January 25, 2022 Conference paper Open Access

Bernard, Guillaume; Suire, Cyrille; Faucher, Cyril; Doucet, Antoine

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  <identifier identifierType="DOI">10.5281/zenodo.5900742</identifier>
  <creators>
    <creator>
      <creatorName>Bernard, Guillaume</creatorName>
      <givenName>Guillaume</givenName>
      <familyName>Bernard</familyName>
    </creator>
    <creator>
      <creatorName>Suire, Cyrille</creatorName>
      <givenName>Cyrille</givenName>
      <familyName>Suire</familyName>
    </creator>
    <creator>
      <creatorName>Faucher, Cyril</creatorName>
      <givenName>Cyril</givenName>
      <familyName>Faucher</familyName>
    </creator>
    <creator>
      <creatorName>Doucet, Antoine</creatorName>
      <givenName>Antoine</givenName>
      <familyName>Doucet</familyName>
    </creator>
  </creators>
  <titles>
    <title>Event Related Document Retrieval with Multilingual Real World Event Representation</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2022</publicationYear>
  <dates>
    <date dateType="Issued">2022-01-25</date>
  </dates>
  <resourceType resourceTypeGeneral="ConferencePaper"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5900742</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.5900741</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/newseye</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://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;This demonstration paper introduces a tool to analyse historical digital libraries with the benefit of publicly available knowledge bases, such as Wikidata and Wikipedia. In this paper, we focus on real-world-events of the past, such as festivals or assassinations. We introduce our method which merges knowledge from Wikidata and Wikipedia article summaries to gather entities involved in events, dates, types and labels. We hereby present the Web tool we designed and the implemented method to characterise events. It integrates easily into any event oriented pipeline: in our demonstration, we use it to find event related documents in the NewsEye corpus.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/100010661</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/770299/">770299</awardNumber>
      <awardTitle>NewsEye: A Digital Investigator for Historical Newspapers</awardTitle>
    </fundingReference>
  </fundingReferences>
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