# Categorise sentences based on their semantic similarity

I have a set of unique sentences. For each sentence I calculate a semantic similarity score (between 0 to 1) with the remaining sentences as mentioned in the below example.

E.g.,

Dataset = {sen1, sen2, sen3, sen4,..., senN}


For sen1 I calculate pairwise semantic similarity scores as follows.

sen1 and sen2 = 0.3
sen1 and sen3 = 0.7
sen1 and sen4 = 0.9
...
...
...
sen1 and senN = 1.0


Likewise for all the sentences I calculate pairwise semantic similarity scores.

Since, I am getting a pairwise value, is it possible to cluster these sentences? Also what is the most appropriate clustering technique in my situation?

(I want to cluster sentences based on the similarity value I have and also I consider values above 0.5 as semantically similar sentences.)