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- 000 01944cam a2200337 i 4500
- 008 110429s2011 nyuad b 000 0 eng d
- 035 __ |a (EXLCZ)992670000000076026
- 040 __ |a MiAaPQ |b eng |c MiAaPQ |e rda |d MiAaPQ
- 050 _4 |a Q375 |b .H83 2011
- 100 1_ |a Hua, Ming, |e author.
- 245 10 |a Ranking queries on uncertain data / |c Ming Hua [and] Jian Pei.
- 260 __ |a New York : |b Springer, |c 2011.
- 300 __ |a xv, 221 pages : |b illustrations ; |c 25 cm.
- 336 __ |a text |b txt |2 rdacontent
- 337 __ |a unmediated |b n |2 rdamedia
- 338 __ |a volume |b nc |2 rdacarrier
- 490 1_ |a Advances in database systems, |x 1386-2944 ; |v v. 42
- 500 __ |a Description based upon print version of record.
- 504 __ |a Includes bibliographical references.
- 520 __ |a 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.
- 650 _0 |a Uncertainty (Information theory)
- 700 1_ |a Pei, Jian, |e author.