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你好~感谢你们将你们的工作开源,受贵组论文启示,我想要用自己的语料库训练context为word+char+ngram的SGNS embedding。于是我又看了ngram2vec的论文,发现其根据target和context不同分为:uni_uni, uni_bi, bi_bi... 。CA8中是只用target为uni的uni_bi吗?然后又在context中加入char?如果我想训练context为word+char+ngram的SGNS embedding,如何将char加入到context呢?是要自己在ngram2vec toolkit中自己写代码添加<word,char>对嘛?
The text was updated successfully, but these errors were encountered:
target和context都可以用word+char+ngram,这个项目提供的词向量target大部分都是word,下面的Various Co-occurrence Information有char的。 用ngram2vec训练的话可以自定义target和context,按需求改代码就可以,比较容易的。
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你好~感谢你们将你们的工作开源,受贵组论文启示,我想要用自己的语料库训练context为word+char+ngram的SGNS embedding。于是我又看了ngram2vec的论文,发现其根据target和context不同分为:uni_uni, uni_bi, bi_bi... 。CA8中是只用target为uni的uni_bi吗?然后又在context中加入char?如果我想训练context为word+char+ngram的SGNS embedding,如何将char加入到context呢?是要自己在ngram2vec toolkit中自己写代码添加<word,char>对嘛?
The text was updated successfully, but these errors were encountered: