DEVELOPING A METHODOLOGY FOR TRANSDISCURSIVE KNOWLEDGE TRANSFER: AT THE INTERSECTION OF COGNITIVE AND COMPUTATIONAL LINGUISTICS
DOI:
https://doi.org/10.17072/2073-6681-2021-2-25-35Keywords:
knowledge mediation, information misrepresentation, interdiscursive metaphor, metaphorical model-ling, ontological modelling, transdiscursive knowledge transfer, overlapping ontologies.Abstract
In the era of modern information society, the study of effective ways of transmitting, receiving, processing, and storing knowledge becomes relevant. Special knowledge, formed in the process of professional activity, stored in the form of ontology in the mind of an individual and represented in the form of the language of professional communication, terminologies, and term systems is of particular value. At the same time, the role of interdisciplinary communication and the communication of special knowledge increases, and the problem of the misrepresentation of special knowledge, caused by the mismatch of communicants’ ontologies, arises in the course of this communication. The solution to this problem could be the mediation of special knowledge during its transfer, which allows transforming the outgoing knowledge with minimal information losses and a high degree of assimilation.This article presents the results of a project aimed at solving this problem of the misrepresentation of special knowledge in the process of interdisciplinary communication. In the framework of the project, the methodology of knowledge mediation was developed, and new software was created to automate the process of term system generation (TSBuilder) and identifying potentially close subject areas for the selection of effective linguistic means of cognitive mediation (TSGraph).The novelty of the research lies in its interdisciplinary approach to the problem solution and the use of data mining tools for the implementation of ontological and metaphorical modelling. The developed methodology of special knowledge mediation can be used to optimize professional communication in various subject areas, especially between experts and nonexperts, as well as in the implementation of students’ professional learning. The software provided is applicable for both linguistic research and other areas involved in professional communication.References
Список источников
НКРЯ – Национальный корпус русского языка. 2021. URL: https://ruscorpora.ru/new/ (дата обращения: 04.04.2021).
РуТез – Тезаурус русского языка РуТез. 2016. URL: http://www.labinform.ru/pub/ruthes/index.htm (дата обращения: 04.04.2021)
BNC – British National Corpus. 2021. URL: http://www.natcorp.ox.ac.uk/ (дата обращения: 04.04.2021).
COCA – Corpus of Contemporary American English. URL: https://www.english-corpora.org/coca/ (дата обращения: 04.04.2021).
Datamuse – Datamuse API. 2021. URL: http://www.datamuse.com/api/ (дата обращения: 04.04.2021).
FrameNet – FrameNet, 2021. URL: https://framenet.icsi.berkeley.edu/fndrupal/ (дата обращения: 04.04.2021).
WordNet – Princeton, New Jersey 08544 USA. URL: https://wordnet.princeton.edu/ (дата обращения: 04.04.2021)
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