Clustering Small Text Descriptions
On the top of my head:


with regular clustering techniques you could try to use text-specific distance/similarity measures instead of only considering distinct words as elements. There are hybrid string similarity measures such as SoftTFIDF which take into account character-based and word-based similarity.
use lemmas instead of words in order to facilitate matching of the same concept
for more specific NLP methods you could look at topic modeling and/or word sense induction techniques. The two follow similar ideas in different ways: the former is closer semantically to your case, the latter is meant to work with small context windows similar to your short descriptions size. I'm not sure what is the state of the art nowadays but Latent Semantic Analysis was the standard not so long ago. Afaik these techniques are meant for a quite high amount of data, but they might be worth trying.