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Word embedding is the collective name for a set of language modeling and feature learning techniques in NLP where words are mapped to vectors of real numbers in a low dimensional space, relative to the vocabulary size.

1 vote

Alternatives to doc2vec?

Depending on your target task. If you are to classify documents, then e.g. fastText has it's own approach and there are other classification techniques, not strictly generating embeddings, like LSA / …
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1 vote

Word vectors to Sentence Vectors

There is doc2vec algorithm which is modification of word2vec - by the same authors, paper: https://arxiv.org/pdf/1405.4053v2.pdf And it's implemented e.g. in gensim https://radimrehurek.com/gensim/mo …
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