Determination of Channel Effects on User Conversion Rate in Online Advertising by Deep Learning Derin Öǧrenme ile Çevrimiçi Reklamlarda Kullanici Dönüşüm Oranlari Üzerindeki Kanal Etkilerinin Belirlenmesi

Kahraman O., KARSLIGİL M. E.

30th Signal Processing and Communications Applications Conference, SIU 2022, Safranbolu, Türkiye, 15 - 18 Mayıs 2022 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu55565.2022.9864991
  • Basıldığı Şehir: Safranbolu
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: Long-Short term memory, multi-channel, online advertising
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

In online advertising, multi-touch attribution and distributing credits is big challenge for publishers. The common approach to solve this problem is that allocating the budget to the resources by visual evaluation by experts. Current solutions are not effective due to size of the data, the diversity of sources and channels, and the need to make decisions in a short time. In this paper, an LSTM based deep learning model was designed and implemented for determining the effect of different advertising sources on the user's purchase in online advertisements.