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    <identifier>10.11922/sciencedb.j00104.00059</identifier>
    <datestamp>2020-10-17T10:45:58Z</datestamp>
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  <dc:date>2020-10-17</dc:date>
  <dc:title>Refining Linked Data with Games with a Purpose</dc:title>
  <dc:identifier>doi:10.11922/sciencedb.j00104.00059</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>Two tables, 1 algorithm and six figures. Table 1 shows the number of required contributions for truth inference over N tasks. Table 2 shows the truth inference results comparison between our incremental approach and state-of-the-art techniques. Algorithm 1 shows incremental truth inference algorithm. Figure 1 shows incremental Truth Inference approach. Figure 2 presents architecture of the GWAP enabler. Figure 3 shows Indomilando: gameplay (left) and asset visualisation on a map (right). Figure 4 shows land cover validation game: pixel classification (left) and badges (right). Figure 5 shows Night Knights: the game play. Figure 6 presents sample screenshot from ARGO game to collect analogies.</dc:description>
  <dc:subject>Human computation;  Games with a purpose;  Linked data;  Knowledge graph;  Data refinement;  Data  linking;  Truth inference</dc:subject>
  <dc:creator>Irene Celino</dc:creator>
  <dc:creator>Gloria Re Calegari</dc:creator>
  <dc:creator>Andrea Fiano</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.1162/dint_a_00056</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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