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Multi-Document News Web Page Summarization Using Content Extraction and Lexical Chain Based Key Phrase Extraction

Author

Listed:
  • Chandrakala Arya

    (School of Computing, Graphic Era Hill University, Dehradun 248002, India)

  • Manoj Diwakar

    (CSE Department, Graphic Era Deemed to be University, Dehradun 248002, India)

  • Prabhishek Singh

    (School of Computer Science Engineering and Technology, Bennett University, Greater Noida 201009, India)

  • Vijendra Singh

    (School of Computer Science, University of Petroleum and Energy Studies, Dehradun 248007, India)

  • Seifedine Kadry

    (Department of Applied Data Science, Noroff University College, 4608 Kristiansand, Norway
    Artificial Intelligence Research Center (AIRC), Ajman University, Ajman 346, United Arab Emirates
    Department of Electrical and Computer Engineering, Lebanese American University, Byblos 13-5053, Lebanon)

  • Jungeun Kim

    (Department of Software and CMPSI, Kongju National University, Cheonan 31080, Republic of Korea)

Abstract

In the area of text summarization, there have been significant advances recently. In the meantime, the current trend in text summarization is focused more on news summarization. Therefore, developing a synthesis approach capable of extracting, comparing, and ranking sentences is vital to create a summary of various news articles in the context of erroneous online data. It is necessary, however, for the news summarization system to be able to deal with multi-document summaries due to content redundancy. This paper presents a method for summarizing multi-document news web pages based on similarity models and sentence ranking, where relevant sentences are extracted from the original article. English-language articles are collected from five news websites that cover the same topic and event. According to our experimental results, our approach provides better results than other recent methods for summarizing news.

Suggested Citation

  • Chandrakala Arya & Manoj Diwakar & Prabhishek Singh & Vijendra Singh & Seifedine Kadry & Jungeun Kim, 2023. "Multi-Document News Web Page Summarization Using Content Extraction and Lexical Chain Based Key Phrase Extraction," Mathematics, MDPI, vol. 11(8), pages 1-20, April.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:8:p:1762-:d:1117821
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    References listed on IDEAS

    as
    1. Hsin‐Hsi Chen & June‐Jei Kuo & Sheng‐Jie Huang & Chuan‐Jie Lin & Hung‐Chia Wung, 2003. "A summarization system for Chinese news from multiple sources," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(13), pages 1224-1236, November.
    2. Rautray, Rasmita & Balabantaray, Rakesh Chandra, 2017. "Cat swarm optimization based evolutionary framework for multi document summarization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 477(C), pages 174-186.
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