A Phenetic Approach to Selected Variants of Arabic and Aramaic Scripts

A Phenetic Approach to Selected Variants of Arabic and Aramaic Scripts

Osama A. Salman, Gábor Hosszú
Copyright: © 2022 |Pages: 23
DOI: 10.4018/IJDA.297519
OnDemand:
(Individual Articles)
Available
$37.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

This paper aims to introduce the phenetic method for processing paleographical datasets and evaluating their similarity relationships. The presented numerical taxonomic method was applied for selected varieties of the Arabic and Aramaic scripts. The phenetic model was evaluated by hierarchical clustering and—after applying multidimensional scaling—a centroid-based clustering method. The hierarchical clustering results were presented as dendrograms (phenograms), while the centroid-based results were given in 2- and 3-dimensional Cartesian coordinate systems. The obtained results demonstrate that the numerical taxonomy's phenetic approach is useful in describing the distances between different writing systems. The long-term goal of the research is to apply machine learning tools to clarify the relationships between the large number of Aramaic and Arabic script variants. This study belongs to the field of pattern evolution, in which machine learning methods of biological evolution are used to model evolving patterns (such as writing systems) over time.
Article Preview
Top

Introduction

Scriptinformatics deals with the investigation concerning the evolution of graphemes in scripts and the exploration of relationships between scripts, where scripts could be any sequence of symbols of cultural origin, such as historical writing systems (Hosszú, 2017; Hosszú, 2021a, p. 9). Evolutionary modeling of scripts includes phylogenetic modelling, namely phenetic, evolutionary, and statistical analyses of the studied scripts' features (Hosszú, 2014; Hosszú, 2021b).

This paper's main goal is to demonstrate how the developed exploratory data analysis algorithm applies to processing paleographical datasets and evaluating their phenetic modelling. The presented phenetic method was used for the selected varieties of the Arabic and Aramaic scripts. This modelling demonstrates that phenetic modelling, known from biology, can be used to detect similarities between otherwise closely related writing variants. The obtained phenetic results correlate well with their evolutionary relationships.

Complete Article List

Search this Journal:
Reset
Volume 5: 1 Issue (2024)
Volume 4: 1 Issue (2023)
Volume 3: 2 Issues (2022): 1 Released, 1 Forthcoming
Volume 2: 2 Issues (2021)
Volume 1: 2 Issues (2020)
View Complete Journal Contents Listing