Defense Date

2006

Document Type

Thesis

Degree Name

Master of Science

Department

Computer Science

First Advisor

Dr. Lorraine Parker

Abstract

A fuzzy set is one in which membership in a category is not Boolean, rather items have a degree of membership. Fuzzy databases expand on this idea by storing fuzzy data and allowing data to be retrieved based on its degree of membership. Determining the degree of membership that satisfies the largest number of users is difficult. Five different methods of determining the membership function: the Direct Rating Method, the Random Method with step sizes of .02 and .03, the Steplock Method, and the Weighted Average Method, were compared on the basis of convergence and user satisfaction. The results support use of the Direct Rating Method and the Steplock Method in conjunction with each other, to produce the membership function in the least time and with the highest user satisfaction.

Rights

© The Author

Is Part Of

VCU University Archives

Is Part Of

VCU Theses and Dissertations

Date of Submission

June 2008

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