This paper explores methods for increasing performance of CRF models, with a particular concern for transfer learning. We consider in particular the transfer case from political news to hard-to-tag business news, and show the effectiveness of several methods, including a novel semi-supervised approach.
['Marc B. Vilain', 'Jonathan H. Huggins', 'Ben Wellner']
Sources of Performance in CRF Transfer Training: a Business Name-tagging Case Study