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 -- Fundamental Theory and Methods of Computational Linguistics -- Arabic Collocation Extraction Based on Hybrid Methods -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Experimental Design for Arabic Collocation Extraction -- 3.1 Definition of Collocation -- 3.2 Method for Arabic Collocation Extraction -- 4 Results and Analysis -- 5 Conclusion -- References -- Employing Auto-annotated Data for Person Name Recognition in Judgment Documents -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Data Collection and Annotation -- 3.1 Human-annotated Data -- 3.2 Auto-annotated Data -- 4 Methodology -- 4.1 LSTM Model for Name Recognition -- 4.2 Joint Learning for Person Name Recognition via Aux-LSTM -- 5 Experimentation -- 5.1 Experimental Settings -- 5.2 Experimental Results -- 6 Conclusion -- Acknowledgments -- References -- Closed-Set Chinese Word Segmentation Based on Convolutional Neural Network Model -- 1 Introduction -- 2 The Proposed Model -- 2.1 Shallow Reprensentations -- 2.2 Deep Representations -- 2.3 Tag Scores -- 2.4 Dropout -- 2.5 Tag Prediction and Word Segmentation -- 2.6 Model Training -- 3 Experiments -- 3.1 Results -- 3.2 Ablation Analysis -- 4 Conclusion -- References -- Improving Word Embeddings for Low Frequency Words by Pseudo Contexts -- 1 Introduction -- 2 The Empirical Relation -- 2.1 Semantic Nearest-Neighbors -- 2.2 Semantic Density -- 3 Invariance of the Relation -- 3.1 Corpus Size -- 3.2 Dimension of Word Embeddings -- 3.3 Different Languages -- 3.4 General Discussion -- 4 Pseudo-context Word Embedding -- 5 Experiments -- 6 Conclusion and Future Works -- References -- A Pipelined Pre-training Algorithm for DBNs -- Abstract -- 1 Introduction -- 2 Related Work -- 3 DBN and Greedy Layer-Wise Algorithm -- 4 Pipelined Pre-training Algorithm -- 5 Experiment

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