There are mainly 2 reasons Some pair of words always occur together more often than they occur individually. Hence it is important to treat such co-occurring words as a single entity or a single token in training. For named entity recognition problem, Tokens such as “United States”, “North America”, “Red Wine” would make sense when…
Why are bigrams or any n-grams important in NLP(task like sentiment classification or spam detection) or important enough to find them explicitly?
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