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    <identifier>10.57760/sciencedb.j00133.00446</identifier>
    <datestamp>2024-07-26T16:35:58Z</datestamp>
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  <dc:date>2024-07-26</dc:date>
  <dc:title>a Dataset of Disruptive Technology Weak Signal Recognition Models Based on Machine Learning</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.j00133.00446</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>The data comes from the patent database Incopat and includes hydrogen energy strategic plans of various countries. A total of 41466 invention patents were obtained, and after simple homologous mergers, 14897 invention patents and 24 hydrogen energy strategic plans were obtained. The main process and result data are as follows:Comparison of DI-P, RDI, and DI recognition effects. xlsxMulti machine learning prediction results. xlsxLink prediction recognition results. csvProspective Phrase List Matching Results.xlsxRelative Disruptive Index Distribution. xlsxBasic information of cited patents. xlsMainstream technology patent data, xlsx</dc:description>
  <dc:subject>Disruptive technology; weak signal; machine learning</dc:subject>
  <dc:creator>Wang Lixiao</dc:creator>
  <dc:creator>Chen Wei</dc:creator>
  <dc:creator>Qiu Hanqi</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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