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    <identifier>10.57760/sciencedb.13705</identifier>
    <datestamp>2024-09-23T16:01:54Z</datestamp>
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  <dc:date>2024-09-23</dc:date>
  <dc:title>High-value Patent Identification Dataset</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.13705</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>The data is derived from Incopat, and is obtained by using the search formula &amp;quot;(AP-OR=(Chinese Academy of Sciences)) AND (AD=[20030101 TO 20221231])&amp;quot;, with 10917 positive samples and 22652 negative samples.&amp;nbsp;According to the IPC, there are three datasets, each divided into train, val, and test. Train is used for model training, val is used for model tuning, and test is used to evaluate model performance.&amp;nbsp;The image data folder contains the abstract drawings of the patent.&amp;nbsp;</dc:description>
  <dc:subject>high-value ptent; dataset; patent recognition</dc:subject>
  <dc:creator>Zhang Biao</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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