Ranking Queries on Uncertain Data (Paperback, 2011 ed.)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Advances in Database Systems, 42
Release date:	May 2013
First published:	2011
Authors:	Ming Hua • Jian Pei
Dimensions:	235 x 155 x 12mm (L x W x T)
Format:	Paperback
Pages:	224
Edition:	2011 ed.
ISBN-13:	978-1-4614-2855-8
Categories:	Books > Computing & IT > Computer communications & networking > General Books > Computing & IT > Applications of computing > Databases > General
LSN:	1-4614-2855-6
Barcode:	9781461428558

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