Hash kernels are a method of representing very large sparse feature vectors. But with a little imagination, they can serve as a way to represent just about any kind of feature.
Machine learning datasets obtained from the UCI Machine Learning Repository made experimenting with hash kernels incredibly easy. Details:
Frank, A. & Asuncion, A. (2010). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.