Abstract: It is difficult to exaggerate the importance, the urgency and complexity of “good” classifications
creation, especially in knowledge management, artificial intelligence, decision making. To what extend it is
possible within a short paper, the peculiarities and advantages of the new system method of the systemological
classification analysis for the classifications of concepts creation were discussed. It is noted that the
systemological classification analysis on the basis of the natural classification improves considerably the quality
and the power of the classification knowledge models and ontologies, allows taking into account the deep
knowledge of any, including ill-structured, domains. In the process of the research conduction the system models
of the domain fragment of the ontologies on the basis of the parametric classification were created. Some results
of the actual domain “Social Networks in Internet” analysis and modelling and the ontology fragments, realized in
the ontologies engineering tool Protégé 3.2, are also considered. The systemological classification analysis
application has allowed proving the obtained classifications of social networks functions, taking into account the
objects essential properties. It has also successfully recommended itself for deep knowledge acquisition; the
basic hierarchy of classes, “good” classifications and ontologies creation; possesses predictive power, simple
logically relevant structure, ensures the possibility of the correct inference on knowledge.
Keywords: conceptual knowledge, knowledge systematization, natural classification, ontology, systemological
classification analysis, social network, hierarchy, systemology, artificial intelligence.
ACM Classification Keywords: 1.2 Artificial Intelligence – 1.2.6 Learning: Knowledge Acquisition
Link:
SYSTEMOLOGICAL CLASSIFICATION ANALYSIS IN CONCEPTUAL KNOWLEDGE
MODELING
Mikhail Bondarenko, Nikolay Slipchenko, Kateryna Solovyova,
Viktoriia Bobrovska, Andrey Danilov
http://foibg.com/ibs_isc/ibs-18/ibs-18-p19.pdf