基于协同过滤的移动电子商务推荐算法
RECOMMENDATION ALGORITHMS FOR MOBILE E-COMMERCE BASED ON COLLABORATIVE FILTERING
随着移动电子商务的快速发展, 信息过载现象成为该领域的研究热点, 个性化移动推荐系统开始成为理论和应用的热点. 文章将协同过滤技术应用到移动电子商务中, 结合移动电子商务移动性和随时性的特点, 在协同过滤中加入时间因素和位置因素, 通过遗忘函数改进协同过滤算法, 最后实验证明改进的协同过滤移动推荐算法比传统的协同过滤算法能更有效地提高推荐精度.
With the rapid development of mobile e-commerce, the phenomenon of information overload has become a hot research topic in this field. The personalized mobile recommendation system has become the hot topic of theory and application. In this paper, collaborative filtering technique which is updated by the time factor and location factor is applied to the mobile e-commerce. Forgetting function improved collaborative filtering algorithm. Finally, the experiments prove that improved collaboration mobile filtering recommendation algorithm is better than the traditional collaborative filtering algorithm, which can improve the recommendation accuracy.
协同过滤 / 移动电子商务 / 推荐系统. {{custom_keyword}} /
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