International Journal of Electronic Commerce
Web-Based Recommender Systems and User Needs --the Comprehensive View
Proceedings of the 2008 conference on New Trends in Multimedia and Network Information Systems
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Recommender systems are a powerful tool for promoting sales in electronic commerce. An effective shopping recommender system can help boost the retailer驴s sales by reminding customers to purchase additional products originally not on their shopping lists. Existing recommender systems are designed to identify the top selling items, also called hot sellers, based on the store驴s sales data and customer purchase behaviors. It turns out that timely reminders for unsought products, which are cold sellers that the consumer either does not know about or does not normally think of buying, present great opportunities for significant sales growth. In this paper, we propose the framework and process of a recommender system that identifies potential customers of unsought products using boosting-SVM. The empirical results show that the proposed approach provides a promising solution to targeted advertisement for unsought products in an E-Commerce environment.