Graph-Based Extractive Text Summarization Models: A Systematic Review

نویسندگان
Bichi, Abdulkadir Abubakar ID 1
Hassan, Rohayanti ID 2
Keikhosrokiani, Pantea ID 3
Almekhlafi, Khalil ID 4

1 School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Johor-Malaysia

2 Senior Lecturer, School of Computing, University Technology Malaysia, 81310 Johor Bahru, Johor, Malaysia

3 School of Computer Sciences, University Sains Malaysia, 11800 Minden, Penang, Malaysia.

4 Assistant Professor, Taibah University, CBA-Yanbu, 42353, Saudi Arabia.

doi
10.22059/jitm.2022.84899
چکیده

The volume of digital text data is continuously increasing both online and offline storage, which makes it difficult to read across documents on a particular topic and find the desired information within a possible available time. This necessitates the use of technique such as automatic text summarization. Many approaches and algorithms have been proposed for automatic text summarization including; supervised machine learning, clustering, graph-based and lexical chain, among others. This paper presents a novel systematic review of various graph-based automatic text summarization models.

کلیدواژه‌ها
Natural Languages Processing, Text mining, Graph approaches