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- W4206191572 abstract "In this paper, part-of-speech tagging on Kazakh text has been implemented using an LSTM neural network with a bidirectional modifier. A quite simple and fast tagger has been built, tested and evaluated on the self-collected dataset of Kazakh sentences with an accuracy of 94 %. There was addressed basically the problem of tagging having a small number of training samples (around 100 Kazakh sentences). It has been shown that quite good accuracy can be achieved in this situation." @default.
- W4206191572 created "2022-01-26" @default.
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- W4206191572 date "2021-11-25" @default.
- W4206191572 modified "2023-09-27" @default.
- W4206191572 title "Part-of-speech tagging of Kazakh text via LSTM network with a bidirectional modifier" @default.
- W4206191572 doi "https://doi.org/10.1109/icecco53203.2021.9663794" @default.
- W4206191572 hasPublicationYear "2021" @default.
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