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Modeling a modern POS tagger using HMM and Viterbi Algorithm

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The paper presents a modern way of an improved POS tagger which was modeled by using Hidden Markov Model and Viterbi Algorithm. The algorithm provides ideas for handling unknown words. This issue is caused by such words that have the same spelling but relate to complete different parts of speech and have various meanings. The accuracy of such POS tagger exceeds 96%. Such algorithm’s accuracy was analyzed to other existing algorithms and suggestions were provided.

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