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Book Cover
E-book
Author Hua, Ming

Title Ranking queries on uncertain data / Ming Hua, Jian Pei
Published New York : Springer, ©2011

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Description 1 online resource (xv, 221 pages)
Series Advances in database systems ; v. 42
Advances in database systems ; v. 42.
Contents Probabilistic ranking queries on uncertain data -- Related work -- Top-k typicality queries on uncertain data -- Probabilistic ranking queries on uncertain data -- Continuous ranking queries on uncertain streams -- Ranking queries on probabilistic linkages -- Probabilistic path queries on road networks
Summary 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
Bibliography Includes bibliographical references (pages 215-221)
Notes Print version record
Subject Uncertainty (Information theory)
Data mining.
Data Mining
COMPUTERS -- Information Theory.
Informatique.
Uncertainty (Information theory)
Form Electronic book
Author Pei, Jian
LC no. 2011924205
ISBN 9781441993809
1441993800