Paper: The Necessity of Combining Adaptation Methods

ACL ID D10-1075
Title The Necessity of Combining Adaptation Methods
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2010

Problems stemming from domain adaptation continue to plague the statistical natural lan- guage processing community. There has been continuingworktryingtofindgeneralpurpose algorithms to alleviate this problem. In this paper we argue that existing general purpose approaches usually only focus on one of two issues related to the difficulties faced by adap- tation: 1) difference in base feature statistics or 2) task differences that can be detected with labeled data. We argue that it is necessary to combine these two classes of adaptation algorithms, using evidence collected through theoretical analy- sis and simulated and real-world data exper- iments. We find that the combined approach often outperforms the individual adaptation approaches. By combining simple approaches from each class of...