Handling Uncertain Information in Vague Databases

PhD Thesis Proposal Defence


Title: "Handling Uncertain Information in Vague Databases"

by

Mr. An LU


Abstract:

The relational data model has been extensively studied for over three
decades in handling crispy data. It is well known that fuzzy database
models based on the fuzzy set theory by have been introduced to handle
uncertain data, which exist in many real life applications. Essentially,
in a fuzzy set (FS) each element is associated with a point-value
selected from the unit interval [0,1], which is termed the grade of
membership in the set. A vague set (VS) is a further generalization of
an FS. Instead of using point-based membership as in FSs, interval-based
member- ship is used in a VS. The interval-based membership in VSs is
more expressive in capturing vagueness of data. Thus, we extend
relational data model by vague set theory to handle uncertain
information. In our initial work, we utilize functional dependencies
(FDs), which are the most fundamental integrity constraints that arise in
practice in relational databases, to maintain the consistency of a vague
database by adopting the vague chase (VChase) procedure. We also propose
the concept of vague association rule (VAR). VARs address a limitation in
the traditional association rule (AR) mining problem, which ignores the
hesitation information of items in transactions. For example, in many
online shopping applications, the items that are put into the basket but
not checked out carry hesitation information. All the above work
indicates that the vague set model is an effective means to capture and
process uncertain information involved in applications. In this proposal,
we also discuss several on-going plans on handling uncertain information
in vague databases.


Date:     		Wednesday, 3 September 2008

Time:                   10:30a.m.-12:30p.m.

Venue:                  Room 4480
			lifts 25-26

Committee Members:      Dr. Wilfred Ng (Supervisor)
			Prof. Qiang Yang (Chairperson)
                        Dr. Ke Yi
			Dr. Nevin Zhang


**** ALL are Welcome ****