Proximity relations in the fuzzy relational database model
Fuzzy Sets and Systems
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
A Generalized Definition of Rough Approximations Based on Similarity
IEEE Transactions on Knowledge and Data Engineering
Fuzzy Functional Dependency and Its Application to Approximate Data Querying
IDEAS '00 Proceedings of the 2000 International Symposium on Database Engineering & Applications
Conditional Probability Relations in Fuzzy Relational Database
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
Similarity relations and fuzzy orderings
Information Sciences: an International Journal
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In this paper, we discuss preciseness of data in terms of obtaining degree of similarity in which fuzzy set can be used as an alternative to represent imprecise data. Degree of similarity between two imprecise data represented in two fuzzy sets is approximately determined by using fuzzy conditional probability relation. Moreover, degree of similarity relationship between fuzzy sets corresponding to fuzzy classes as results of fuzzy partition on a given finite set of data is examined. Related to a well known fuzzy partition, called fuzzy pseudopartition or fuzzy c-partition where c designates the number of fuzzy classes in the partition, we introduce fuzzy symmetric c-partition regarded as a special case of the fuzzy c-partition. In addition, we also introduce fuzzy covering as a generalization of fuzzy partition. Similarly, two fuzzy coverings, namely fuzzy c-covering and fuzzy symmetric c-covering are proposed corresponding to fuzzy c-partition and fuzzy symmetric c-partition, respectively.