An Online Shoppers Purchasing Intention Model Based on Ensemble Learning
Küçük Resim Yok
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The sales trends and the visitors' purchase intention of e-commerce are crucial issues for companies. Therefore, companies want to know whether products are purchased based on customer visits. This study proposes an ensemble learning-based model to analyze customers' purchase intentions for e-commerce companies. It is possible to create a more accurate model using several machine learning methods within a system, which is the ensemble learning approach. The prediction performance of the proposed model is evaluated by different metrics, such as accuracy, precision, recall, AUC, and F-score. This paper aims to improve the purchasing rates of online shopping sites by determining the rate of visitors who intend to purchase but leave the site without taking action by using information such as the click flow of visitors. © 2023 IEEE.
Açıklama
4th International Informatics and Software Engineering Conference, IISEC 2023 -- 21 December 2023 through 22 December 2023 -- -- 196814
Anahtar Kelimeler
E-Commerce, Ensemble Learning, Online Shoppers' Behavior, E-Learning, Electronic Commerce, Purchasing, Sales, Accurate Modeling, E- Commerces, Ensemble Learning, Intention Modeling, Learning Based Models, Machine Learning Methods, Model-Based Opc, Online Shopper' Behavior, Online Shops, Purchase İntention, Learning Systems
Kaynak
4th International Informatics and Software Engineering Conference - Symposium Program, IISEC 2023
WoS Q Değeri
Scopus Q Değeri
N/A
