Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data - Info and Reading Options

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Intro -- Preface -- Organization -- Contents -- Semantics -- Radical Enhanced Chinese Word Embedding -- Abstract -- 1 Introduction -- 2 Model -- 3 Experiment -- 3.1 Parameter Settings -- 3.2 Word Similarity -- 3.3 Word Analogy -- 4 Relate Work -- 5 Conclusion -- Acknowledgements -- References -- Syntax Enhanced Research Method of Stylistic Features -- 1 Introduction -- 2 Related Work -- 3 Principal Stylistic Feature Analysis -- 3.1 Feature Extraction -- 3.2 Difference Discovery -- 3.3 Mining Internal Relations -- 3.4 Principal Feature Analysis -- 4 Experiment -- 4.1 Experimental Settings -- 4.2 Difference Discovery (RQ1) -- 4.3 Internal Relation Mining (RQ2) -- 4.4 Verification by Classification (RQ3) -- 5 Conclusion -- References -- Addressing Domain Adaptation for Chinese Word Segmentation with Instances-Based Transfer Learning -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Instances-Based Transfer Learning for CWS -- 3.2 Obtaining Unlabeled Target Domain Instances -- 3.3 Obtaining Annotated Result of Instances -- 4 Experiments -- 4.1 Datasets -- 4.2 Hyper-parameter Settings -- 4.3 Experimental Results -- 5 Conclusion -- Acknowledgments -- References -- Machine Translation -- Collaborative Matching for Sentence Alignment -- 1 Introduction -- 2 Problem Statement -- 2.1 Notation -- 2.2 Sentence Length -- 2.3 Sentence Alignment -- 3 Collaborative Matching -- 3.1 An Illustrative Example -- 3.2 Collaborative Similarity -- 3.3 Two Alignment Approaches -- 4 Evaluation -- 4.1 Data Sets -- 4.2 Adaptivity of the Baseline -- 4.3 Alignment by Collaborative Matching -- 5 Related Work -- 6 Conclusion -- References -- Finding Better Subword Segmentation for Neural Machine Translation -- 1 Introduction -- 2 Neural Machine Translation -- 3 Unsupervised Subword Segmentation -- 3.1 Generalized BPE Segmentation -- 3.2 Goodness Measures

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