# short text categorization with spelling correction

I am building a classifier for short texts in a chat system. My features are words and pairs of words.

Naturally, the sentences contain spelling mistakes. If a particular wrong spelling of a certain word hasn't appeared in the training corpus, the classifier has no chance to identify it.

I consider taking an existing spelling corrector, and integrate it with my current classifier, but I am not sure how to do it.

Do you know of a paper that integrates an automatic spelling correction tool with a short text classifier?

It you really want to incorporate the correction into your model, it would seem that you can re-define edit distance to compute the log-probability of some misspelled word matching another for some mismatch probability $\theta \sim \text{Beta}(\alpha, \beta)$.
The resulting probabilities can then be incorporated into the classifier directly, which would be parameterized by $\theta$. Depending on how complex your internal model is, you could find the ML or MAP estimate $\hat{\theta}$ by some EM algorithm, or if the model allows, analytically.