word2vec

How to check if a key exists in a word2vec trained model or not

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Word2Vec also provides a ‘vocab’ member, which you can access directly. Using a pythonistic approach: if word in w2v_model.vocab: # Do something EDIT Since gensim release 2.0, the API for Word2Vec changed. To access the vocabulary you should now use this: if word in w2v_model.wv.vocab: # Do something EDIT 2 The attribute ‘wv’ is being … Read more

How to use Gensim doc2vec with pre-trained word vectors?

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Note that the “DBOW” (dm=0) training mode doesn’t require or even create word-vectors as part of the training. It merely learns document vectors that are good at predicting each word in turn (much like the word2vec skip-gram training mode). (Before gensim 0.12.0, there was the parameter train_words mentioned in another comment, which some documentation suggested … Read more

How to use word2vec to calculate the similarity distance by giving 2 words?

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gensim has a Python implementation of Word2Vec which provides an in-built utility for finding similarity between two words given as input by the user. You can refer to the following: Intro: http://radimrehurek.com/gensim/models/word2vec.html Tutorial: http://radimrehurek.com/2014/02/word2vec-tutorial/ UPDATED: Gensim 4.0.0 and above The syntax in Python for finding similarity between two words goes like this: >> from gensim.models … Read more

How can a sentence or a document be converted to a vector?

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1) Skip gram method: paper here and the tool that uses it, google word2vec 2) Using LSTM-RNN to form semantic representations of sentences. 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 … Read more

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