Abstract
This Compared with the traditional text classification model, the Tibetan text classification based on N-Gram model has adopted N-Gram model in terms of the level of word. In other words, during the text classification, word segmentation is not required. Also, feature selection and abundant pre-treatment processes are avoided. This paper not only carried out profound research on N-Gram models, but also discusses the selection of parameter N in the model by adopting Naïve Bayes Multinomial classifier.
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