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›› 2005, Vol. 31 ›› Issue (13): 41-43.

• 论文 • 上一篇    下一篇

贝叶斯网模型在推荐系统中的应用研究

冀俊忠,沙志强,刘椿年   

  1. 北京工业大学多媒体与智能软件技术北京市重点实验室,北京工业大学多媒体与智能软件技术北京市重点实验室,北京工业大学多媒体与智能软件技术北京市重点实验室 北京 100022
  • 发布日期:2005-07-15

Research of Applying Bayesian Network to Recommendation System

JI Junzhong, SHA Zhiqiang, LIU Chunnian   

  1. (Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing 100022)
  • Published:2005-07-15

摘要: 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。

关键词: 网上智能, 贝叶斯网, 概率推理, 个性化推荐

Abstract: 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.

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