We demonstrated that a machine learning approach can overcome the problem of sparse data which is closely related to the productivity of compounding.
by exploiting information about frequent compounds or frequent contexts (which can be easily retrieved from the corpus) we can indirectly recreate evidence about the likelihood of two nouns to form a valid com-pound without necessarily relying on parsed text.