Computer scienceData scienceNLPLanguage representationEmbeddings

Word embeddings

Embeddings characteristics

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Match the statements that are true about word embeddings (excluding TF-IDF and bag-of-words representations).

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There are only two ways of word embeddings training: SkipGram and CBOW

Word2Vec is the only way to get embeddings

If a word was not seen during word embeddings' training, we cannot get its embeddings

Embeddings can be of any shape

Words cannot be divided into parts during word embeddings training

Word embeddings pay attention to the context around a word

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