A Model for Collaborative Filtering Recommendation in E-Commerce Environment

In modern business environment, product life cycle gets shorter and the customer's buying preference changes over time. Time plays a more and more important role in collaborative filtering. However, there is a gap in one class collaborative filtering (OCCF). On the basis of collecting different real-time information, this paper proposes an optimization model for e-retailers. Through comparing different methods with different weights, results show that real-time dependent in OCCF performs better in improving the quality of recommendation. The model is effective in cross-selling e-commerce, personalized, targeted recommendation sales.