Self-training provides a direct solution to the lack of labelled data in the target do-main in UDA (McClosky et al., 2006;Reichart and Rappoport, 2007;Drury et al., 2011).
the source domain's labelled instances are used to initialise the self-training process and during subsequent iterations labels are inferred for the target domain's unlabelled instances, which can be used to train a classifier for the task of interest.