Detecting Turkish Synonyms Used in Different Time Periods

Dynamic structure of languages poses significant challenges in applying natural language processing models on historical texts, causing decreased performance in various downstream tasks. Turkish is a prominent example of rapid linguistic transformation due to the language reform in the 20th century. In this paper, we propose two methods for detecting synonyms used in different time periods, focusing on Turkish. In our first method, we use Orthogonal Procrustes method to align the embedding spaces created using documents written in the corresponding time periods. In our second method, we extend the first one by incorporating Spearman's correlation between frequencies of words throughout the years. In our experiments, we show that our proposed methods outperform the baseline method. Furthermore, we observe that the efficacy of our methods remains consistent when the target time period shifts from the 1960s to the 1980s. However, their performance slightly decreases for subsequent time periods.

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Publication Details

Published
2024-10-16
DOI
https://doi.org/10.1109/asyu62119.2024.10757040
Primary Topic
Natural Language Processing Techniques
Type
article
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article

Detecting Turkish Synonyms Used in Different Time Periods

Mücahid Kutlu, Umur Togay Yazar
Natural Language Processing Techniques
article

Detecting Turkish Synonyms Used in Different Time Periods

Mücahid Kutlu, Umur Togay Yazar
article en

Abstract

Dynamic structure of languages poses significant challenges in applying natural language processing models on historical texts, causing decreased performance in various downstream tasks. Turkish is a prominent example of rapid linguistic transformation due to the language reform in the 20th century. In this paper, we propose two methods for detecting synonyms used in different time periods, focusing on Turkish. In our first method, we use Orthogonal Procrustes method to align the embedding spaces created using documents written in the corresponding time periods. In our second method, we extend the first one by incorporating Spearman's correlation between frequencies of words throughout the years. In our experiments, we show that our proposed methods outperform the baseline method. Furthermore, we observe that the efficacy of our methods remains consistent when the target time period shifts from the 1960s to the 1980s. However, their performance slightly decreases for subsequent time periods.

TOBB University of Economics and Technology (TR), Qatar University (QA)
Openalex Percentile: Top 77%
Natural Language Processing Techniques
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Detecting Turkish Synonyms Used in Different Time Periods — Mücahid Kutlu, Umur Togay Yazar · (2024) | TGRS Research Map | TGRS