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Received:November 12, 2013 Revised:December 06, 2013
Received:November 12, 2013 Revised:December 06, 2013
中文摘要: 针对O2O电子商务平台推荐准确率低的问题,本文从用户活跃度和用户权威度两个方面计算用户全局信任度,引入用户之间的信任关系对传统的协同过滤算法进行改进,设定信任度阀值来确定邻居用户的范围,在此基础之上结合信任度和相似度两个因素确定邻居用户,以信任度和相似度结合的混合值作为推荐权重,实验证明,该算法与传统的协同过滤推荐算法和基于信任关系的推荐算法相比有更好的效果.
Abstract:According to the problem of the low precision rate of resources recommended in O2O E-Commerce platform, the paper calculates user's global-trust in the system from two aspects of user activity and user authority. On this basis, it improves the traditional collaborative filtering algorithm with the introduction of trust relationship between users. It sets confidence threshold to determine the scope of neighboring users. On this basis, combined with trust and similarity to determine the neighbor users, this work puts their combined mixed Numerical as recommended weights. The experimental results can prove the validity and superiority of the proposed algorithm.
keywords: trust collaborative filtering algorithm
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吴慧,卞艺杰,赵喆,马瑞敏.基于信任的协同过滤算法.计算机系统应用,2014,23(7):131-135
WU Hui,BIAN Yi-Jie,ZHAO Zhe,MA Rui-Min.Collaborative Filtering Algorithm Based on Trust.COMPUTER SYSTEMS APPLICATIONS,2014,23(7):131-135
吴慧,卞艺杰,赵喆,马瑞敏.基于信任的协同过滤算法.计算机系统应用,2014,23(7):131-135
WU Hui,BIAN Yi-Jie,ZHAO Zhe,MA Rui-Min.Collaborative Filtering Algorithm Based on Trust.COMPUTER SYSTEMS APPLICATIONS,2014,23(7):131-135

