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Notice that the actual constraint graph representing this problem must contain two edges between X and Y since C2 is undirected but the graph representation being used by AC-3 is directed. AC-3 solves the problem by first removing the non-even values from of the domain of X as required by C1, leaving D(X) = { 0, 2, 4 }.
In relational database theory, a functional dependency is the following constraint between two attribute sets in a relation: Given a relation R and attribute sets X,Y R, X is said to functionally determine Y (written X → Y) if each X value is associated with precisely one Y value.
Database constraints are constraints on a database that require relation to satisfy certain properties. Relations that satisfy all such constraints are legal relations. Pages in category "Database constraints"
In database systems, consistency (or correctness) refers to the requirement that any given database transaction must change affected data only in allowed ways. Any data written to the database must be valid according to all defined rules, including constraints, cascades, triggers, and any combination thereof. This does not guarantee correctness ...
Consistency ensures that a transaction can only bring the database from one consistent state to another, preserving database invariants: any data written to the database must be valid according to all defined rules, including constraints, cascades, triggers, and any combination thereof. This prevents database corruption by an illegal transaction.
A physical data model (or database design) is a representation of a data design as implemented, or intended to be implemented, in a database management system. In the lifecycle of a project it typically derives from a logical data model , though it may be reverse-engineered from a given database implementation.
The concept of ABAC can be applied at any level of the technology stack and an enterprise infrastructure. For example, ABAC can be used at the firewall, server, application, database, and data layer. The use of attributes bring additional context to evaluate the legitimacy of any request for access and inform the decision to grant or deny access.
Association rule learning is a rule-based machine learning method for discovering interesting relations between variables in large databases. It is intended to identify strong rules discovered in databases using some measures of interestingness. [1]