On one approach to the implementation of the domain ontology

An ontology model implemented in the almost intelligent learning system KARKAS is considered. Its possibilities are analyzed on the example of determining exposure in the assessment of environmental risk.

Over the past decades, ontologies have been of particular interest to artificial intelligence (AI) researchers. Ontologies can be used to represent knowledge about the concepts of the subject area (DQ) and the relationships between them, as well as to describe the content of Web pages. In addition, ontologies can be used to build knowledge bases (KB) not only for expert systems (ES), but also for any other applications.
One of the reasons for the need for an ontology is its sharing by both people and software agents. For example, the W3C is developing RDF (Resource Description Framework), a knowledge encoding language for Web pages, to make them understandable to software agents that search for information. In this sense, ontologies are intellectual tools for the development and improvement of the Internet.
There is no clear boundary between knowledge base and domain ontology.
The purpose of this work is to analyze the implementation of the ontology model for the almost intelligent learning system KARKAS.
Scientific and theoretical journal "Artificial Intelligence" №3, 2010 p.608 ─ 617
Abstract: II-2010 /materials of the International Scientific and Technical Conference/ 2010. T2 p.262 ─ 269
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