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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-Verlag New York Inc. Imprint: Springer-Verlag New York Inc. Edition: 2011 ed. Volume: 42 Dimensions: Width: 15.50cm , Height: 1.20cm , Length: 23.50cm Weight: 0.454kg ISBN: 9781461428558ISBN 10: 1461428556 Pages: 224 Publication Date: 28 May 2013 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand We will order this item for you from a manufactured on demand supplier. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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