Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data

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Intro -- Preface -- Organization -- Contents -- Semantics -- Improving Chinese Semantic Role Labeling with English Proposition Bank -- 1 Introduction -- 2 Related Work -- 3 Two-Pass Training Approach -- 3.1 Basic Idea -- 3.2 Bilingual Word Representation -- 3.3 Basic SRL Model -- 3.4 Training Criteria -- 4 Experiments -- 4.1 Experiment Settings -- 4.2 SRL Results -- 4.3 Translation Equivalent Regularizer -- 5 Conclusion -- References -- Transition-Based Chinese Semantic Dependency Graph Parsing -- 1 Introduction -- 2 Methods -- 2.1 Tree-Based Method -- 2.2 Dependency Graph Parser -- 3 Experiments -- 3.1 Datasets -- 3.2 Results -- 3.3 Discussions -- 4 Related Works -- 5 Conclusion -- References -- Improved Graph-Based Dependency Parsing via Hierarchical LSTM Networks -- 1 Introduction -- 2 Neural Network Model -- 2.1 Word Representation -- 2.2 Score Model -- 2.3 Neural Training -- 3 Experiments -- 3.1 Experiments Setup -- 3.2 Experiments Results -- 4 Conclusion -- References -- Machine Translation -- Error Analysis of English-Chinese Machine Translation -- Abstract -- 1 Categorization of Errors in Machine Translation -- 2 NT Clause, SV Clause and Non-SV Clause -- 3 Analysis of Errors in English-Chinese Machine Translation -- 4 Statistics and Analysis of Errors in English-Chinese Machine Translation -- 4.1 Analysis of Error Types -- 4.2 Comparison Between Whole Sentence Translation and NT Clause Translation -- 4.3 Correlation Between the NT Clause Number in a Sentence and the Error Number in Its Whole-Sentence Translation -- 5 Discussion -- Acknowledgements -- References -- I Can Guess What You Mean: A Monolingual Query Enhancement for Machine Translation -- 1 Introduction -- 2 Our Model -- 2.1 TFIDF -- 2.2 Latent Semantic Indexing -- 2.3 NN Word Embedding -- 3 Experiments -- 3.1 Experimental Settings -- 3.2 Results -- 3.3 Discussion

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