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Word2Vec generates a feature vector for each word. I was wondering if exist something2vec that generates one feature vector for one document. In this way I could compute the distance between two documents by only comparing two feature vectors.

Thanks.

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Yes, there are such things, but they aren't really related to word2vec.

First of all, Bag of Words is the old "something2vec" approach of representing documents in a vector space. Of course, the resulting vectors are very sparse, and distance does not always behave well in such cases, and it is better to use dot-product based similarities like cosine.

But you can reduce the dimensionality of this vector space with SVD or NMF (Non-Negative Matrix Factorization), and this will give you what you want: dense vectors of small dimensionality for which you can compute the distances.

Then you can go further and use Topic Modelling, which also will give you a vectorial representation of documents, and you can use it for comparing them.

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how about Doc2vec. Mikolov released the journal after the successful attempt of word2vec. A single feature vector for a whole paragraph or sentence or document (depending upon your use case) could be generated. Personally, I didn't get quite good results with it for sentence classification problems. Rather I went with averaged word vectors for sentences.

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