary text or reference. Professionals working in this related field and KDD application developers will also find this book useful.
Keywords
Editors and Affiliations
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, School of Information Technology, Deakin University, Burwood, Australia
Honghua Dai
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, Computing, Hong Kong Polytechnic University, Hunghom, Hong Kong SAR
James N. K. Liu
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, Department of Knowledge Engineering, Maastricht University, Maastricht, Netherlands
Evgueni Smirnov
Bibliographic Information
Book Title: Reliable Knowledge Discovery
Editors: Honghua Dai, James N. K. Liu, Evgueni Smirnov
DOI: https://doi.org/10.1007/978-1-4614-1903-7
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Science+Business Media, LLC 2012
Hardcover ISBN: 978-1-4614-1902-0Published: 23 February 2012
Softcover ISBN: 978-1-4899-9532-2Published: 12 April 2014
eBook ISBN: 978-1-4614-1903-7Published: 23 February 2012
Edition Number: 1
Number of Pages: XVIII, 310
Topics: Artificial Intelligence, Database Management, Pattern Recognition, Data Storage Representation, Computer Graphics