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    <identifier>10.57760/sciencedb.15157</identifier>
    <datestamp>2024-01-12T10:04:57Z</datestamp>
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<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_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">
  <dc:date>2024-01-12</dc:date>
  <dc:title>tianchi_mobile_recommend</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.15157</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>In real business scenarios, we often need to build personalized recommendation models for a subset of all products. In the process of completing this task, we not only need to utilize user behavior data on this subset of products, but also often need to utilize richer user behavior data. Define the following symbols:&amp;nbsp;U - User Collection&amp;nbsp;I - Complete Collection of Products&amp;nbsp;P - Product subset, P &amp;sube; I&amp;nbsp;D - User behavior data set for the complete set of products&amp;nbsp;So our goal is to use D to construct a recommendation model for U users to P products.&amp;nbsp;</dc:description>
  <dc:subject>personalized recommendation; user behavior data; product subset</dc:subject>
  <dc:creator>Cui Ying</dc:creator>
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  <dc:publisher>Science Data Bank</dc:publisher>
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