Clustering of Word Contexts as a Method of Eliminating Polysemy of Words

Kapitanov, Andrey I.; Kapitanova, Ilona I.; Troyanovskiy, Vladimir M.; Ilyushechkin, Vladimir; Dorogova, Ekaterina

doi:10.1109/eiconrus.2019.8656851

Cited by 2 publications

(1 citation statement)

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“…Research by Kapitanov et al in 2019 [6] proposed "a method of eliminating the polysemy of words based on the clustering of word contexts" in order to improve the quality of text translation into natural language. They reported that, by using this method, it was possible to "improve the algorithms of automatic classification of text documents in natural language" by 1.8%, which amounted to 96.1% overall.…”

Section: Development Of Computer-based Translation Toolsmentioning

confidence: 99%

Some Challenges in Using Computer-Aided Translation Tools to Facilitate Second Language Fluency in Education

Excell¹

2019

AETiC

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At every level of education, from early years to postgraduate, students can arrive in the UK (or US) classroom with little or no English language ability. It is impossible for teachers to have knowledge of every first language that students bring into the classroom and thus they may rely on a computer-aided translation tool so that their students can have access to the English needed in all subjects across the curriculum. At the same time, students need to move from basic English skills in listening, speaking, reading and writing towards the subtleties of academic English which they must achieve in order to reach the UK government’s required standards in English at every level of assessment. Using her extensive knowledge of the challenges that students learning English as an Additional Language (EAL) and their teachers face in the classroom situation and the English needed in assessments, the author examines possible benefits of computer-aided translation tools such as Google Translate and Talking Pen and outlines some of the problems and drawbacks with such tools that create barriers to acquiring full academic fluency, thus posing challenges to future translation tool developers.

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Section: Development Of Computer-based Translation Toolsmentioning

confidence: 99%