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TnT is an efficient statistical Parts-of-speech (POS) Tagger based on Hidden Markov Model. TnT performs well on known word sequences. But, the performance degrades with increase in the number of unknown words. In this paper, we propose a method to overcome this performance degradation using fuzzy rules. Fuzzy rule based model is designed to provide TnT with(More)
TnT is an efficient statistical Parts-of-speech (POS) Tagger based on Hidden Markov Model. TnT stands for Trigrams`n'Tags. Viterbi algorithm is used for finding the best tag sequence for a given observation sequence of words. TnT performs well on known word sequences. But, the performance degrades with increase in the number of unknown words. In this paper,(More)
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