Graph Learning and Network Science for Natural Language Processing

12 Graph-based Text Document Extractive Summarization

Sheetal Sonawane

DOI: 10.1201/9781003272649-12

CONTENTS

12.1 Introduction

12.2 Extractive Summarization

12.2.1 Commonly used Features in Extractive Summarization Method

12.2.2 Summary Length

12.3 Graph-based Methods for Extractive Summarization

12.3.1 Graph-based Ranking Algorithm

12.3.2 Weighted/unweighted Simple Graph

12.3.3 Heterogeneous Graph Model

12.3.4 Correlation Graph Model

12.3.5 Semantic Graph Model

12.3.6 Hypergraph Model

12.3.6.1 Hypergraph Construction

12.3.7 Semigraph Model

12.4 Conclusion

References

12.1 Introduction

On a daily basis, millions of web pages are being created, so there is a huge demand for condensing text documents. Text document summarization [1] is an ...