Survey on Query Semantics and Evaluation in Uncertain Databases

PhD Qualifying Examination


Title: "Survey on Query Semantics and Evaluation in Uncertain Databases"

by

Mr. Da YAN


Abstract:

Uncertain data are inherent in many real world applications. As a result,
uncertain data management is becoming more and more important due to the
large amount of uncertain data collected by the emerging data collection
techniques, such as sensors or GPS devices. Current research focuses on
both defining useful queries on uncertain data, and the efficient
algorithms of processing such queries.

This work surveys different uncertain data models, different types of
queries on uncertain data, and the corresponding query processing
techniques.

In terms of uncertain data models, we review the two popular sources
of uncertainty, i.e. existential uncertainty & attribute-level
uncertainty. Then we examine all kinds of uncertain data models for
relational data, XML data and graph data. We also study the graphical
model that is used to model data correlations.

As for query semantics, we mainly focus on top-k queries (ranking
queries), spatial queries, join queries. We also briefly review the
semantics of data mining tasks on uncertain data. The definition of
these queries are different from the deterministic case, and are
usually based on the possible world semantics.

Finally, we discuss the methods for processing queries on uncertain
data, including spatial pruning, probabilistic pruning (for threshold
queries), sampling, etc.


Date:                   Friday, 6 May 2011

Time:                   3:30pm - 5:30pm

Venue:                  Room 3416
                         lifts 17/18

Committee Members:	Dr. Wilfred Ng (Supervisor)
                         Dr. Ke Yi (Chairperson)
  			Dr. Lei Chen
  			Dr. Raywong Wong


**** ALL are Welcome ****