Intro
Preface
Organization
Contents
Part II
Natural Language Processing
A Calibration Method for Sentiment Time Series by Deep Clustering
1 Introduction
2 Related Work
3 Methods
3.1 Sentence Embedding
3.2 Representative Sampling
3.3 Sentiment Score Calibration
4 Experiment
4.1 Dataset
4.2 Baselines
4.3 Experimental Settings
4.4 Evaluation Metrics
4.5 Analysis of the Parameter Cluster Number
4.6 Compare with Random Sampling
5 Conclusion
References
A Weak Supervision Approach with Adversarial Training for Named Entity Recognition

1 Introduction
2 Related Work
3 Approach
3.1 Labeling Functions
3.2 WSAT: Weak Supervision Approach with Adversarial Training
4 Experimental Results
4.1 Dataset
4.2 Baselines
4.3 Results and Discussion
5 Conclusion
References
An Attention-Based Approach to Accelerating Sequence Generative Adversarial Nets
1 Introduction
2 Related Work
3 Our Approach
3.1 Attention-Based Discriminator
3.2 Attention to Rewards
3.3 Training of G
4 Experiments
4.1 Training Settings
4.2 Baselines
4.3 Evaluation Metrics
4.4 Synthetic Data Experiments

4.5 Dialogue Generation: DailyDialog
4.6 Internal Comparison Experiments
5 Conclusion and Future Work
References
Autoregressive Pre-training Model-Assisted Low-Resource Neural Machine Translation
1 Introduction
2 Background
3 Method
3.1 Partial Factorization Sequence Acquisition
3.2 NMT Model Integrated with Autoregressive Based XLNet
3.3 Knowledge Distillation Method
4 Experiments
4.1 Results and Analysis
4.2 Ablation Experiments
4.3 Case Study
5 Conclusion
References

Combining Improvements for Exploiting Dependency Trees in Neural Semantic Parsing
1 Introduction
2 Related Work
3 Three Improvements
3.1 Parent-Scaled Self-attention (PASCAL)
3.2 Syntax-Aware Word Representations (SAWRs)
3.3 Constituent Attention (CA)
4 Combining Improvements
5 Experiments
5.1 Datasets
5.2 Evaluation Metrics
5.3 Implementation Details
5.4 Results
5.5 Visual Analysis
6 Conclusion
References
Deep Semantic Fusion Representation Based on Special Mechanism of Information Transmission for Joint Entity-Relation Extraction
1 Introduction

2 Related Work
3 Task Definition and Tagging Scheme
4 The Proposed Model
4.1 Representations of Token and Relation
4.2 Deep Semantics Fusion
4.3 Triple Extraction
4.4 Training
5 Experiments
5.1 Dataset and Experimental Settings
5.2 Baselines and Evaluation Metrics
5.3 Experimental Results
6 Analysis
6.1 Ablation Study
6.2 Parameter Analysis
6.3 Analysis on Different Sentence Types
7 Conclusion
References
Exploiting News Article Structure for Automatic Corpus Generation of Entailment Datasets
1 Introduction
2 Methodology
2.1 NLI Datasets from News Articles.