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  <doi_batch_id>aspg-25-1098-1792223509</doi_batch_id>
  <timestamp>20261017075149</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>Journal of Cognitive Human-Computer Interaction</full_title>
    <abbrev_title>JCHCI</abbrev_title>
    <issn media_type="print">2771-1471</issn>
    <issn media_type="electronic">2771-1463</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <journal_volume>
     <volume>3</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Machine Learning Based Product Price Inference Using Price Elasticity of Demand Approach</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>K.</given_name>
      <surname>Vengatesan</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Computer Engineering, Sanjivani College of Engineering, Kopargaon, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Raghvendra Vijay</given_name>
      <surname>Naidu</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Computer Engineering, Sanjivani College of Engineering, Kopargaon, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Kunal Ganesh</given_name>
      <surname>Joshi</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Computer Engineering, Sanjivani College of Engineering, Kopargaon, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>ChaitanyaSantosh</given_name>
      <surname>Tekane</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Computer Engineering, Sanjivani College of Engineering, Kopargaon, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Siddhant Ravindra</given_name>
      <surname>Gore</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Computer Engineering, Sanjivani College of Engineering, Kopargaon, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>In India lot of production and manufacturing industries are there, every time the price fixing to any new or existing product is considered many factors. Many parameters are involved to fix the price of any product. In market price fixing consists of various parameters, before finalize price value of any product, that will be based on the market demand of any product, and customer behavior also may be vary based on the day of purchasing in this proposed work we need to optimization of price product using machine learning algorithm and how effectively increase the proof of any product.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <pages>
     <first_page>08</first_page>
     <last_page>16</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">1098</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
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    <doi_data>
     <doi>10.54216/JCHCI.030101</doi>
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