An approach for a next-word prediction for Ukrainian language

Khrystyna Shakhovska, Iryna Dumyn, Natalia Kryvinska, Mohan Krishna Kagita

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)
18 Downloads (Pure)


Text generation, in particular, next-word prediction, is convenient for users because it helps to type without errors and faster. Therefore, a personalized text prediction system is a vital analysis topic for all languages, primarily for Ukrainian, because of limited support for the Ukrainian language tools. LSTM and Markov chains and their hybrid were chosen for next-word prediction. Their sequential nature (current output depends on previous) helps to successfully cope with the next-word prediction task. The Markov chains presented the fastest and adequate results. The hybrid model presents adequate results but it works slowly. Using the model, user can generate not only one word but also a few or a sentence or several sentences, unlike T9.

Original languageEnglish
Article number5886119
Number of pages10
JournalWireless Communications and Mobile Computing
Publication statusPublished - 15 Aug 2021
Externally publishedYes


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