Personal recommendation algorithm with customer preference model and BP neural networks

Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (2): 57-60.

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Personal recommendation algorithm with customer preference model and BP neural networks

XIN Juqin1, JIANG Yan1, SHU Shaolong2

1.School of Business, University of Shanghai for Science and Technology, Shanghai 200093, China
2.School of Electronics and Information Engineering, Tongji University, Shanghai 200092, China

Online:2013-01-15 Published:2013-01-16

综合用户偏好模型和BP神经网络的个性化推荐

辛菊琴1，蒋艳1，舒少龙2

1.上海理工大学管理学院，上海 200093
2.同济大学电子与信息工程学院，上海 200092

Abstract

Abstract: Personal recommendation is very effective to find the useful information from database of products for customers in electronic commerce. The paper investigates personal recommendation algorithms based on customer preference model and BP neural networks. In details, a customer preference model is proposed and BP neural network is used to train the model. Movielens database is used to verify the validity of BP neural network model. A content-based personal recommendation algorithm is proposed.

Key words: electronic commerce, personal recommendation algorithm, neural networks, product feature, customer preference

摘要： 个性化推荐是目前解决电子商务中产品信息过载问题的有效工具之一。对综合用户偏好模型和BP神经网络的个性化推荐算法进行了研究。具体讨论了如何建立用户偏好模型，采用神经网络训练得到目标用户的偏好模型，通过Movielens数据库验证该模型的有效性。提出了一个基于内容的个性化推荐算法。

XIN Juqin1, JIANG Yan1, SHU Shaolong2. Personal recommendation algorithm with customer preference model and BP neural networks[J]. Computer Engineering and Applications, 2013, 49(2): 57-60.

辛菊琴1，蒋艳1，舒少龙2. 综合用户偏好模型和BP神经网络的个性化推荐[J]. 计算机工程与应用, 2013, 49(2): 57-60.

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Personal recommendation algorithm with customer preference model and BP neural networks

综合用户偏好模型和BP神经网络的个性化推荐

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