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» Structural Correspondence Learning for Dependency Parsing
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EMNLP
2009
13 years 2 months ago
An Empirical Study of Semi-supervised Structured Conditional Models for Dependency Parsing
This paper describes an empirical study of high-performance dependency parsers based on a semi-supervised learning approach. We describe an extension of semisupervised structured ...
Jun Suzuki, Hideki Isozaki, Xavier Carreras, Micha...
EMNLP
2006
13 years 6 months ago
Domain Adaptation with Structural Correspondence Learning
Discriminative learning methods are widely used in natural language processing. These methods work best when their training and test data are drawn from the same distribution. For...
John Blitzer, Ryan T. McDonald, Fernando Pereira
ACL
2008
13 years 6 months ago
Semi-Supervised Convex Training for Dependency Parsing
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
Qin Iris Wang, Dale Schuurmans, Dekang Lin
ACL
2003
13 years 6 months ago
Probabilistic Parsing for German Using Sister-Head Dependencies
We present a probabilistic parsing model for German trained on the Negra treebank. We observe that existing lexicalized parsing models using head-head dependencies, while successf...
Amit Dubey, Frank Keller
INTERSPEECH
2010
12 years 12 months ago
Using dependency parsing and machine learning for factoid question answering on spoken documents
This paper presents our experiments in question answering for speech corpora. These experiments focus on improving the answer extraction step of the QA process. We present two app...
Pere Comas, Jordi Turmo, Lluís Màrqu...