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Using deep learning to explore movement of people in a large corpus of biographies

Schlögl, Matthias; Lejtovicz, Katalin; Bernád, Ágoston Zénó; Kaiser, Maximilian; Rumpolt, Peter


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  <identifier identifierType="DOI">10.5281/zenodo.1149023</identifier>
  <creators>
    <creator>
      <creatorName>Schlögl, Matthias</creatorName>
      <givenName>Matthias</givenName>
      <familyName>Schlögl</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-1451-0987</nameIdentifier>
      <affiliation>Austrian Academy of Sciences</affiliation>
    </creator>
    <creator>
      <creatorName>Lejtovicz, Katalin</creatorName>
      <givenName>Katalin</givenName>
      <familyName>Lejtovicz</familyName>
      <affiliation>Austrian Academy of Sciences</affiliation>
    </creator>
    <creator>
      <creatorName>Bernád, Ágoston Zénó</creatorName>
      <givenName>Ágoston Zénó</givenName>
      <familyName>Bernád</familyName>
      <affiliation>Austrian Academy of Sciences</affiliation>
    </creator>
    <creator>
      <creatorName>Kaiser, Maximilian</creatorName>
      <givenName>Maximilian</givenName>
      <familyName>Kaiser</familyName>
      <affiliation>Austrian Academy of Sciences</affiliation>
    </creator>
    <creator>
      <creatorName>Rumpolt, Peter</creatorName>
      <givenName>Peter</givenName>
      <familyName>Rumpolt</familyName>
      <affiliation>Austrian Academy of Sciences</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Using deep learning to explore movement of people in a large corpus of  biographies</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2018</publicationYear>
  <dates>
    <date dateType="Issued">2018-01-16</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Text">Presentation</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/1149023</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.1149022</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;In this presentation we showcase our first experiences with deep learning models for relation extraction in german biographies. These models are trained on human annotations of relations between the biographed person and entities found in the full-text (e.g. person A &amp;gt;&amp;gt; travelled to &amp;gt;&amp;gt; Wien).&lt;/p&gt;

&lt;p&gt;An interactive version of this presentation that allows also to test the trained model can be found &lt;a href="https://apis.acdh.oeaw.ac.at/presentation_innsbruck17/"&gt;here&lt;/a&gt;.&lt;/p&gt;</description>
    <description descriptionType="Other">Interactive version of this presentation is available here: https://apis.acdh.oeaw.ac.at/presentation_innsbruck17/</description>
  </descriptions>
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