THE USE OF DISTRIBUTIVE SEMANTICS IN THE IDENTIFICATION OF SIGNIFICANT COMBINATIONS OF TITLES OF SEVERAL TEXT COLLECTIONS IN THE FORMALIZATION OF LINGUISTIC EXPERT INFORMATION
Abstract
The paper discusses methods of forming special models for the representation of various sets
of knowledge in various information systems. The work is devoted to the application of distributive
semantics in the identification of significant combinations in one subject area (PRO) within the
framework of the formalization of linguistic expert information (LEI). The paper applies an approach
to the formalization of LEI based on a set of analytical methods, where linear algebra is used as
models. This approach makes it possible to initialize the procedure for the automatic formation of
hierarchical architectures of LEI or dendrograms when identifying significant combinations of titles
of several collections of texts. The scientific novelty lies in the proposed analytical approach using
distributive semantics in identifying significant combinations of titles of several collections of texts,
which allows for the analysis and processing of linguistic expert information. A distinctive characteristic
of the proposed approach is the ability to formalize the ABM "Global Optimization Methods"
based on the synthesis of various already existing hierarchies of the ABM under consideration. The
paper aims to create conditions for the formalization of the LEI by applying distributive semantics
when identifying significant combinations of titles of several collections. The practical value of the
work lies in the development of a new approach to the formalization of LEI, taking into account distributive
semantics when identifying significant combinations of titles of several collections of texts.
The ontology in owl format "Methods of global optimization" in the program "Protege" is also built
in the work. The ontology is built on the basis of related data about. The ontology constructed in this
work complements the search structure within the framework of the considered PRO and can be
supplemented and developed in the future.
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