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小世界网络在聚类应用中具有良好的性质,贝叶斯网络在概率推理中也得到了广泛的研究.将小世界网络和贝叶斯网络结合起来,形成了一种混合推荐模型.该混合模型由两层组成,分别是用户层和商品层.其中小世界网络用于描述用户层内用户-用户结点间的关系,贝叶斯网络用于描述商品层内商品-商品结点,以及层间用户-商品结点间的偏好关系.对小世界网络的用户聚类方法、贝叶斯网络结构和参数学习方法、以及两层混合模型的推荐算法进行了描述,实验表明,该模型能够很好地表示用户-用户、商品-商品、以及用户-商品间的关系,推荐结果具有良好的准确度.
Small-world networks have good properties in clustering applications, and Bayesian networks have also been widely studied in probability reasoning. Combining small-world networks with Bayesian networks, a hybrid recommendation model is formed. The model consists of two layers, user layer and commodity layer, of which the small-world network is used to describe the relationship between user-user nodes in the user layer, the Bayesian network is used to describe the commodity-product node in the product layer, and Layer user-commodity node.Clustering method of user-cluster in small-world network, Bayesian network structure and parameter learning method, as well as the recommendation algorithm of two-layer hybrid model are described.The experiment shows that this model can Good representation of user - user, product - product, and user - the relationship between the goods, the recommended results with good accuracy.