Uncertainty models in information and database systems
Journal of Information Science
Fuzzy functional dependencies and lossless join decomposition of fuzzy relational database systems
ACM Transactions on Database Systems (TODS)
The relational model for database management: version 2
The relational model for database management: version 2
An extension of classical functional dependency: dynamic fuzzy functional dependency
Information Sciences: an International Journal - Relational methods in computer science
The Lowell database research self-assessment
Communications of the ACM - Adaptive complex enterprises
Fuzzy logic programming via multilattices
Fuzzy Sets and Systems
A Complete Logic for Fuzzy Functional Dependencies over Domains with Similarity Relations
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
An efficient algorithm for reasoning about fuzzy functional dependencies
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
Dual multi-adjoint concept lattices
Information Sciences: an International Journal
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Fuzzy set theory has proved to be a successful paradigm to extend the database relational model, augmenting its skill to capture uncertaintly. This capability may be consider in two levels: the data itself and the constraints defined to adjust the database schema to the real system. When constraints are considered, it is necessary to design methods to reason about it and not only a way to express them. This situation leads to a ambitious goal: the design of automated reasoning methods. Highly-expressive data models are not useful without an automated reasoning method. In this work we introduce an automated method to infer with fuzzy functional dependencies over a high level generalization of the relational model and provide its completeness result.