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OverviewUncertain 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. Full Product DetailsAuthor: Ming Hua , Jian PeiPublisher: Springer Imprint: Springer Dimensions: Width: 23.40cm , Height: 1.30cm , Length: 15.60cm Weight: 0.340kg ISBN: 9781441993816ISBN 10: 1441993819 Pages: 240 Publication Date: 30 March 2011 Audience: General/trade , General Format: Undefined Publisher's Status: Unknown Availability: Available To Order ![]() Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |