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With the rise in large amounts of data and information, it is getting tedious to comprehend all of it, which is why algorithms to generate summaries for a given text prompt are being implemented. Summarization techniques like abstractive text summarization and extractive text summarization are a great way to reduce the size of large amounts of information into concise texts that are similar to the original text. However, it is necessary to determine the best method of producing summaries, among other numerous algorithms. This paper aims to investigate and evaluate four of the popular algorithms used in generating summaries. This study tries to highlight the impact of algorithm selection for generating highly concise, quality, and meaningful summaries.

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Comparative Analysis of Different Algorithms for Extractive Text Summarization

  • 会议论文

  • 发表日期：

    2025年

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  • Hussain Falih Mahdi,
  • Utkarsh Goyal,
  • Satvik Srivastava,
  • Tanupriya Choudhury,
  • Tridha Bajaj,
  • Ayan Sar

摘要

With the rise in large amounts of data and information, it is getting tedious to comprehend all of it, which is why algorithms to generate summaries for a given text prompt are being implemented. Summarization techniques like abstractive text summarization and extractive text summarization are a great way to reduce the size of large amounts of information into concise texts that are similar to the original text. However, it is necessary to determine the best method of producing summaries, among other numerous algorithms. This paper aims to investigate and evaluate four of the popular algorithms used in generating summaries. This study tries to highlight the impact of algorithm selection for generating highly concise, quality, and meaningful summaries.