Advances in Database Systems

Hua, Ming; Pei, Jian

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.

Details

Published by: Springer

Publication Date: 2013-05-28

Format: Paperback

ISBN-13: 9781461428558

DOI: 10.1007/978-1-4419-9380-9

Dimensions: 235cm x155cm

Pages: 224