word2vec

I have generated the vectors for a list of tokens from a large document using word2vec. Given a sentence, is it possible to get the vector of the sentence from the vector of the tokens in the sentence. There are differet methods to get the sentence vectors : Doc2Vec : you can train your dataset using Doc2Vec and then use the sentence vectors. Average of Word2Vec vectors : You can just take the average of all the word vectors in a sentence. This average vector will represent your sentence vector. Average of Word2Vec vectors with TF-IDF : this is one of the best approach which I will recommend.

版权声明：本文为博主原创文章，遵循 CC 4.0 by-sa 版权协议，转载请附上原文出处链接和本声明。 本文链接：https://blog.csdn.net/qq_28840013/article/details/89681499 这里，我们不讲word2vec的原理（其实是还了解不透彻，以后明白了再写，大家在阅读本文之前，可以先简单了解一下其推理过程），就只了解其参数和输入输出。网上还有对word2vec用tensorflow进行的实现，以后再说吧。 1.Word2vec作用：表达不同词之间的相似和类比关系 2.安装方法：pip install --upgrade gensim #因为Gensim开发了一套工具箱叫做gensim，里面继承了Word2vec方法。 3.输入参数格式： import gensim #sentences=[["a","b"],["b","c"] ... ] sentences=word2vec.Text8Corpus("test.txt") #text8为语料库文件名 #sentences是训练所需预料，可通过该方式加载，此处训练集为英文文本或分好词的中文文本 1 2 3 4 sentences是训练所需材料，可通过两种格式载入： 1.文本格式： 将每篇文章 分词去停用词后，用空格分割，将其存入txt文本中（每一行一篇文章） 这个格式文本处理后

According to the Gensim Word2Vec , I can use the word2vec model in gensim package to calculate the similarity between 2 words. e.g. trained_model.similarity('woman', 'man') 0.73723527 However, the word2vec model fails to predict the sentence similarity. I find out the LSI model with sentence similarity in gensim, but, which doesn't seem that can be combined with word2vec model. The length of corpus of each sentence I have is not very long (shorter than 10 words). So, are there any simple ways to achieve the goal? This is actually a pretty challenging problem that you are asking. Computing

** 【理论学习】 ** 学习词袋模型概念：离散、高维、稀疏。 学习分布式表示概念：连续、低维、稠密。 https://blog.csdn.net/spring_willow/article/details/81452162 理解word2vec词向量原理并实践，来表示文本。 https://www.leiphone.com/news/201812/2o1E1Xh53PAfoXgD.html word2vec 中的数学原理详解 https://blog.csdn.net/itplus/article/details/37969519 word2vec原理推导与代码分析 http://www.hankcs.com/nlp/word2vec.html 【NLP学习博客】 推荐 | 一份从入门到精通NLP的完整指南 来源： https://blog.csdn.net/qq_15699467/article/details/98985567