句子或文档如何转换为向量? [英] How can a sentence or a document be converted to a vector?

问题描述

我们有用于将单词转换为向量的模型(例如word2vec模型).是否存在类似的模型，可能使用针对单个单词学习的向量，将句子/文档转换为向量?

We have models for converting words to vectors (for example the word2vec model). Do similar models exist which convert sentences/documents into vectors, using perhaps the vectors learnt for the individual words?

推荐答案

1)跳过gram方法: google word2vec

1) Skip gram method: paper here and the tool that uses it, google word2vec

2)使用 LSTM-RNN 形成句子的语义表示.

2) Using LSTM-RNN to form semantic representations of sentences.

3)

3) Representations of sentences and documents. The Paragraph vector is introduced in this paper. It is basically an unsupervised algorithm that learns fixed-length feature representations from variable-length pieces of texts, such as sentences, paragraphs, and documents.

4)尽管此纸并不构成句子/段落向量，但这样做很简单.只需插入各个单词向量即可(手套

4) Though this paper does not form sentence/paragraph vectors, it is simple enough to do that. One can just plug in the individual word vectors(Glove word vectors are found to give the best performance) and then can form a vector representation of the whole sentence/paragraph.

5)使用 CNN 到总结文档.

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