Deep Learning Based Prediction Model for the Next Purchase

Utku A., Akcayol M. A.

ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING, cilt.20, ss.35-44, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 20
  • Basım Tarihi: 2020
  • Doi Numarası: 10.4316/aece.2020.02005
  • Dergi Adı: ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Communication Abstracts, INSPEC, Metadex, Directory of Open Access Journals
  • Sayfa Sayıları: ss.35-44
  • Anahtar Kelimeler: time series analysis, deep learning, prediction, e-commerce, NEURAL-NETWORK, ARIMA, ALGORITHM, DEMAND
  • Gazi Üniversitesi Adresli: Evet

Özet

Time series represent the consecutive measurements taken at equally spaced time intervals. Time series prediction uses the information in a time series to predict future values. The future value prediction is important for many business and administrative decision makers especially in e-commerce. To promote business, sales prediction and sensing of future consumer behavior can help business decision makers in marketing campaigns, budget and resource planning. In this study, deep learning based a new prediction model has been developed for the time of next purchase in e-commerce. The proposed model has been extensively tested and compared with RF, ARIMA, CNN and MLP using a retail market dataset. The experimental results show that the developed model has been more successful than RF, ARIMA, CNN and MLP to predict the time of the next purchase.