Managing subjective information in fuzzy database systems
CSC '93 Proceedings of the 1993 ACM conference on Computer science
Implementing a fuzzy relational database using community defined membership values
Proceedings of the 43rd annual Southeast regional conference - Volume 1
Determining the membership values to optimize retrieval in a fuzzy relational database
Proceedings of the 44th annual Southeast regional conference
Adjusting Fuzzy Similarity Functions for use with standard data mining tools
Journal of Systems and Software
Granularity of weighted averages and use of rate statistics in AggPro
Proceedings of the Winter Simulation Conference
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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 it to be retrieved based on its degree of membership. Determining the degree of membership in a category that best satisfies the largest number of users is difficult. A training phase is conducted in which a community that is representative of the final users is asked a series of questions about the category to which an element belongs. This input is then used to construct the membership function. However, the best way to construct the membership function is elusive. This paper evaluates different methods of constructing the membership function based on community opinions. It was determined that all of the methods produced similar results, however the Direct Rating and Weighted Average Methods arrive at their final value sooner and maintain that value for a longer period of time. More research is needed using a larger training community and a verification phase to distinguish between these two methods.