Could I use BERT to Cluster phrases with pre-trained model
I found it was a failure that I had used Gensim with GoogleNews pre-trained model to cluster phrases like:


knitting
knit loom
loom knitting
weaving loom
rainbow loom
home decoration accessories
loom knit/knitting loom
...


I am advised that GoogleNews model does't have the phrases in it. The phrases I have are a little specific to GoogleNews model while I don't have corpus to train a new model. I have only the phrases. And now I am considering to turn to BERT. But could BERT do that as I expected as above? Thank you.

You can feed a phrase into the pretrained BERT model and get an embedding, i.e. a fixed-dimension vector. So BERT can embed your phrases in a space. Then you can use a clustering algorithm (such as k-means) to cluster the phrases. The phrases do not need to occur in the training corpus of BERT, as long as the words they consist of are in the vocabulary. You will have to try to see if the embeddings give you relevant results.
