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  <doi_batch_id>aspg-3-3862-1791417775</doi_batch_id>
  <timestamp>20261008000255</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
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  <registrant>American Scientific Publishing Group</registrant>
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  <journal>
   <journal_metadata language="en">
    <full_title>Fusion: Practice and Applications</full_title>
    <abbrev_title>FPA</abbrev_title>
    <issn media_type="print">2770-0070</issn>
    <issn media_type="electronic">2692-4048</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2025</year>
    </publication_date>
    <journal_volume>
     <volume>20</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>A comprehensive and systematic exposition on Automatic Text Summarization Technique: A deeper coverage on extractive, abstractive and hybrid methods</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Sini Raj</given_name>
      <surname>Pulari</surname>
      <affiliations>
       <institution>
        <institution_name>Dept. of CSE, Vignan’s Foundation for Science, Technology and Research, Guntur, Andhra Pradesh, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Umadevi</given_name>
      <surname>Maramreddy</surname>
      <affiliations>
       <institution>
        <institution_name>Dept. of CSE, Vignan’s Foundation for Science, Technology and Research, Guntur, Andhra Pradesh, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Shriram K.</given_name>
      <surname>Vasudevan</surname>
      <affiliations>
       <institution>
        <institution_name>Intel India Pvt. Ltd., Bengaluru, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Artificial Intelligence's remarkable advancement and Natural Language Processing enabled innovations that fulfill various vertical requirements. News summarization has become a popular topic where systems extract valuable semantic content and generate shorter abstracts from the original content. News readers benefit from a quick understanding of essential details because an informative summary provides them with important points without forced reading of the whole article. This article covers essential NLP news summarization methods, including Abstractive summarization, Extractive summarization, and Hybrid summarization, together with recent datasets, evaluation metrics, applications and future challenges. The main benefit of this work serves both researchers by providing them with complete information about contemporary summarization developments to select suitable summarization models during application development.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2025</year>
    </publication_date>
    <pages>
     <first_page>179</first_page>
     <last_page>192</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">3862</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
    </ai:program>
    <doi_data>
     <doi>10.54216/FPA.200114</doi>
     <resource>https://www.americaspg.com/journal/3/article/3862</resource>
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       <resource mime_type="application/pdf">https://www.americaspg.com/storage/51747352167.pdf</resource>
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