贝叶斯网模型在推荐系统中的应用研究

Research of Applying Bayesian Network to Recommendation System

针对网上智能中推荐系统的个性化问题,提出了一种新的基于贝叶斯网模型的商品推荐方法,它包括贝叶斯网客户购物模型的建立和基于概率推理的推荐集的产生两个过程。实数据上的实验表明该方法是一种有效的能为不同客户产生准确而个性化的商品推荐方法。

Aiming at the personalization of recommendation systems in Web Intelligence, this paper presents a new commodity recommendation method based on Bayesian networks, which includes two phases: the building of customer shopping model of Bayesian network and the generation of recommendation sets based on probability inference. Experimental results on real world data show that this method is an effective method that can achieve personalized recommendation for different customers.