Journal article Open Access

Clustering Biblical Texts Using Recurrent Neural Networks

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


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    <subfield code="a">Biblical Hebrew</subfield>
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    <subfield code="a">Diachronic Liguistics</subfield>
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    <subfield code="u">Vrije Universiteit Amsterdam</subfield>
    <subfield code="a">Yanniek van der Schans</subfield>
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    <subfield code="a">Clustering Biblical Texts Using Recurrent Neural Networks</subfield>
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    <subfield code="a">&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;
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