Improving Abstractive Summarization with Graph Sequence Model

Hailing Zhang; Jianyue Zhai; Hongbo Wang

doi:10.1007/978-981-97-5181-5_8

ScienceGate Book Chapters

BOOK-CHAPTER

Improving Abstractive Summarization with Graph Sequence Model

Hailing Zhang Jianyue Zhai Hongbo Wang

Year: 2024 Smart innovation, systems and technologies Pages: 93-102 Publisher: Springer Nature

DOI: 10.1007/978-981-97-5181-5_8

Get Full-Text PDF Get Analytical Report

Keywords:

Automatic summarization Computer science Sequence (biology) Graph Natural language processing Artificial intelligence Theoretical computer science Biology Genetics

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.51

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Topic Modeling

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Text Analysis Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Data Quality and Management

Social Sciences → Decision Sciences → Management Science and Operations Research

Improving Abstractive Summarization with Graph Sequence Model

Metrics

Topics

Related Documents

Improving Abstractive Dialogue Summarization with Graph Structures and Topic Words

Graph-Based Abstractive Summarization

Improving Abstractive Summarization with Iterative Representation

Improving Abstractive Summarization with Commonsense Knowledge

Abstractive Document Summarization with a Graph-Based Attentional Neural Model