Ranking Queries on Uncertain Data [recurso electrónico] / by Ming Hua, Jian Pei.

Por: Hua, Ming [author.]Colaborador(es): Pei, Jian [author.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Advances in Database Systems ; 42Editor: New York, NY : Springer New York, 2011Edición: 1Descripción: XVI, 224 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9781441993809Tema(s): Computer science | Information systems | Database management | Data mining | Computer Science | Database Management | Data Mining and Knowledge Discovery | Information Systems Applications (incl.Internet) | Information Systems and Communication ServiceFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 005.74 Clasificación LoC:QA76.9.D3Recursos en línea: Libro electrónicoTexto
Contenidos:
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.
En: Springer eBooksResumen: 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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Tipo de ítem Biblioteca actual Colección Signatura Copia número Estado Fecha de vencimiento Código de barras
Libro Electrónico Biblioteca Electrónica
Colección de Libros Electrónicos QA76.9 .D3 (Browse shelf(Abre debajo)) 1 No para préstamo 372212-2001

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.

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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