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这个ngram,是指考虑了word的ngram,还是character的ngram呢?可是常出现的character的ngram,不就是word了吗?不是很理解这个context features是怎么考虑的。求解答,谢谢!
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是word的unigram和bigram以及character的unigram,因为中文的词一般就是两三个字所以用character的ngram和词没什么区别了。
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@shenshen-hungry 好的谢谢,那么再问一下。context feature中word和word+character的区别,是在分词后,前者去掉了分词结果为单个字的情况嘛?
word就是分词意义上的词,word+character是说不但有词还有字。也就是在Skip-gram模型中,中心词不但预测上下文中的词,同时也预测里面的字。
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这个ngram,是指考虑了word的ngram,还是character的ngram呢?可是常出现的character的ngram,不就是word了吗?不是很理解这个context features是怎么考虑的。求解答,谢谢!
The text was updated successfully, but these errors were encountered: