Database Reference
In-Depth Information
Figure 4: Example 2. Fuzzy aggregations
for example. In this case, the model does not use some attributes (color and potency), and
some entities (computer).
Fuzzy aggregation of attributes and fuzzy aggregation of entities are studied by Chen
and Kerre (1998), and Ma et al. (2001) respectively, but their approaches are more limited.
Besides, as we will see bellow we can use fuzzy cardinality constraints in aggregation.
FUZZY DEGREES IN SPECIALIZATIONS
This approach is an extension of the fi rst level by Zvieli and Chen too. We can assign
a degree to a specialization in two ways, and the meaning of this degree may be expressed
in the model:
1.
Degree in the subclasses:
This degree expresses a fuzzy degree of one subclass in the
specialization. It is denoted by
G
m
=<degree> labeling the line joining the subclass with
the circle referred to as specialization circle, where m is the meaning of this degree.
2.
Degree in the specializations:
This degree expresses a fuzzy degree of all the special-
ization. It is denoted by
G
m
=<degree> labeling the specialization circle.
Example 3.
Let us consider an entity Employee which is a superclass with various
subclasses defi ning the abilities of the employees: Management Programmer, Systems
Programmer, Internet Programmer, Analyst, Graphic Designer, Accountant, etc., just like
Figure 5. These abilities have different importance denoted by the different degrees expressed
in the model.
FUZZY COMPLETENESS
CONSTRAINT ON SPECIALIZATIONS
The relationship between a class and all its subclasses can be
total
, if each member of
the class (or superclass) must compulsorily be a member of one (or some) of the subclasses,
