Query evaluation in probabilistic relational databases
Selected papers from the international workshop on Uncertainty in databases and deductive systems
On semantic issues connected with incomplete information databases
ACM Transactions on Database Systems (TODS)
Rough approximation quality revisited
Artificial Intelligence
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets and Data Mining: Analysis of Imprecise Data
Rough Sets and Data Mining: Analysis of Imprecise Data
Rough Sets, Fuzzy Sets and Knowledge Discovery
Rough Sets, Fuzzy Sets and Knowledge Discovery
Current Approaches to Handling Imperfect Information in Data and Knowledge Bases
IEEE Transactions on Knowledge and Data Engineering
Functional dependencies and incomplete information
VLDB '80 Proceedings of the sixth international conference on Very Large Data Bases - Volume 6
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Partial functional dependencies, functional dependencies accompanied by a factor, are examined in a relational database based on or-sets. The partial functional dependencies are dealt with under tuples having their belongingness degree to a relation. Whether a functional dependency accompanied by a factor holds in a relation is determined by comparing the factor with to what degree the relation satisfies the functional dependency. Inference rules, similar to Armstrong's axioms in the conventional relational databases, are obtained. Thus, we can discover another functional dependencies related with a partial functional dependency by using the inference rules.