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    <responseDate>2026-10-15T02:02:42Z</responseDate>
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    <identifier>10.57760/sciencedb.20299</identifier>
    <datestamp>2025-01-26T20:00:59Z</datestamp>
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  <dc:date>2025-01-26</dc:date>
  <dc:title>Tribology Literature Experimental Dataset</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.20299</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>The tribology literature dataset used in this study was sourced from the Lubrication Technology Information Platform (http://lub.licp.cn/), which aggregates over 200,000 pieces of literature data related to the field of tribology. After downloading and preprocessing the data, a tribology literature dataset containing 8,500 data points was constructed for empirical research.The pre-classification labels used in this study are based on the eight sub-navigation categories under the &amp;quot;Literature Express&amp;quot; section of the aforementioned platform. Specifically, the pre-classification labels include:Coating (Surface Engineering)Friction Materials (Tribological Materials)Wear and Lubrication Theory and Application (Tribology and Lubrication Theory and Application)Tribological Bearings (Tribological Components)Lubricants and Additives (Lubricants and Additives)Biomechanic (Biological and Bionic Tribology)Nano-tribology (Micro/Nano Tribology)Mechanical Seals (Mechanical Sealing Technology)These pre-classification labels provide a basis for categorizing and analyzing the tribology literature data, facilitating a deeper understanding of the research trends and topics in the field of tribology.</dc:description>
  <dc:subject>tribology; Multi-label Classification;  literature dataset</dc:subject>
  <dc:creator>Jing Hao</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/publicdomain/zero/1.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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