ENGLISH

Ranking Queries on Uncertain Data

By Ming Hua , Jian Pei (auth.)

Book information

Publisher
Springer-Verlag New York
Year
2011
ISBN
1441993797, 9781441993793
DOI
10.1007/978-1-4419-9380-9
ISSN
1386-2944
Google Books ID
o9Q5vuJ1-XEC
Open Library ID
OL25058796M
Language
english
Format
PDF
Filesize
2 MB (1614261 bytes)
Series
ADVANCES IN DATABASE SYSTEMS 42
Edition
1
Pages
224\238
Orientation
yes
Scanned
no
Time added
2011-08-31 04:54:40
Database Management; Data Mining and Knowledge Dis

Description

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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