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On the Copying Behaviors of Pre-Training for Neural Machine Translation ...
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Norm-Based Curriculum Learning for Neural Machine Translation ...
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Shared-Private Bilingual Word Embeddings for Neural Machine Translation ...
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Unsupervised Neural Dialect Translation with Commonality and Diversity Modeling ...
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Towards Bidirectional Hierarchical Representations for Attention-Based Neural Machine Translation ...
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A Relationship: Word Alignment, Phrase Table, and Translation Quality
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iSentenizer-μ: Multilingual Sentence Boundary Detection Model
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Unsupervised Quality Estimation Model for English to German Translation and Its Application in Extensive Supervised Evaluation
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A Systematic Comparison of Data Selection Criteria for SMT Domain Adaptation
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15 |
Unsupervised Chunking Based on Graph Propagation from Bilingual Corpus
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Abstract:
This paper presents a novel approach for unsupervised shallow parsing model trained on the unannotated Chinese text of parallel Chinese-English corpus. In this approach, no information of the Chinese side is applied. The exploitation of graph-based label propagation for bilingual knowledge transfer, along with an application of using the projected labels as features in unsupervised model, contributes to a better performance. The experimental comparisons with the state-of-the-art algorithms show that the proposed approach is able to achieve impressive higher accuracy in terms of F-score.
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Keyword:
Research Article
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URL: https://doi.org/10.1155/2014/401943 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3977424 http://www.ncbi.nlm.nih.gov/pubmed/24772017
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