Analysis of Abstractive and Extractive Summarization Methods

Authors

DOI:

https://doi.org/10.3991/ijet.v19i01.46079

Keywords:

Textual Summarization, Structured Based Approach, Extractive Summary, Abstractive Summary, Sentence Ranking Methods, Semantic Based Approach

Abstract


This paper explains the existing approaches employed for (automatic) text summarization. The summarizing method is part of the natural language processing (NLP) field and is applied to the source document to produce a compact version that preserves its aggregate meaning and key concepts. On a broader scale, approaches for text-based summarization are categorized into two groups: abstractive and extractive. In abstractive summarization, the main contents of the input text are paraphrased, possibly using vocabulary that is not present in the source document, while in extractive summarization, the output summary is a subset of the input text and is generated by using the sentence ranking technique. In this paper, the main ideas behind the existing methods used for abstractive and extractive summarization are discussed broadly. A comparative study of these methods is also highlighted.

Author Biographies

Gagandeep Kaur, Chandigarh University

Assistant  Professor  at University Institute of Computing (UIC) chandigarh University

Mudasir Mohd, University of Kashmir

Senior Assistant Professor at University of Kashmir

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Published

2024-01-10

How to Cite

Kirmani, M., Kaur, G., & Mohd, M. (2024). Analysis of Abstractive and Extractive Summarization Methods. International Journal of Emerging Technologies in Learning (iJET), 19(01), pp. 86–96. https://doi.org/10.3991/ijet.v19i01.46079

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Papers