In view of the current E-commerce Recommender System can not be good for unregistered users, the paper set two different sets of data collection program according to the characteristics of unregistered users and registered users, in order to enhance the friendly of website and the accuracy of the data. Because the decision tree algorithm and bayesian network algorithms both have advantages and disadvantages, the paper uses a combination of two algorithms, and introduces the content-based algorithm to research the attribute of goods to improve the accuracy of the recommendation. The experiments prove that these methods can provide good service for unregistered users and the recommendation based on the hybrid algorithm is superior to single algorithm.
王虹予,赵英,党跃武. 基于混合算法的电子商务推荐系统设计研究[J]. 现代图书情报技术, 2009, 3(1): 80-85.
Wang Hongyu,Zhao Ying,Dang Yuewu. Design of an E-commerce Recommender System Based on Hybrid Algorithm. New Technology of Library and Information Service, 2009, 3(1): 80-85.
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