We extract new terminology from a text by term validation in a dictionary. Our approach is based on estimating probabilities for previously unseen terms, i.e. not present in a dictionary. To do this we apply several probabilistic models previously not used for term recognition and propose a new one. We apply restriction of domain similarity on terms used for probability estimation and vary the parameters of the models. Performance of our approach is demonstrated using Wikipedia titles vocabulary. 