Chinese Named Entity Recognition Based on Bidirectional LSTM--CRF Model

目录

声明

Acknowledgements

Abstract

Table of contents

List of figures

List of tables

Chapter 1 Introduction

1．1 Research Background and Significance of the Subject

1．1．1 Research Background

1．1．2 Research Significance

1．2 Analysis of Research Status at Home and Abroad

1．2．1 Status of Foreign Research

1．2．2 Status of Chinese Research

1．3 Problems and Analysis of Named Entity Recognition

1．4 Main Work of This Thesis

1．5 Structure of Thesis

Chapter 2 Related Work

2．1 Method of Named Entity Recognition

2．1．1 Hidden Markov Model

2．1．2 Conditional Random Field Model

2．2 Basic Neural Network

2．2．1 Neurons

2．2．2 Perceptron and Multilayer Network

2．2．3 Recurrent Neural Network

2．3 Tensorflow Framework

2．4 Summary of This Chapter

Chapter 3 BiLSTM-CRF Models for Chinese Named Entity Recognition

3．1 LSTM Networks

3．2 Bidirectional LSTM Networks

3．3 Conditional Random Field Networks

3．4 BiLSTM-CRF Networks

3．4．1 Chinese Data Preprocessing

3．4．2 Word Vector Layer

3．4．3 BiLSTM Layer

3．4．4 CRF layer

Chapter 4 Experiments

4．1 Experimental Environment

4．2 Data Sets

4．2．1 MSRA Corpus

4．3 Evaluation Methods

4．4 Experimental Results

Chapter 5 Conclusion and Future Work

5．1 Conclusion

5．2 Future Work

References

Appendix