Procedure for quantitatively comparing the syntactic coverage of English grammars
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Using register-diversified corpora for general language studies
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Building a large annotated corpus of English: the penn treebank
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Recognizing text genres with simple metrics using discriminant analysis
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Learning to Parse Natural Language with Maximum Entropy Models
Machine Learning - Special issue on natural language learning
Automatic recognition of distinguishing negative indirect history language in judicial opinions
Proceedings of the tenth international conference on Information and knowledge management
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A comparison between supervised learning algorithms for word sense disambiguation
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
An empirical study of the domain dependence of supervised word sense disambiguation systems
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Using a support-vector machine for Japanese-to-English translation of tense, aspect, and modality
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
Reranking and self-training for parser adaptation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
CICLing '09 Proceedings of the 10th International Conference on Computational Linguistics and Intelligent Text Processing
A look at parsing and its applications
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Automatic domain adaptation for parsing
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Detecting errors in automatically-parsed dependency relations
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Genre and domain in patent texts
PaIR '10 Proceedings of the 3rd international workshop on Patent information retrieval
Effective measures of domain similarity for parsing
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
A word clustering approach to domain adaptation: effective parsing of biomedical texts
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
Biased representation learning for domain adaptation
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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A major concern in corpus based approaches is that the applicability of the acquired knowledge may be limited by some feature of the corpus, in particular, the notion of text 'domain'. In order to examine the domain dependence of parsing, in this paper, we report 1) Comparison of structure distributions across domains; 2) Examples of domain specific structures; and 3) Parsing experiment using some domain dependent grammars. The observations using the Brown corpus demonstrate domain dependence and idiosyncrasy of syntactic structure. The parsing results show that the best accuracy is obtained using the grammar acquired from the same domain or the same class (fiction or nonfiction). We will also discuss the relationship between parsing accuracy and the size of training corpus.