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A Review of Graph-Based Extractive Text Summarization Models

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Innovative Systems for Intelligent Health Informatics (IRICT 2020)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 72))

Abstract

The amount of text data is continuously increasing both at online and offline storage, that makes is difficult for people to read across and find the desired information within a possible available time. This necessitate the use of technique such as automatic text summarization. A text summary is the briefer form of the original text, in which the principal document message is preserved. 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 review of various graph-based automatic text summarization models.

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Author information

Authors and Affiliations

  1. School of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia

    Abdulkadir Abubakar Bichi, Ruhaidah Samsudin & Rohayanti Hassan

  2. MIS Department, College of Business Administration - Yanbu, Taibah University, Yanbu, 42353, Saudi Arabia

    Khalil Almekhlafi

Authors
  1. Abdulkadir Abubakar Bichi
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  2. Ruhaidah Samsudin
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  3. Rohayanti Hassan
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  4. Khalil Almekhlafi
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Editors and Affiliations

  1. College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia

    Faisal Saeed

  2. School of Computing, Information Systems Department, Universiti Utara Malaysia, Sintok, Malaysia

    Fathey Mohammed

  3. Sanaa’a Community College, Sana'a, Yemen

    Abdulaziz Al-Nahari

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Bichi, A.A., Samsudin, R., Hassan, R., Almekhlafi, K. (2021). A Review of Graph-Based Extractive Text Summarization Models. In: Saeed, F., Mohammed, F., Al-Nahari, A. (eds) Innovative Systems for Intelligent Health Informatics. IRICT 2020. Lecture Notes on Data Engineering and Communications Technologies, vol 72. Springer, Cham. https://doi.org/10.1007/978-3-030-70713-2_41

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