Resumen

PETRENKO, Mykola; COHN, Ellen; SHCHUROV, Oleksandr  y  MALAKHOV, Kyrylo. Ontology-Driven Computer Systems: Elementary Senses in Domain Knowledge Processing. SACJ [online]. 2023, vol.35, n.2, pp.127-144. ISSN 2313-7835.  http://dx.doi.org/10.18489/sacj.v35i2.17445.

This article delves into the evolving frontier of ontology-driven natural language information processing. Through an in-depth examination, we put forth a novel linguistic processor architecture, uniquely integrating linguistic and ontological paradigms during semantic analysis. Distancing from conventional methodologies, our approach showcases a profound merger of knowledge extraction and representation techniques. A central highlight of our research is the development of an ontology-driven information system, architected with an innate emphasis on self-enhancement and adaptability. The system's salient capability lies in its adept handling of elementary knowledge, combined with its dynamic aptitude to foster innovative concepts and relationships. A particular focus is accorded to the system's application in scientific information processing, signifying its potential in revolutionising knowledge-based applications within scientific domains. Through our endeavours, we aim to pave the way for more intuitive, precise, and expansive ontology-driven tools in the realm of knowledge extraction and representation. Categories · Artificial intelligence ~ Knowledge representation and reasoning, Ontology engineering

Palabras clave : Ontology engineering; Elementary sense; Knowledge representation; Commonsense knowledge; Deep artificial intelligence; Scientific model of the World.

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