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Approach to the description of the meaning of a word based on an associative-ontological approach

DOI 10.18127/j20700814-201905-12


K.V. Nenausnikov – Post-graduate Student, Junior Research Scientist, St. Petersburg Institute for Informatics and Automation of RAS
V.V. Alexandrov – Dr.Sc.(Eng.), Professor, Main Research Scientist, St. Petersburg Institute for Informatics and Automation of RAS

Natural language words are ambiguous. Resolving the ambiguity of a word in a text is one of the main directions in the development of automatic word processing. This task has not been completely solved. Under a number of conditions, some approaches allow solving the problem with high accuracy, but in this case the requirements for the analyzed sources increase significantly.
To develop an algorithm for representing word meanings for small cases. A method based on an associative ontological approach is developed.
In this paper a new method for the automatic construction of word meanings based on the associative ontological approach is proposed and tested. This approach can be applied to both small and large corpus of texts without preliminary preparation (annotation of corps, compilation of thesauri, etc). The model of the meaning of a word is represented by a knowledge graph. The meaning of the central word described by the connections between him and the surrounding words. The central word is a word, one of the meanings of which is reflected in the model. Connections image the associative closeness of words. All the words presented are often found in the context. Words located on the first level are words whose connection with the central meaning is unambiguous. Words located on the second level are also associated with a central meaning, but have a higher rating of the relationship between the describing words – this may be a word associated with the described value, collocation, syntactic turnover, etc.
This model does not make it possible to give a formal description of a word, by definition or by constructing an ontology, which complicates its formal analysis by an expert. However, due to the non-discreteness of word meanings and the absence of definitions for all possible meanings, a formal description for all word meanings may not be possible.
The method allows you to automatically select from the proposed set of texts descriptions of objects (objects, facts, etc.) and a general description. It is up to the expert to determine when the obtained concepts are sufficiently distant from each other, so with a small number of iterations of the union real objects (objects, facts, etc.) will be obtained, and with a large number of iterations abstract concepts of the word will be highlighted – various lexical meanings of the word. The system is convergent, therefore, it has a certain final state even with a large amount of input data.
The idea of having a single concept on one page of the Internet turns out to be erroneous, therefore, in the future, before processing, texts will be preliminarily divide into thematic areas.

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