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ACL
2006

Semantic Parsing with Structured SVM Ensemble Classification Models

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Semantic Parsing with Structured SVM Ensemble Classification Models
We present a learning framework for structured support vector models in which boosting and bagging methods are used to construct ensemble models. We also propose a selection method which is based on a switching model among a set of outputs of individual classifiers when dealing with natural language parsing problems. The switching model uses subtrees mined from the corpus and a boosting-based algorithm to select the most appropriate output. The application of the proposed framework on the domain of semantic parsing shows advantages in comparison with the original large margin methods.
Minh Le Nguyen, Akira Shimazu, Xuan Hieu Phan
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where ACL
Authors Minh Le Nguyen, Akira Shimazu, Xuan Hieu Phan
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