Form of presentation | Articles in Russian journals and collections |
Year of publication | 2017 |
Язык | английский |
|
Makhmutova Alsu Nigmatyanovna, author
|
|
Bedrin Oleg Aleksandrovich, author
|
Bibliographic description in the original language |
Bedrin O.A., Makhmutova A.N. Using artificial neural network in machine translation / O.A. Bedrin, A.N. Makhmutova // Informacionnye tekhnologii v issledovatelskom prostranstve raznostrukturnykh yazykov: sbornik I mezhdunar. internet-konferencii molodykh uchenykh. – Kazan, 2017. - S. 34-37 |
Annotation |
Информационные технологии в исследовательском пространстве разноструктурных языков: |
Keywords |
artificial neural network (ANN), feedforward neural network (FFNN), recurrent
neural network (RNN), long-short term memory (LSTM), machine learning, neuron |
The name of the journal |
Информационные технологии в исследовательском пространстве разноструктурных языков:
|
Please use this ID to quote from or refer to the card |
https://repository.kpfu.ru/eng/?p_id=153401&p_lang=2 |
Full metadata record |
Field DC |
Value |
Language |
dc.contributor.author |
Makhmutova Alsu Nigmatyanovna |
ru_RU |
dc.contributor.author |
Bedrin Oleg Aleksandrovich |
ru_RU |
dc.date.accessioned |
2017-01-01T00:00:00Z |
ru_RU |
dc.date.available |
2017-01-01T00:00:00Z |
ru_RU |
dc.date.issued |
2017 |
ru_RU |
dc.identifier.citation |
Бедрин О.А., Махмутова А.Н. Using artificial neural network in machine translation / О.А. Бедрин, А.Н. Махмутова // Информационные технологии в исследовательском пространстве разноструктурных языков: сборник I междунар. интернет-конференции молодых ученых. – Казань, 2017. - С. 34-37 |
ru_RU |
dc.identifier.uri |
https://repository.kpfu.ru/eng/?p_id=153401&p_lang=2 |
ru_RU |
dc.description.abstract |
Информационные технологии в исследовательском пространстве разноструктурных языков: |
ru_RU |
dc.description.abstract |
Each method of machine translation has a number of the shortcomings and the need for their elimination proceeds from an urgent requirement of automation of the work of translators. The goal of this paper is to examine how artificial neural network (ANN) can progress machine translation. The focus of our research is on principles of the work of ANN, with
the aim of answering the question whether or not ANN can be effectively used in machine translation. In order to conduct the research, several specific architectures were discussed and the appropriate candidate for writing a test program was selected. The pilot study involved translation of English phrases into Russian and vice versa. Methodology used for conducting the pilot study took in a laptop and a number of deep machine learning technologies. The data obtained from the experiment showed effectiveness of using ANN for machine. |
ru_RU |
dc.language.iso |
ru |
ru_RU |
dc.subject |
artificial neural network (ANN) |
ru_RU |
dc.subject |
feedforward neural network (FFNN) |
ru_RU |
dc.subject |
recurrent
neural network (RNN) |
ru_RU |
dc.subject |
long-short term memory (LSTM) |
ru_RU |
dc.subject |
machine learning |
ru_RU |
dc.subject |
neuron |
ru_RU |
dc.title |
Using artificial neural network in machine translation |
ru_RU |
dc.type |
Articles in Russian journals and collections |
ru_RU |
|