A Personalized Recommender System Based on a Hybrid Model

作者：Hussein Wedad^*; Ismail Rasha M; Gharib Tarek F; Mostafa Mostafa G M

来源：Journal of Universal Computer Science, 2013, 19(15): 2224-2240.

• Recommender Systems
• Web Usage Mining
• Next Page Prediction

Recommender systems are means for web personalization and tailoring the browsing experience to the users%26apos; specific needs. There are two categories of recommender systems; memory-based and model-based systems. In this paper we propose a personalized recommender system for the next page prediction that is based on a hybrid model from both categories. The generalized patterns generated by a model based techniques are tailored to specific users by integrating user profiles generated from the traditional memory-based system%26apos;s user-item matrix. The suggested system offered a significant improvement in prediction speed over traditional model-based usage mining systems, while also offering an average improvement in the system accuracy and system precision by 0.27% and 2.35%, respectively.

• 出版日期2013