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.
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