Best practical algorithm for sentence similarity I have two sentences, S1 and S2, both which have a word count (usually) below 15.

What are the most practically useful and successful (machine learning) algorithms, which are possibly easy to implement (neural network is ok, unless the architecture is as complicated as Google Inception etc.).

I am looking for an algorithm that will work fine without putting too much time into it. Are there any algorithms you've found successful and easy to use? 

This can, but does not have to fall into the category of clustering. My background is from machine learning, so any suggestions are welcome :)
Cosine Similarity for Vector Space could be you answer.
Or you could calculate the eigenvector of each sentences. But the Problem is, what is similarity?
&quot;This is a tree&quot;,
&quot;This is not a tree&quot;
If you want to check the semantic meaning of the sentence you will need a wordvector dataset. With the wordvector dataset you will able to check the relationship between words. Example: (King - Man + woman = Queen)
Siraj Raval has a good python notebook for creating wordvector datasets.