Talk
"URank: Ranking and Aggregation Queries in Probabilistic Databases"
Ihab Ilyas, University of Waterloo
Monday, July 7, 2008 at 2:00 P.M.
Lubrano Conference Room (CIT 4th floor)
Ranking and aggregation queries are widely exploited in data exploration, data analysis and decision making scenarios. While most of the currently proposed ranking and aggregation techniques focus on deterministic data, several emerging applications involve data that is unclean or uncertain. Ranking and aggregating uncertain (probabilistic) data raises new challenges with respect to query semantics and processing, which makes conventional methods inapplicable.
In this talk, I will introduce new formulations for ranking and aggregation queries in probabilistic databases. The new formulations are based on marriage of traditional ranking and aggregation algorithms with possible worlds semantics. In the light of these formulations, I will describe a generic processing framework supporting both query types, and leveraging existing query processing and indexing capabilities in current database systems. The framework encapsulates a state space model, and efficient search algorithms that compute query answers with optimality guarantees.
Ihab Ilyas is an Assistant Professor of Computer Science at the University of Waterloo. He received his PhD in computer science from Purdue University, West Lafayette in 2004. He spent two summers with IBM Almaden Research Center and he's been an IBM CAS faculty fellow since January 2006. 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. For more information and a list of publications, please visit http://www.cs.uwaterloo.ca/~ilyas
Host: Ugur Cetintemel
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