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V. Babenko et al.
• development of a method for analyzing the sources of knowledge of tabular
structures based on targeted enumeration and its mathematical support;
• development of a method for generating instances of objects of subject areas based
on knowledge sources of tabular structures and its mathematical support;
• application of the developed methods for the implementation of a set of software
tools for the formation of ontological knowledge bases.
In the course of solving the first of the stated tasks, it was found that historically the
first was the approach to the formation of ontological knowledge bases based on the
methods of structural analysis. The effectiveness of methods of this kind is limited
by the small number of tabular structures analyzed and the inconsistency of interpretation of the structural components of the knowledge sources of tabular structures
and their visual representation. The need to solve the problem of creating ontological
knowledge bases based on the sources of tabular structures, characterized by a high
level of complexity of organizing the contents of these sources, has led to the emergence of a new generation of intelligent methods for forming ontological knowledge
bases based on top-level ontologies. The approach to the formation of ontological
knowledge bases on the basis of upper-level ontologies involves the formation of
such bases in accordance with the terminology defined in the upper-level ontology.
Thus, the boundaries of the presentation of the components of domain objects, in
contrast to structural analysis, are found as a possible combination of terms defined
in the ontology by calculating measures of semantic similarity. This approach allows
you to build procedures for obtaining new knowledge, abstracting from the method
and format of storing the contents of structured sources of knowledge. The methodological basis of research includes the ideas and principles of artificial intelligence,
elements of the hypertext technologies of the Semantic Web, tools for knowledge
engineering, in particular ontological engineering. Experimental studies were carried
out on test examples and on real sources of knowledge of tabular structures in the form
of documents that are widely used in the Semantic Web environment for organizing
workflows. The implementation of the theoretical results of the study in the form
of algorithmic, mathematical support, as well as experimental studies conducted to
determine the upper bound and the nature of the growth of complexity of the method
of forming the ontological knowledge bases based on targeted enumeration, confirm
the validity of the hypothesis adopted at the beginning.
Keywords Semantic web · Ontological knowledge bases · Tabular structures ·
Organizing workflows · Hypermedia environment
1 Goal and Objectives of the Research
Important tasks that arise in the implementation of modern artificial intelligence
systems include the development of methods and means of forming the knowledge
bases of these systems. The need for this is due, first of all, to the active development of the Semantic Web initiative [1] to create expressive models for representing
V. Babenko et al.
• development of a method for analyzing the sources of knowledge of tabular
structures based on targeted enumeration and its mathematical support;
• development of a method for generating instances of objects of subject areas based
on knowledge sources of tabular structures and its mathematical support;
• application of the developed methods for the implementation of a set of software
tools for the formation of ontological knowledge bases.
In the course of solving the first of the stated tasks, it was found that historically the
first was the approach to the formation of ontological knowledge bases based on the
methods of structural analysis. The effectiveness of methods of this kind is limited
by the small number of tabular structures analyzed and the inconsistency of interpretation of the structural components of the knowledge sources of tabular structures
and their visual representation. The need to solve the problem of creating ontological
knowledge bases based on the sources of tabular structures, characterized by a high
level of complexity of organizing the contents of these sources, has led to the emergence of a new generation of intelligent methods for forming ontological knowledge
bases based on top-level ontologies. The approach to the formation of ontological
knowledge bases on the basis of upper-level ontologies involves the formation of
such bases in accordance with the terminology defined in the upper-level ontology.
Thus, the boundaries of the presentation of the components of domain objects, in
contrast to structural analysis, are found as a possible combination of terms defined
in the ontology by calculating measures of semantic similarity. This approach allows
you to build procedures for obtaining new knowledge, abstracting from the method
and format of storing the contents of structured sources of knowledge. The methodological basis of research includes the ideas and principles of artificial intelligence,
elements of the hypertext technologies of the Semantic Web, tools for knowledge
engineering, in particular ontological engineering. Experimental studies were carried
out on test examples and on real sources of knowledge of tabular structures in the form
of documents that are widely used in the Semantic Web environment for organizing
workflows. The implementation of the theoretical results of the study in the form
of algorithmic, mathematical support, as well as experimental studies conducted to
determine the upper bound and the nature of the growth of complexity of the method
of forming the ontological knowledge bases based on targeted enumeration, confirm
the validity of the hypothesis adopted at the beginning.
Keywords Semantic web · Ontological knowledge bases · Tabular structures ·
Organizing workflows · Hypermedia environment
1 Goal and Objectives of the Research
Important tasks that arise in the implementation of modern artificial intelligence
systems include the development of methods and means of forming the knowledge
bases of these systems. The need for this is due, first of all, to the active development of the Semantic Web initiative [1] to create expressive models for representing