Neural network pattern for enhancing functionality of electronic dictionaries

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dc.contributor.authorFokin, Serhii
dc.date.accessioned2022-12-08T12:08:59Z
dc.date.available2022-12-08T12:08:59Z
dc.date.issued2019
dc.description.abstractenThe value of a dictionary is traditionally considered to be proportio nal to its physical volume, measured in the number of entries. However, the amount of useful data varies depending on existing hypertextual links across a dictionary. Therefore, its utilit y might also be calculated as proportional to the number of useful l inks among its structural parts which can interact in a similar way as neurons do via synapse links, provided that the number of links turns out to be exponentially greater than the number of entr ies. Today’s lexicographic practice, as well as an experimen t held by the author with his own developed onomasiological electronic dictionary of phraseological synonyms “IdeoPhrase”, appears to demonstrate that the main criterion for establishing links automatically is the repetition of each kind of signs (stylisti c labels, graphical word, metalinguistic comments). Automatically generated hypertextual links can be used for finding out semantic relations of different types among lexemes (synonymic, anto nymic and others), semantic equivalence or similarity among lexem es in different languages (which is close to automatic translation), as well as compiling a new dictionary. The fact that generated relation established by а computer constitute new useful knowledge which has not been directly input by the compiler, qualif ies this algorithm as artificial intelligence engine.uk
dc.format.pagerangePp. 150-158uk
dc.identifier.citationFokin, S. Neural network pattern for enhancing functionality of electronic dictionaries / Serhii Fokin // Advanced education. – 2019. – Iss. 12. – Pp. 150-158.uk
dc.identifier.urihttps://ela.kpi.ua/handle/123456789/51307
dc.language.isoenuk
dc.publisherIgor Sikorsky Kyiv Polytechnic Instituteuk
dc.publisher.placeKyivuk
dc.sourceAdvanced education : збірник наукових праць, Вип. 12uk
dc.subjectdictionaryuk
dc.subjectonomasiologyuk
dc.subjecthypertextualityuk
dc.subjectcomputational lexicographyuk
dc.subjecttranslationuk
dc.subjectsemanticsuk
dc.subjectphraseologyuk
dc.titleNeural network pattern for enhancing functionality of electronic dictionariesuk
dc.typeArticleuk

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Advanced education: збірник наукових праць, Вип. 12