<record>
  <header>
    <identifier>oai:eurokd.com:article/393</identifier>
    <datestamp>2025-12-15</datestamp>
  </header>
  <metadata>
    <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/">
      <dc:title>Implementation of Recommendation Algorithm based on Recommendation Sessions in E-commerce IT System</dc:title>
      <dc:description>&lt;p style="text-align:justify;"&gt;The aim of the paper is to present a study as the implementation of the author’s Algorithm of&amp;nbsp;the Recommendation Sessions ARS in an operating e‐commerce information system and to&amp;nbsp;analyse basic parameters of the recommendation system created as a result of the&amp;nbsp;implementation. The first part of the study contains a synthetic description of the area of&amp;nbsp;recommendation systems. The next section presents the proprietary ARS recommendation&amp;nbsp;algorithm based on recommendation sessions. The third part of the paper describes the&amp;nbsp;mathematical model of the recommendation session built on the basis of the theory of graphs&amp;nbsp;and networks, which such model makes the input data for the algorithm in question. The next&amp;nbsp;part of the publication describes the possibilities of representing graph structures and the&amp;nbsp;method of implementing a G graph (constituting a set of the recommendation session) in a&amp;nbsp;relational database. The implementation of the ARS algorithm, based on the SQL standard, was&amp;nbsp;also presented. The implementations in question have been developed on the basis of a&amp;nbsp;working information system of the e‐commerce class. As a result of the implementation of the&amp;nbsp;algorithm, a fully functional recommendation system was created, which can be adapted to&amp;nbsp;various e‐commerce IT systems. The positive result of the work was confirmed by the research&amp;nbsp;on the parameters of the recommendation system, included in the last part of the study.&lt;/p&gt;</dc:description>
      <dc:publisher>EuroKD Publishing</dc:publisher>
      <dc:date>2021-08-24</dc:date>
      <dc:type>Text</dc:type>
      <dc:identifier>https://api.eurokd.com/Uploads/Article/393/mbrq.2021.19.02.pdf</dc:identifier>
      <dc:identifier>https://doi.org/10.32038/mbrq.2021.19.02</dc:identifier>
      <dc:language>en</dc:language>
      <dc:coverage>Pages 14–32</dc:coverage>
    </oai_dc:dc>
  </metadata>
</record>