HEURISTICS AND NUMERICAL METHOD FOR NORMALIZING THE EMPIRICAL CONTEXT IN ONTOLOGICAL DATA ANALYSIS
Valentina A. Semenova
Samara Federal Research Scientific Center RAS, Institute for the Control of Complex Systems RAS
The research field is ontological data analysis, which consists in the construction of formal ontologies based on empirical data on semi-structured subject domains. The subject of the research is the normalization of the empirical VTF-context - a non-strict correspondence "objects-properties" - with properties existence constraints. The research objective is to develop a numerical method that implements a heuristic approach to the normalization of empirical contexts. The work uses the methods of the theory of sets and binary relations, models and methods of formal concept analysis, as well as the existing methodology for applying the properties existence constraints to construct formal ontologies. The difference and novelty of the proposed method consists in the more efficient implementation of the heuristic approach by representing the system of measured properties - the set of properties fixed in the objects of the studied subject domain with the existence constraints on it - as a set of substructures that are homogeneous in the form of existential relation of member properties.
ontological data analysis, empirical context, VTF-logic, system of measured properties, group of related properties, normal set, Manhattan metric