I'm trying to use doc2vec(gensim) to identify the most similar sentence and get its label. That is, for example, when the data is composed of 36 types of TVs (each sentence explains a specific product and its labeled to that product), the doc2vec categorizes the user input and decides what TV the user is referring to.
I only know how to get the most similar word: model.most_similar('red/noun') How can you, instead of words, get the most similar sentence and its label?
Doc2Vec - How to label the paragraphs (gensim) (this tells that the above method is actually possible in doc2vec)
Thank you :)