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Graph-Based Extractive Text Summarization Models: A Systematic Review
2022
Journal of Information Technology Management
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
doi:10.22059/jitm.2022.84899
doaj:66273e45f5d7421dbdf101925fbfc6b8
fatcat:7wuowbtj4few3kp37sl5g4i42m