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Clustering Biblical Texts Using Recurrent Neural Networks

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


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    "description": "<p>This study examines linguistic variation within Biblical Hebrew<br>\nby using Recurrent Neural Networks (RNNs) to detect differences<br>\nand cluster the Old Testament books accordingly. Various linguistic<br>\nfeatures are analysed that are traditionally considered to be of importance in analysing linguistic variation. The traditional division<br>\nof books as either Early Biblical Hebrew or Late Biblical Hebrew is<br>\nhereby put to the test. Results show that RNNs are a fitting method<br>\nfor analysing the (morpho)syntax of a language. The model works<br>\nwell on both separate features, as well as all the features combined.<br>\nOn the basis of the results the RNNs provide, we propose that<br>\nthe diachronic approach to Biblical Hebrew is indeed plausible.<br>\nThe clusters generally hint to the scholarly division made in the<br>\ndiachronic approach to linguistic variation<br>\n&nbsp;</p>", 
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    "title": "Clustering Biblical Texts Using Recurrent Neural Networks", 
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    "keywords": [
      "Recurrent Neural Networks", 
      "Biblical Hebrew", 
      "Diachronic Liguistics", 
      "Computational Semantics"
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    "publication_date": "2020-08-27", 
    "creators": [
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        "affiliation": "Vrije Universiteit Amsterdam", 
        "name": "Yanniek van der Schans"
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        "affiliation": "Vrije Universiteit Amsterdam", 
        "name": "David Ruhe"
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      {
        "affiliation": "Vrije Universiteit Amsterdam", 
        "name": "Wido van Peursen"
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      {
        "affiliation": "Vrije Universiteit Amsterdam", 
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