Probabilistic Ranking Techniques in Relational Databases by Ihab Ilyas

Probabilistic Ranking Techniques in Relational Databases by Ihab Ilyas

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.

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.

SKU	Unavailable
ISBN 13	9783031007187
ISBN 10	3031007182
Title	Probabilistic Ranking Techniques in Relational Databases
Author	Ihab Ilyas
Series	Synthesis Lectures On Data Management
Condition	Unavailable
Binding Type	Paperback
Publisher	Springer International Publishing AG
Year published	2011-03-21
Number of pages	71
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.