BERT Modeli'nin Sınıflandırma Doğruluğunun Sıfır-Atış Öğrenmesi ile Artırılması

Yıl 2021, Cilt: 14 Sayı: 2, 99 - 108, 22.12.2021

Şükrü Ozan , Umut Özdil Davut Emre Taşar , Büşra Arslan Gökçe Polat

https://doi.org/10.54525/tbbmd.1004781

Cited By: 1

Öz

Bu çalışmada, çevrimiçi reklam platformlarında oluşturulan reklam metinlerinin sektöre göre otomatik olarak sınıflandırılması için Çift Yönlü Kodlayıcı Gösterimleri (BERT) modeli kullanılmıştır. Eğitim veri setimiz 44 farklı sektöre ait yaklaşık 101.000 adet, ilgili sektör isimleri ile etiketlenmiş reklam metninden oluşmaktadır. Sınıflandırma başarımının belirli sektörler için düşük olduğu gözlemlenmiştir. Bunun, ilgili eğitim veri setindeki aykırı bazı reklam metinlerinden kaynaklandığı gözlemlenmiştir. Bu sebeple sektör ve reklam metni uygunluğunu otomatik olarak tespit etmek ve veri seti için bir ön işleme gerçekleştirmek amacıyla doğal dil işleme (NLP) alanında güncel bir yöntem olan Sıfır-Atış Öğrenmesi yöntemi kullanılmıştır. Bu ön işleme çalışmasından sonra temizlenen veri seti ile tekrardan eğitilen BERT modelinin sınıflandırma başarımının önemli ölçüde arttığı gözlemlenmiştir.

Anahtar Kelimeler

Dijital Pazarlama, Reklam Metni, NLP, Metin Sınıflandırma, BERT, Sıfır-Atış Öğrenmesi

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