Using unlabeled data to estimate a target distribution for importance sampling, or for semi-supervised learning (Søgaard, 2013), as well as wide-coverage, crowd-sourced tag dictionaries to obtain more robust predictions for out-of-domain data have been succesfully used for domain adaptation Hovy et al., 2015a;Li et al., 2012).
we also see an average increase in performance on known words of 1% for both systems.