Probabilistic Ranking Techniques in Relational Databases

Häftad, Engelska, 2011

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Ranking queries are widely used in data exploration, data analysis and decision making scenarios. We also discuss supporting rank join queries on uncertain data, and we show how to extend current rank join methods to handle uncertainty in scoring attributes.

Produktinformation

Utgivningsdatum2011-03-21
Mått191 x 235 x 5 mm
Vikt169 g
FormatHäftad
SpråkEngelska
SerieSynthesis Lectures on Data Management
Antal sidor71
FörlagSpringer International Publishing AG
ISBN9783031007187
OriginaltitelProbabilistic Ranking Techniques in Relational Databases

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Ihab F. Ilyas is an Associate Professor of Computer Science at the University of Waterloo. He received his PhD in computer science from Purdue University, West Lafayette, in 2004. He holds BS and MS degrees in computer science from Alexandria University, Egypt. His main research is in the area of database systems, with special interest in top-k and rank-aware query processing, managing uncertain and probabilistic databases, self-managing databases, indexing techniques, and spatial databases. Mohamed A. Soliman is a software engineer at Greenplum, where he works on building massively distributed database systems for efficient support of data warehousing and analytics. He received his PhD in computer science from University of Waterloo in 2010. He holds BS and MS degrees in computer science from Alexandria University, Egypt. His main research is in the area of rank-aware retrieval in relational databases, focusing primarily on supporting ranking queries on uncertain and probabilistic data.