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» Making Tree Kernels Practical for Natural Language Learning
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EACL
2006
ACL Anthology
14 years 11 months ago
Online Learning of Approximate Dependency Parsing Algorithms
In this paper we extend the maximum spanning tree (MST) dependency parsing framework of McDonald et al. (2005c) to incorporate higher-order feature representations and allow depen...
Ryan T. McDonald, Fernando C. N. Pereira
77
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IJCNLP
2005
Springer
15 years 3 months ago
Exploring Syntactic Relation Patterns for Question Answering
Abstract. In this paper, we explore the syntactic relation patterns for opendomain factoid question answering. We propose a pattern extraction method to extract the various relatio...
Dan Shen, Geert-Jan M. Kruijff, Dietrich Klakow
ECML
2003
Springer
15 years 2 months ago
Learning Context Free Grammars in the Limit Aided by the Sample Distribution
We present an algorithm for learning context free grammars from positive structural examples (unlabeled parse trees). The algorithm receives a parameter in the form of a finite se...
Yoav Seginer
ACL
2010
14 years 7 months ago
Efficient Inference through Cascades of Weighted Tree Transducers
Weighted tree transducers have been proposed as useful formal models for representing syntactic natural language processing applications, but there has been little description of ...
Jonathan May, Kevin Knight, Heiko Vogler
JMLR
2008
148views more  JMLR 2008»
14 years 9 months ago
Linear-Time Computation of Similarity Measures for Sequential Data
Efficient and expressive comparison of sequences is an essential procedure for learning with sequential data. In this article we propose a generic framework for computation of sim...
Konrad Rieck, Pavel Laskov