Creation of Ontological Knowledge Bases in the Semantic Web …
215
properties; c
inst —instance object; c
—class object; E = {c
∈ C : c
instc}—the set
of instances of the object c, and E ⊆ I
U , where I
U —the finite set of instance objects
OKB; = {ω 0 , . . . , ω z }—attached procedures of the ODR object.
The set D and F of these objects can be represented in a simplified form by the
formulas:
D = {< d o , ∅ >, . . . , < d m , ∅ >}
(8)
F = {< f 0 , t 0 : c
0 ∈ C, ∅ >, . . . , < f q , t q : c
q ∈ C, ∅ >}.
(9)
We use a simplified record of properties, then the property-values of the objectclass will be defined as D = {d 0 , . . . , d m }, and the property-objects.
F = {< f 0 , t 0 : c
0 ∈ C >, . . . , < f q , t q : c
q ∈ C >}
(10)
Thus, the formal OKB model is adequately represented by formulas (1–10). The
synthesized model is necessary to develop a method for generating OKB based on
targeted enumeration.
4 Method for the Formation of Ontological Knowledge
Bases in Semantic Web Systems Based on Targeted
Enumeration
The need to develop a method for building ontological knowledge bases based on
targeted enumeration is due to the fact that ODR objects obtained as a result of SKTS
analysis and their instances obtained as a result of analysis of SKTS datasets from
which OKB is formed should be hierarchically organized according to the principle
of “inheritance”, according to which the root object of the hierarchy (the base object)
contains the most common properties, and already within the framework of subclass
objects there is a more accurate specification of ODR entities.
Given the above and the features of the property-centric representation of knowledge in OKB, the author proposes the formation of OKB by iteratively adding ODR
objects to OKB based on requests to enter ODR objects in OKB containing structural
logical diagrams of ODR objects, as represented by the expression below. Thus, the
formation of an OKB based on SKTS requires solving sub-tasks related to the analysis of incoming requests for entering ODR objects in OKB, searching for the most
relevant or fully matching ODR objects in OKB, and adding new related objects and
their instances.
The search for the most relevant ODR object query in OKB, if any, will be carried
out on the basis of targeted enumeration of ODR objects in OKB by finding the most
215
properties; c
inst —instance object; c
—class object; E = {c
∈ C : c
instc}—the set
of instances of the object c, and E ⊆ I
U , where I
U —the finite set of instance objects
OKB; = {ω 0 , . . . , ω z }—attached procedures of the ODR object.
The set D and F of these objects can be represented in a simplified form by the
formulas:
D = {< d o , ∅ >, . . . , < d m , ∅ >}
(8)
F = {< f 0 , t 0 : c
0 ∈ C, ∅ >, . . . , < f q , t q : c
q ∈ C, ∅ >}.
(9)
We use a simplified record of properties, then the property-values of the objectclass will be defined as D = {d 0 , . . . , d m }, and the property-objects.
F = {< f 0 , t 0 : c
0 ∈ C >, . . . , < f q , t q : c
q ∈ C >}
(10)
Thus, the formal OKB model is adequately represented by formulas (1–10). The
synthesized model is necessary to develop a method for generating OKB based on
targeted enumeration.
4 Method for the Formation of Ontological Knowledge
Bases in Semantic Web Systems Based on Targeted
Enumeration
The need to develop a method for building ontological knowledge bases based on
targeted enumeration is due to the fact that ODR objects obtained as a result of SKTS
analysis and their instances obtained as a result of analysis of SKTS datasets from
which OKB is formed should be hierarchically organized according to the principle
of “inheritance”, according to which the root object of the hierarchy (the base object)
contains the most common properties, and already within the framework of subclass
objects there is a more accurate specification of ODR entities.
Given the above and the features of the property-centric representation of knowledge in OKB, the author proposes the formation of OKB by iteratively adding ODR
objects to OKB based on requests to enter ODR objects in OKB containing structural
logical diagrams of ODR objects, as represented by the expression below. Thus, the
formation of an OKB based on SKTS requires solving sub-tasks related to the analysis of incoming requests for entering ODR objects in OKB, searching for the most
relevant or fully matching ODR objects in OKB, and adding new related objects and
their instances.
The search for the most relevant ODR object query in OKB, if any, will be carried
out on the basis of targeted enumeration of ODR objects in OKB by finding the most