Полное описание

Hua, M. Ranking Queries on Uncertain Data / by Ming Hua, Jian Pei. - Electronic text data. - New York, NY : Springer, 2011. - (Advances in Database Systems, ISSN 1386-2944 ; vol. 42). - URL: http://dx.doi.org/10.1007/978-1-4419-9380-9. - Загл. с экрана. - ISBN 978-1-4419-9380-9. - DOI 10.1007/978-1-4419-9380-9. - Текст : электронный.
Содержание:
Introduction -- Probabilistic Ranking Queries on Uncertain Data -- Related Work -- Top-k Typicality Queries on Uncertain Data -- Probabilistic Ranking Queries on Uncertain Data -- Continuous Ranking Queries on Uncertain Streams -- Ranking Queries on Probabilistic Linkages -- Probabilistic Path Queries on Road Networks -- Conclusions -- References.

ГРНТИ	УДК
20.23.19	004.657

Рубрики:
computer science
computers
database management
data mining
computer Science
database Management
data Mining and Knowledge Discovery
information Systems Applications (incl Internet)
information Systems and Communication Service

Аннотация: 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.
Доп. точки доступа:
Pei, J.

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