Abbreviation Classification using machine learning
Look into this package for Python:
https://pypi.python.org/pypi/Distance/

You can use this to generate a numeric value representing the similarity between word.

Here is a similar post that should help:
https://stats.stackexchange.com/questions/123060/clustering-a-long-list-of-strings-words-into-similarity-groups

Additionally, a level up in complexity would be to use t-SNE on an array generated using word2vec (this is word embedding).  Examples and resources for this are:
https://www.codeproject.com/tips/788739/visualization-of-high-dimensional-data-using-t-sne
http://sebastianruder.com/word-embeddings-1/