Creation of Ontological Knowledge Bases in the Semantic Web by Analyzing Table Structures

Abstract

The active development of the Semantic Web initiative to create expressive models for representing knowledge distributed on the Web in the form of ontologies raises a number of problems associated with the development of information structures of ontological knowledge bases for automatic processing of data and knowledge. The subject of the research is the ontological knowledge base and methods of their formation within the framework of the Semantic Web. Moreover, various tabular structures are considered as sources of knowledge. The problem arises as a result of the contradiction between the wide variety of tabular structures used to organize the content of knowledge sources in a hypermedia environment and the insufficient efficiency of classical methods for analyzing sources of this type. In the course of research, this problem was decomposed into a number of tasks: analysis of existing approaches to the formation of ontological knowledge bases based on the sources of tabular structures; development of a formal model of ontological knowledge bases; development of a method for the formation of databases of ontological knowledge based on targeted enumeration and its mathematical support; development of a formal model of the sources of knowledge of table structures; 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.