Overview
- Survey information included with each chapter is unique in terms of introducing the different topics more comprehensively
- Includes case studies based on real-world examples
Part of the book series: Advances in Database Systems (ADBS, volume 35)
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Table of contents (16 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Managing and Mining Uncertain Data, a survey with chapters by a variety of well known researchers in the data mining field, presents the most recent models, algorithms, and applications in the uncertain data mining field in a structured and concise way. This book is organized to make it more accessible to applications-driven practitioners for solving real problems. Also, given the lack of structurally organized information on this topic, Managing and Mining Uncertain Data provides insights which are not easily accessible elsewhere. Managing and Mining Uncertain Data is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a reference book for advanced-level students in computer science and engineering, as well as the ACM, IEEE, SIAM, INFORMS and AAAI Society groups.
Reviews
From the reviews:
"The three broad areas covered in Aggarwal’s book are modeling and system design, management, and mining of uncertain data. … Aggarwal’s book is a timely publication, in that it provides a good summary of the current state of the art in the area of uncertain data modeling, management, and mining. It should be of interest to researchers and graduate students involved in the area, as well as novices who wish to become acquainted with the topic." (John Fulcher, ACM Computing Reviews, May, 2009)
Editors and Affiliations
Bibliographic Information
Book Title: Managing and Mining Uncertain Data
Editors: Charu C. Aggarwal
Series Title: Advances in Database Systems
DOI: https://doi.org/10.1007/978-0-387-09690-2
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag US 2009
Hardcover ISBN: 978-0-387-09689-6Published: 11 February 2009
Softcover ISBN: 978-1-4419-3517-5Published: 06 December 2010
eBook ISBN: 978-0-387-09690-2Published: 08 July 2010
Series ISSN: 1386-2944
Edition Number: 1
Number of Pages: XXII, 494
Number of Illustrations: 60 b/w illustrations
Topics: Data Mining and Knowledge Discovery, Database Management, Artificial Intelligence, Information Storage and Retrieval, Systems and Data Security, Information Systems Applications (incl. Internet)