<p>Facebook Research group released a new solution called InferSent 
Results and code are published on Github, check their repo. It is pretty awesome. I am planning to use it. 
<a href="https://github.com/facebookresearch/InferSent" rel="nofollow noreferrer">https://github.com/facebookresearch/InferSent</a> </p>

<p>their paper
<a href="https://arxiv.org/abs/1705.02364" rel="nofollow noreferrer">https://arxiv.org/abs/1705.02364</a> 
Abstract: 
Many modern NLP systems rely on word embeddings, previously trained in an unsupervised manner on large corpora, as base features. Efforts to obtain embeddings for larger chunks of text, such as sentences, have however not been so successful. Several attempts at learning unsupervised representations of sentences have not reached satisfactory enough performance to be widely adopted. In this paper, we show how universal sentence representations trained using the supervised data of the Stanford Natural Language Inference datasets can consistently outperform unsupervised methods like SkipThought vectors on a wide range of transfer tasks. Much like how computer vision uses ImageNet to obtain features, which can then be transferred to other tasks, our work tends to indicate the suitability of natural language inference for transfer learning to other NLP tasks. Our encoder is publicly available.</p>
How to calculate the sentence similarity using word2vec model of gensim with python
<p>According to the <a href="http://radimrehurek.com/gensim/models/word2vec.html" rel="noreferrer">Gensim Word2Vec</a>, I can use the word2vec model in gensim package to calculate the similarity between 2 words.</p>

<p>e.g.</p>

<pre><code>trained_model.similarity('woman', 'man') 
0.73723527
</code></pre>

<p>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?</p>