They showed that, depending on the domain, a small number (e.g., 50) of labeled examples allows to adapt the model learned on another corpus to a new domain.
many applications require reliable processing of heterogeneous corpora, such as the World Wide Web, where the diversity of genres and domains present in the Internet limits the feasibility of in-domain training.