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tf-idf与计算句子向量的相关性

[英]How tf-idf is relevant in calculating sentence vectors

I am interested to find sentence vectors using word vectors.I read that by multiplying each word's tf-idf weights with their vectors and finding their average we can get whole sentence vector. 我有兴趣使用单词向量找到句子向量,我读到通过将每个单词的tf-idf权重乘以它们的向量并找到它们的平均值,我们可以获得整个句子向量。

Now I want to know that how these tf-idf weights helps us to get sentence vectors ie how these tf-idf and sentence vector are related? 现在,我想知道这些tf-idf权重如何帮助我们获取句子向量,即这些tf-idf和句子向量之间如何关联?

Any aggregative operation on the word vectors can give you a sentence vector. 对单词向量的任何聚合操作都可以为您提供一个句子向量。 You should consider what do you want your representation to mean and choose the operation accordingly. 您应考虑您希望代表的意思是什么,并相应地选择操作。

Possible operations are summing the vectors, averaging them, concatenating, etc. 可能的操作是对向量求和,取平均值,进行级联等。

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