Affiliation:
1. Budapest University of Technology and Economics, Hungary
Abstract
This chapter presents statistical evaluations of script relics. Its concept is exploiting mathematical statistical methods to extract hidden correlations among different script relics. Examining the genealogy of the graphemes of scripts is necessary for exploring the evolution of the writing systems, reading undeciphered inscriptions, and deciphering undeciphered scripts. The chapter focuses on the cluster analysis as one of the most popular mathematical statistical methods. The chapter presents the application of the clustering in the classification of Rovash (pronounced “rove-ash,” an alternative spelling: Rovas) relics. The various Rovash scripts were used by nations in the Eurasian Steppe and in the Carpathian Basin. The specialty of the Rovash paleography is that the Rovash script family shows a vital evolution during the last centuries; therefore, it is ideal to test the models of the evolution of the glyphs. The most important Rovash script is the Szekely-Hungarian Rovash. Cluster analysis algorithms are applied for determining the common sets among the significant Szekely-Hungarian Rovash alphabets. The determined Rovash relic ties prove the usefulness of the clustering methods in the Rovash paleography.
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