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ECML
2006
Springer
13 years 8 months ago
Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees
In this paper, we provide a study on the use of tree kernels to encode syntactic parsing information in natural language learning. In particular, we propose a new convolution kerne...
Alessandro Moschitti
ACL
2010
13 years 2 months ago
Dynamic Programming for Linear-Time Incremental Parsing
Incremental parsing techniques such as shift-reduce have gained popularity thanks to their efficiency, but there remains a major problem: the search is greedy and only explores a ...
Liang Huang, Kenji Sagae
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
2001
13 years 6 months ago
Grammars for Local and Long Dependencies
Polarized dependency (PD-) grammars are proposed as a means of efficient treatment of discontinuous constructions. PD-grammars describe two kinds of dependencies : local, explicit...
Alexander Ja. Dikovsky
AI
2009
Springer
13 years 8 months ago
Executable Specifications of Fully General Attribute Grammars with Ambiguity and Left-Recursion
Abstract. A top-down parsing algorithm has been constructed to accommodate any form of ambiguous context-free grammar, augmented with semantic rules with arbitrary attribute depend...
Rahmatullah Hafiz