Semantic knowledge models of non-crisp knowledge
2025, vol.17 , no.2, pp. 65-76
Article [2025-02-07]
Many practical applications, such as medical diagnosis, business decision-making, information searching and retrieval, etc., require usage of uncertain or ambiguous knowledge. Classical ontology-based technologies can represent and reasoning only with cri Several fuzzy or probabilistic extensions of classical description logics and languages for semantic knowledge representation have been proposed recently, but high reasoning complexity of its decision procedures make difficult its usage in real applications. It is of great importance to select the knowledge representation technology, ensuring both the needed expressiveness and effective reasoning. In this paper we make short analysis of knowledge representation and reasoning capabilities of description logics and ontology representation languages allowing representation of uncertain knowledge and propose a methodology for selecting the best description logic and ontology representation variant for every practical application.
probabilistic description logic, fuzzy description logic, ontology, methodology
https://doi.org/10.59035/ISMV6176
Tatyana Ivanova, Petya Petkova. Semantic knowledge models of non-crisp knowledge. International Journal on Information Technologies and Security, vol.17 , no.2, 2025, pp. 65-76. https://doi.org/10.59035/ISMV6176