Efficient Query Processing in Uncertain Databases

PhD Thesis Proposal Defence


Title: "Efficient Query Processing in Uncertain Databases"

by

Mr. Xiang LIAN


Abstract:

Recently, many new applications, such as sensor data monitoring and mobile 
device tracking, raise up the issue of uncertain data management. Compared 
to precise data, uncertain objects in the uncertain database are not exact 
data points, which, instead, often reside within a region. In our initial 
work, we investigate three types of important queries in the context of 
uncertain databases. Due to the intrinsic differences between uncertain 
and certain data, we formally re-define these query types in uncertain 
databases, providing the confidence guarantee of the query answers. Most 
importantly, to tackle the efficiency problem of query processing, we 
propose effective pruning methods to facilitate reducing the search space 
for each of the three queries, and seamlessly integrate them into 
efficient query procedures. We also formulate and tackle some useful 
variants of these query types. We demonstrate through extensive 
experiments the efficiency and effectiveness of our proposed pruning 
methods and query processing approaches. In this proposal, we report our 
preliminary work and discuss the future research plans including several 
interesting directions on uncertain query processing.


Date:     		Wednesday, 25 February 2009

Time:                   2:00p.m.-4:00p.m.

Venue:                  Room 3588
 			lifts 27-28

Committee Members:      Dr. Lei Chen (Supervisor)
 			Dr. Ke Yi (Chairperson)
 			Prof. Dik-Lun Lee
 			Prof. Frederick Lochovsky


**** ALL are Welcome ****