Learning to Parse Natural Language with Maximum Entropy Models
Machine Learning - Special issue on natural language learning
Discriminative Reranking for Natural Language Parsing
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
Robust probabilistic predictive syntactic processing: motivations, models, and applications
Robust probabilistic predictive syntactic processing: motivations, models, and applications
Probabilistic top-down parsing and language modeling
Computational Linguistics
Estimation of probabilistic context-free grammars
Computational Linguistics
PCFG models of linguistic tree representations
Computational Linguistics
Natural Language Engineering
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NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
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ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
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ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
On minimizing training corpus for parser acquisition
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Statistical parsing with a context-free grammar and word statistics
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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A two-stage approach to domain adaptation for statistical classifiers
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Extracting Protein-Protein Interactions from MEDLINE using the Hidden Vector State model
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Extending boosting for large scale spoken language understanding
Machine Learning
A framework for classifier adaptation and its applications in concept detection
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Minimally lexicalized dependency parsing
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Porting statistical parsers with data-defined kernels
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Structural correspondence learning for parse disambiguation
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
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EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Domain adaptation with latent semantic association for named entity recognition
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
IWPT '07 Proceedings of the 10th International Conference on Parsing Technologies
Domain adaptation for statistical classifiers
Journal of Artificial Intelligence Research
Proceedings of the 18th ACM conference on Information and knowledge management
MAP adaptation of stochastic grammars
Computer Speech and Language
Proceedings of the third international workshop on Data and text mining in bioinformatics
Exploiting heterogeneous treebanks for parsing
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Learning and Domain Adaptation
DS '09 Proceedings of the 12th International Conference on Discovery Science
Coping with Distribution Change in the Same Domain Using Similarity-Based Instance Weighting
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Multiple source adaptation and the Rényi divergence
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Learning and domain adaptation
ALT'09 Proceedings of the 20th international conference on Algorithmic learning theory
Object Recognition in 3D Point Clouds Using Web Data and Domain Adaptation
International Journal of Robotics Research
DANLP 2010 Proceedings of the 2010 Workshop on Domain Adaptation for Natural Language Processing
Domain adaptation with unlabeled data for dialog act tagging
DANLP 2010 Proceedings of the 2010 Workshop on Domain Adaptation for Natural Language Processing
Semantic role labeling for news tweets
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
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HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Parsing natural language queries for life science knowledge
BioNLP '11 Proceedings of BioNLP 2011 Workshop
Cross-Domain Effects on Parse Selection for Precision Grammars
Research on Language and Computation
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
International Journal of Data Mining and Bioinformatics
Analyzing Urdu social media for sentiments using transfer learning with controlled translations
LSM '12 Proceedings of the Second Workshop on Language in Social Media
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This paper investigates adapting a lexicalized probabilistic context-free grammar (PCFG) to a novel domain, using maximum a posteriori (MAP) estimation. The MAP framework is general enough to include some previous model adaptation approaches, such as corpus mixing in Gildea (2001), for example. Other approaches falling within this framework are more effective. In contrast to the results in Gildea (2001), we show F-measure parsing accuracy gains of as much as 2.5% for high accuracy lexicalized parsing through the use of out-of-domain treebanks, with the largest gains when the amount of indomain data is small. MAP adaptation can also be based on either supervised or unsupervised adaptation data. Even when no in-domain treebank is available, unsupervised techniques provide a substantial accuracy gain over unadapted grammars, as much as nearly 5% F-measure improvement.