Journal article Open Access

Clustering Biblical Texts Using Recurrent Neural Networks

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


Citation Style Language JSON Export

{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.4003509", 
  "author": [
    {
      "family": "Yanniek van der Schans"
    }, 
    {
      "family": "David Ruhe"
    }, 
    {
      "family": "Wido van Peursen"
    }, 
    {
      "family": "Sandjai Bhulai"
    }
  ], 
  "issued": {
    "date-parts": [
      [
        2020, 
        8, 
        27
      ]
    ]
  }, 
  "abstract": "<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>", 
  "title": "Clustering Biblical Texts Using Recurrent Neural Networks", 
  "type": "article-journal", 
  "id": "4003509"
}
254
183
views
downloads
All versions This version
Views 254254
Downloads 183183
Data volume 525.7 MB525.7 MB
Unique views 244244
Unique downloads 173173

Share

Cite as