August 27, 2020 Journal article Open Access

Yanniek van der Schans; David Ruhe; Wido van Peursen; Sandjai Bhulai

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  <identifier identifierType="DOI">10.5281/zenodo.4003509</identifier>
  <creators>
    <creator>
      <creatorName>Yanniek van der Schans</creatorName>
      <affiliation>Vrije Universiteit Amsterdam</affiliation>
    </creator>
    <creator>
      <creatorName>David Ruhe</creatorName>
      <affiliation>Vrije Universiteit Amsterdam</affiliation>
    </creator>
    <creator>
      <creatorName>Wido van Peursen</creatorName>
      <affiliation>Vrije Universiteit Amsterdam</affiliation>
    </creator>
    <creator>
      <creatorName>Sandjai Bhulai</creatorName>
      <affiliation>Vrije Universiteit Amsterdam</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Clustering Biblical Texts Using Recurrent Neural Networks</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>Recurrent Neural Networks</subject>
    <subject>Biblical Hebrew</subject>
    <subject>Diachronic Liguistics</subject>
    <subject>Computational Semantics</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2020-08-27</date>
  </dates>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4003509</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4003508</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/niaaproceedings1819</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 study examines linguistic variation within Biblical Hebrew&lt;br&gt;
by using Recurrent Neural Networks (RNNs) to detect differences&lt;br&gt;
and cluster the Old Testament books accordingly. Various linguistic&lt;br&gt;
features are analysed that are traditionally considered to be of importance in analysing linguistic variation. The traditional division&lt;br&gt;
of books as either Early Biblical Hebrew or Late Biblical Hebrew is&lt;br&gt;
hereby put to the test. Results show that RNNs are a fitting method&lt;br&gt;
for analysing the (morpho)syntax of a language. The model works&lt;br&gt;
well on both separate features, as well as all the features combined.&lt;br&gt;
On the basis of the results the RNNs provide, we propose that&lt;br&gt;
the diachronic approach to Biblical Hebrew is indeed plausible.&lt;br&gt;
The clusters generally hint to the scholarly division made in the&lt;br&gt;
diachronic approach to linguistic variation&lt;br&gt;
&amp;nbsp;&lt;/p&gt;</description>
  </descriptions>
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