Journal article Open Access
Yanniek van der Schans; David Ruhe; Wido van Peursen; Sandjai Bhulai
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <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"><p>This study examines linguistic variation within Biblical Hebrew<br> by using Recurrent Neural Networks (RNNs) to detect differences<br> and cluster the Old Testament books accordingly. Various linguistic<br> features are analysed that are traditionally considered to be of importance in analysing linguistic variation. The traditional division<br> of books as either Early Biblical Hebrew or Late Biblical Hebrew is<br> hereby put to the test. Results show that RNNs are a fitting method<br> for analysing the (morpho)syntax of a language. The model works<br> well on both separate features, as well as all the features combined.<br> On the basis of the results the RNNs provide, we propose that<br> the diachronic approach to Biblical Hebrew is indeed plausible.<br> The clusters generally hint to the scholarly division made in the<br> diachronic approach to linguistic variation<br> &nbsp;</p></description> </descriptions> </resource>
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