| Issue |
MATEC Web Conf.
Volume 292, 2019
23rd International Conference on Circuits, Systems, Communications and Computers (CSCC 2019)
|
|
|---|---|---|
| Article Number | 03018 | |
| Number of page(s) | 5 | |
| Section | Computers | |
| DOI | https://doi.org/10.1051/matecconf/201929203018 | |
| Published online | 24 September 2019 | |
Using Data Mining Algorithms to Discover Regular Sound Changes among Languages
Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA
a Corresponding author: revesz@cse.unl.edu
This paper presents a method of using association rule data mining algorithms to discover regular sound changes among languages. The method presented has a great potential to facilitate linguistic studies aimed at identifying distantly related cognate languages. As an experimental example, this paper presents the application of the data mining method to the discovery of regular sound changes between the Hungarian and the Sumerian languages, which separated at least five thousand years ago when the Proto-Sumerian reached Mesopotamia. The data mining method discovered an important regular sound change between Hungarian word initial /f/ and Sumerian word initial /b/ phonemes.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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