The fundamental assumption of these supervised systems is that the training data and the data to which the systems are applied are sampled independently and identically from the same distribution. When there is a mismatch between data distributions, the RE performance of these systems tends to degrade dramatically<cite> (Plank and Moschitti, 2013)</cite> .