Abstract
Text classification is one of the most important issues in natural language processing. In this study, texts belonging to different problems were classified using classical machine learning and deep learning methods. Additionally, transformer-based classifiers using transfer learning were also used, and the effects of transfer learning on classification success were examined. As a result of the experiments, it was seen that higher performance was obtained from the transfer learning based Bert classifier compared to other methods. With the study, transfer learning effect in Turkish text classification was examined in detail.
Keywords
Transfer of learning
Turkish
Artificial intelligence
Computer science
Classifier (UML)
Natural language processing
Machine learning
Learning classifier system
Transformer
Deep learning
Unsupervised learning
Linguistics
Engineering
Subject Areas
Topic Modeling
·Artificial Intelligence ·Physical Sciences
Natural Language Processing Techniques
·Artificial Intelligence ·Physical Sciences
Text and Document Classification Technologies
·Artificial Intelligence ·Physical Sciences
Citations by Year
2022: 1
2023: 2
2025: 2
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