| N06-1020 | for parsing can be helpful for | parser adaptation | . 3 Experimental Setup Our parsing |
| P06-1043 | 2006 ) applies self-training to | parser adaptation | to utilize unlabeled in-domain |
| P06-1043 | present some encouraging results on | parser adaptation | without any in-domain data . |
| P06-1043 | are many different approaches to | parser adaptation | . Steedman et al. ( 2003 ) apply |
| D09-1086 | and cross-lingual ( § 4 ) | parser adaptation | . Finally , we present experiments |
| N10-1004 | of self-training for improving | parser adaptation | . If we excluded all self-trained |
| P06-1043 | data . 2 Related Work Work in | parser adaptation | is premised on the assumption |
| D08-1050 | accuracy in other domains , making | parser adaptation | a pressing issue . In this paper |
| P07-1052 | taken from different domains ( the | parser adaptation | scenario ) the ratio of such |
| D09-1086 | Discussion The two related problems of | parser adaptation | and projection are often approached |
| P06-1043 | Reranking and Self-Training for | Parser Adaptation | </title> David McClosky Eugene |
| D08-1050 | . In this paper we investigate | parser adaptation | in the context of lexicalized |
| D09-1086 | the paper . 1 Introduction 1.1 | Parser Adaptation | Consider the problem of learning |
| D09-1086 | very similar to the monolingual | parser adaptation | scenario , but there are a few |
| P06-1043 | created for new genres . Thus , | parser adaptation | attempts to leverage existing |
| N06-1020 | unsupervised learning problem . In | parser adaptation | , one is given annotated training |
| P06-1043 | would be . Thus , most work on | parser adaptation | resorts to using some labeled |
| N06-1019 | . Previous work has attempted | parser adaptation | without relying on treebank data |
| D09-1127 | 2009 ) use constrained EM and | parser adaptation | tech - niques , respectively |
| D08-1050 | domains might behave differently for | parser adaptation | . 1 Introduction Most state-of-the-art |
