word-embedding

问题 I have trained fasttext model with Gensim over the corpus of very short sentences (up to 10 words). I know that my test set includes words that are not in my train corpus, i.e some of the words in my corpus are like "Oxytocin" "Lexitocin", "Ematrophin",'Betaxitocin" given a new word in the test set, fasttext knows pretty well to generate a vector with high cosine-similarity to the other similar words in the train set by using the characters level n-gram How do i incorporate the fasttext model

来源： https://stackoverflow.com/questions/59865719/how-to-find-the-closest-word-to-a-vector-using-bert

来源： https://stackoverflow.com/questions/59865719/how-to-find-the-closest-word-to-a-vector-using-bert

来源： https://stackoverflow.com/questions/59865719/how-to-find-the-closest-word-to-a-vector-using-bert

来源： https://stackoverflow.com/questions/55619176/how-to-cluster-similar-sentences-using-bert

来源： https://stackoverflow.com/questions/55619176/how-to-cluster-similar-sentences-using-bert

来源： https://stackoverflow.com/questions/58337469/how-to-save-fasttext-model-in-vec-format

来源： https://stackoverflow.com/questions/58337469/how-to-save-fasttext-model-in-vec-format

来源： https://stackoverflow.com/questions/57033566/how-to-train-a-word-embedding-representation-with-gensim-fasttext-wrapper

来源： https://stackoverflow.com/questions/57033566/how-to-train-a-word-embedding-representation-with-gensim-fasttext-wrapper