Exploratory methods for relation discovery in archival data.

In this article, we propose a holistic approach to discover relations in art historical communities and enrich historians' biographies and archival descriptions with graph patterns relevant to art historiographic enquiry. We use exploratory data analysis to detect patterns, we select features, and w...

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Published in:Digital Scholarship in the Humanities Vol. 38; no. 1; pp. 111 - 127
Main Authors: Giagnolini, Lucia, Daquino, Marilena, Mambelli, Francesca, Tomasi, Francesca
Format: Article
Published: Oxford University Press / USA Apr2023
Subjects:
Online Access:View this record in EBSCOhost
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        atl: Exploratory methods for relation discovery in archival data.
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          Giagnolini, Lucia
          Daquino, Marilena
          Mambelli, Francesca
          Tomasi, Francesca
        affil:
          Historical Archive of the University of Bologna , Italy
          Digital Humanities Advanced Research Centre (DH.arc), University of Bologna , Italy
          Fondazione Federico Zeri, University of Bologna , Italy
      su:
        Art & society
        Data analysis
        Archivists
      sug:
        subj:
          Art & society
          Data analysis
          Archivists
      ab: In this article, we propose a holistic approach to discover relations in art historical communities and enrich historians' biographies and archival descriptions with graph patterns relevant to art historiographic enquiry. We use exploratory data analysis to detect patterns, we select features, and we use them to evaluate classification models to predict new relations, to be recommended to archivists during the cataloguing phase. Results show that relations based on biographical information can be addressed with higher precision than relations based on research topics or institutional relations. Deterministic and a priori rules present better results than probabilistic methods.
      pubtype: Academic Journal
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    language: English
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