gensim

Finding the distance between 'Doctag' and 'infer_vector' with Gensim Doc2Vec?

由 送分小仙女□ 提交于 2021-01-28 11:48:51
问题 Using Gensim's Doc2Vec how would I find the distance between a Doctag and an infer_vector() ? Many thanks 回答1: Doctag is the internal name for the keys to doc-vectors. The result of an infer_vector() operation is a vector. So as you've literally asked, these aren't comparable. You could ask a model for a known doc-vector, by its doc-tag key that was supplied during training, via model.docvecs[doctag] . That would be comparable to the result of an infer_vector() call. With two vectors in hand,

Understanding gensim word2vec's most_similar

由 為{幸葍}努か 提交于 2021-01-28 10:50:30
问题 I am unsure how I should use the most_similar method of gensim's Word2Vec. Let's say you want to test the tried-and-true example of: man stands to king as woman stands to X ; find X. I thought that is what you could do with this method, but from the results I am getting I don't think that is true. The documentation reads: Find the top-N most similar words. Positive words contribute positively towards the similarity, negative words negatively. This method computes cosine similarity between a

Understanding gensim word2vec's most_similar

由 一世执手 提交于 2021-01-28 10:48:53
问题 I am unsure how I should use the most_similar method of gensim's Word2Vec. Let's say you want to test the tried-and-true example of: man stands to king as woman stands to X ; find X. I thought that is what you could do with this method, but from the results I am getting I don't think that is true. The documentation reads: Find the top-N most similar words. Positive words contribute positively towards the similarity, negative words negatively. This method computes cosine similarity between a

gensim save load model deprecation warning

由 ぐ巨炮叔叔 提交于 2021-01-27 17:10:34
问题 I get the following deprecation warning when saving/loading a gensim word embedding: model.save("mymodel.model") /home/.../lib/python3.7/site-packages/smart_open/smart_open_lib.py:398: UserWarning: This function is deprecated, use smart_open.open instead. See the migration notes for details: https://github.com/RaRe-Technologies/smart_open/blob/master/README.rst#migrating-to-the-new-open-function 'See the migration notes for details: %s' % _MIGRATION_NOTES_URL I don't understand what to do

维基百科语料中的词语相似度探索

由 戏子无情 提交于 2021-01-23 04:54:39
之前写过《 中英文维基百科语料上的Word2Vec实验 》，近期有不少同学在这篇文章下留言提问，加上最近一些工作也与 Word2Vec 相关，于是又做了一些功课，包括重新过了一遍Word2Vec的相关资料，试了一下gensim的相关更新接口，google了一下" wikipedia word2vec " or " 维基百科 word2vec " 相关的英中文资料，发现多数还是走得这篇文章的老路，既通过gensim提供的维基百科预处理脚本"gensim.corpora.WikiCorpus"提取维基语料，每篇文章一行文本存放，然后基于 gensim 的Word2Vec模块训练词向量模型。这里再提供另一个方法来处理维基百科的语料，训练词向量模型，计算词语相似度（ Word Similarity )。关于Word2Vec, 如果英文不错，推荐从这篇文章入手读相关的资料: Getting started with Word2Vec 。 这次我们仅以英文维基百科语料为例，首先依然是下载维基百科的最新XML打包压缩数据，在这个英文最新更新的数据列表下： https://dumps.wikimedia.org/enwiki/latest/ ，找到 " enwiki-latest-pages-articles.xml.bz2 " 下载，这份英文维基百科全量压缩数据的打包时间大概是2017年4月4号

How to get word2index from gensim

由 两盒软妹~` 提交于 2021-01-21 03:48:49
问题 By doc we can use this to read a word2vec model with genism model = KeyedVectors.load_word2vec_format('word2vec.50d.txt', binary=False) This is an index-to-word mapping, that is, e.g., model.index2word[2] , how to derive an inverted mapping (word-to-index) based on this? 回答1: The mappings from word-to-index are in the KeyedVectors vocab property, a dictionary with objects that include an index property. For example: word = "whatever" # for any word in model i = model.vocab[word].index model

How to get word2index from gensim

由 牧云@^-^@ 提交于 2021-01-21 03:47:30
问题 By doc we can use this to read a word2vec model with genism model = KeyedVectors.load_word2vec_format('word2vec.50d.txt', binary=False) This is an index-to-word mapping, that is, e.g., model.index2word[2] , how to derive an inverted mapping (word-to-index) based on this? 回答1: The mappings from word-to-index are in the KeyedVectors vocab property, a dictionary with objects that include an index property. For example: word = "whatever" # for any word in model i = model.vocab[word].index model

How to get word2index from gensim

由 五迷三道 提交于 2021-01-21 03:47:20
问题 By doc we can use this to read a word2vec model with genism model = KeyedVectors.load_word2vec_format('word2vec.50d.txt', binary=False) This is an index-to-word mapping, that is, e.g., model.index2word[2] , how to derive an inverted mapping (word-to-index) based on this? 回答1: The mappings from word-to-index are in the KeyedVectors vocab property, a dictionary with objects that include an index property. For example: word = "whatever" # for any word in model i = model.vocab[word].index model

what does the vector of a word in word2vec represents?

由 南笙酒味 提交于 2021-01-20 14:17:50
问题 word2vec is a open source tool by Google: For each word it provides a vector of float values, what exactly do they represent? There is also a paper on paragraph vector can anyone explain how they are using word2vec in order to obtain fixed length vector for a paragraph. 回答1: TLDR : Word2Vec is building word projections ( embeddings ) in a latent space of N dimensions, (N being the size of the word vectors obtained). The float values represents the coordinates of the words in this N

what does the vector of a word in word2vec represents?

由 别说谁变了你拦得住时间么 提交于 2021-01-20 14:17:27
问题 word2vec is a open source tool by Google: For each word it provides a vector of float values, what exactly do they represent? There is also a paper on paragraph vector can anyone explain how they are using word2vec in order to obtain fixed length vector for a paragraph. 回答1: TLDR : Word2Vec is building word projections ( embeddings ) in a latent space of N dimensions, (N being the size of the word vectors obtained). The float values represents the coordinates of the words in this N
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