Overview
- Presents challenging problems, the fundamental principles, and the evaluation algorithms of ranking queries on uncertain data
- Includes efficient and scalable query evaluation algorithms for the ranking queries
- Covers a comprehensive empirical evaluation of the queries
- The first book to systematically discuss the problem of ranking queries on uncertain data
- Includes supplementary material: sn.pub/extras
Part of the book series: Advances in Database Systems (ADBS, volume 200)
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Table of contents (9 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Uncertain data is inherent in many important applications, such as environmental surveillance, market analysis, and quantitative economics research. Due to the importance of those applications and rapidly increasing amounts of uncertain data collected and accumulated, analyzing large collections of uncertain data has become an important task. Ranking queries (also known as top-k queries) are often natural and useful in analyzing uncertain data.
Ranking Queries on Uncertain Data discusses the motivations/applications, challenging problems, the fundamental principles, and the evaluation algorithms of ranking queries on uncertain data. Theoretical and algorithmic results of ranking queries on uncertain data are presented in the last section of this book. Ranking Queries on Uncertain Data is the first book to systematically discuss the problem of ranking queries on uncertain data.
Authors and Affiliations
Bibliographic Information
Book Title: Ranking Queries on Uncertain Data
Authors: Ming Hua, Jian Pei
Series Title: Advances in Database Systems
DOI: https://doi.org/10.1007/978-1-4419-9380-9
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Science+Business Media, LLC 2011
Hardcover ISBN: 978-1-4419-9379-3Published: 12 April 2011
Softcover ISBN: 978-1-4614-2855-8Published: 28 May 2013
eBook ISBN: 978-1-4419-9380-9Published: 28 March 2011
Series ISSN: 1386-2944
Edition Number: 1
Number of Pages: XVI, 224
Topics: Database Management, Data Mining and Knowledge Discovery, Information Systems Applications (incl. Internet), Information Systems and Communication Service