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Data-Driven Phenetic Modeling of Scripts’ Evolution

In: Liss 2020

Author

Listed:
  • Gábor Hosszú

    (Budapest University of Technology and Economics)

Abstract

This paper presents an extended phenetic approach to classifying the examined historical scripts and determining some properties of their evolution. The main challenge in the phenetic modeling of historical scripts is the very large number of homoplasies, i.e. the coincidence of unrelated graphemes or writing rules in different scripts. A data-driven framework is proposed for evaluating the extended phenetic model of the examined scripts through the application of the parsimony principle of cladistics. The basic idea is to collect various evolutionary models for each grapheme and extend the phenetic model built on the matches these graphemes in various scripts. The combination of the phenetic model with particular evolutionary concepts of each grapheme results in an improved phenetic model, which is relatively protected from the effect of the homoplasies. To illustrate this framework, it was used to evaluate the extended phenetic model of four descendant scripts, including 117 features (characters in a cladistic sense).

Suggested Citation

  • Gábor Hosszú, 2021. "Data-Driven Phenetic Modeling of Scripts’ Evolution," Springer Books, in: Shifeng Liu & Gábor Bohács & Xianliang Shi & Xiaopu Shang & Anqiang Huang (ed.), Liss 2020, pages 389-403, Springer.
    • Handle: RePEc:spr:sprchp:978-981-33-4359-7_28
    DOI: 10.1007/978-981-33-4359-7_28
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