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E-Commerce Product Recommendation Method Based on Collaborative Filtering Technology

机译：基于协同过滤技术的电子商务产品推荐方法

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摘要

This paper concentrates on the problem of E-commerce product recommendation, and E-commerce market has attracted more and more attentions. Collaborative filtering algorithm supposes that when two users have similar ratings on products, they may have similar preferences. To combine the user preference information and the collaborative filtering model together, we suppose that if there are two users who share the similar interest, it is very possible for them to select similar products. Afterwards, we design an E-commerce product recommendation algorithm based on collaborative filtering model to compute the recommendation score. Finally, experimental results prove that the proposed method can recommend more relevant products for users with high accuracy.
机译：本文主要针对电子商务产品推荐问题，电子商务市场引起了越来越多的关注。协作过滤算法假设，当两个用户对产品的评分相似时，他们可能会具有相似的偏好。为了将用户偏好信息和协作过滤模型组合在一起，我们假设如果有两个用户拥有相似的兴趣，那么他们选择相似产品的可能性就很大。然后，我们设计了基于协同过滤模型的电子商务产品推荐算法，以计算推荐分数。最后，实验结果表明，该方法可以为用户推荐更多相关产品。

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