Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/12007
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yazar, U.T. | - |
dc.contributor.author | Kutlu, M. | - |
dc.date.accessioned | 2025-01-10T21:00:47Z | - |
dc.date.available | 2025-01-10T21:00:47Z | - |
dc.date.issued | 2024 | - |
dc.identifier.isbn | 979-835037943-3 | - |
dc.identifier.uri | https://doi.org/10.1109/ASYU62119.2024.10757040 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/12007 | - |
dc.description | IEEE SMC; IEEE Turkiye Section | en_US |
dc.description.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. © 2024 IEEE. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.ispartof | 2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 16 October 2024 through 18 October 2024 -- Ankara -- 204562 | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Natural Language Processing | en_US |
dc.subject | Semantic Change | en_US |
dc.subject | Turkish | en_US |
dc.title | Detecting Turkish Synonyms Used in Different Time Periods | en_US |
dc.type | Conference Object | en_US |
dc.department | TOBB University of Economics and Technology | en_US |
dc.identifier.scopus | 2-s2.0-85213314441 | - |
dc.identifier.doi | 10.1109/ASYU62119.2024.10757040 | - |
dc.authorscopusid | 58973095800 | - |
dc.authorscopusid | 35299304300 | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | N/A | - |
dc.identifier.wosquality | N/A | - |
item.languageiso639-1 | en | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
item.cerifentitytype | Publications | - |
item.openairetype | Conference Object | - |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
CORE Recommender
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.