Fuzzy functional dependencies and lossless join decomposition of fuzzy relational database systems
ACM Transactions on Database Systems (TODS)
Accommodating imprecision in database systems: issues and solutions
ACM SIGMOD Record - Directions for future database research & development
Functional dependencies and normal forms in the fuzzy relational database model
Information Sciences: an International Journal
Analysis of binary/ternary cardinality combinations in entity-relationship modeling
Data & Knowledge Engineering
Imprecision and uncertainty in the UFO database model
Journal of the American Society for Information Science - Special issue: management of imprecision and uncertainty
Fuzzy logic in data modeling: semantics, constraints, and database design
Fuzzy logic in data modeling: semantics, constraints, and database design
Principles and Applications
Fuzzy Database Modeling
Generalized Normal Forms for Probabilistic Relational Data
IEEE Transactions on Knowledge and Data Engineering
An analysis of structural validity in entity-relationship modeling
Data & Knowledge Engineering
Extending object-oriented databases for fuzzy information modeling
Information Systems - Databases: Creation, management and utilization
Fuzzy Databases: Modeling, Design, and Implementation
Fuzzy Databases: Modeling, Design, and Implementation
RSFDGrC'11 Proceedings of the 13th international conference on Rough sets, fuzzy sets, data mining and granular computing
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A multiargument relationship may be formally presented using the relational notation: R(X1, X2, ..., Xn), where R is the name of the relationship, and attributes Xi denote keys of entity sets which participate in it. The dependencies between all n attributes describe the integrity constraints and must not be infringed. They constitute a restriction for relationships of fewer attributes. In the paper an analysis of fuzzy functional dependencies between attributes of R is presented. Attribute vales are given by means of possibility distributions.