The nature of statistical learning theory
The nature of statistical learning theory
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
A systematic comparison of various statistical alignment models
Computational Linguistics
Stochastic inversion transduction grammars and bilingual parsing of parallel corpora
Computational Linguistics
A syntax-based statistical translation model
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Discriminative training and maximum entropy models for statistical machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Minimum error rate training in statistical machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Learning non-isomorphic tree mappings for machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 2
The Alignment Template Approach to Statistical Machine Translation
Computational Linguistics
A study on convolution kernels for shallow semantic parsing
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
A hierarchical phrase-based model for statistical machine translation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Kernel-based pronoun resolution with structured syntactic knowledge
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Maximum entropy based phrase reordering model for statistical machine translation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
A clustered global phrase reordering model for statistical machine translation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
A composite kernel to extract relations between entities with both flat and structured features
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Reordering constraints for phrase-based statistical machine translation
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Improving a statistical MT system with automatically learned rewrite patterns
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Local phrase reordering models for statistical machine translation
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
A linguistically annotated reordering model for BTG-based statistical machine translation
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Syntactic reordering integrated with phrase-based SMT
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Grammar comparison study for translational equivalence modeling and statistical machine translation
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
SPMT: statistical machine translation with syntactified target language phrases
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Statistical machine reordering
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
A discriminative model for tree-to-tree translation
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Forest-based translation rule extraction
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A simple and effective hierarchical phrase reordering model
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A unigram orientation model for statistical machine translation
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
Discriminative reordering models for statistical machine translation
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
Convolution kernel over packed parse forest
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Dependency-based bracketing transduction grammar for statistical machine translation
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Exploiting discourse information to identify paraphrases
Expert Systems with Applications: An International Journal
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Structured syntactic knowledge is important for phrase reordering. This paper proposes using convolution tree kernel over source parse tree to model structured syntactic knowledge for BTG-based phrase reordering in the context of statistical machine translation. Our study reveals that the structured syntactic features over the source phrases are very effective for BTG constraint-based phrase reordering and those features can be well captured by the tree kernel. We further combine the structured features and other commonly-used linear features into a composite kernel. Experimental results on the NIST MT-2005 Chinese-English translation tasks show that our proposed phrase reordering model statistically significantly outperforms the baseline methods.