Character Level Embeddings I am working on a problem that current depends on word level embeddings created using Word2Vec. I am researching new methods to apply to this model and one was a character level embedding. I have not found much information on it, and I don't imagine Word2Vec but at a character level would be effective. Is there any insight on giving vector representations to characters for an overall classification model?
For the sake of completeness, fastText uses sub-word information (character level n-grams) when creating embeddings and then for classification with some interesting results:


can give prediction for the unknown words that have some similarity with known ones
with interesting results for modelling syntactic relations like 'went' - 'go' + 'give' = 'gave'