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Building Electronic Commerce Recommendation System Based on Ontology Learning and BP Neural Network

机译:基于本体学习的电子商务推荐系统和BP神经网络

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Electronic commerce recommendation system can effectively retain user, prevent users from erosion, and improve e-commerce system sales. BP neural network using iterative operation, solving the weights of the neural network and close values to corresponding network process of learning and memory, to join the hidden layer nodes of the optimization problem of adjustable parameters increase. Ontology learning is the use of machine learning and statistical techniques, with automatic or semi-automatic way, from the existing data resources and obtaining desired body. The paper presents building electronic commerce recommendation system based on ontology learning and BP neural network. Experimental results show that the proposed algorithm has high efficiency.
机译:电子商务推荐系统可以有效地保留用户,防止用户免受侵蚀,并改善电子商务系统销售。 BP神经网络采用迭代操作,解决神经网络的权重,将值贴近的学习和存储器的相应网络过程,加入可调参数的优化问题的隐藏层节点。本体学习是使用机器学习和统计技术,具有自动或半自动方式,从现有的数据资源和获得所需的身体。本文介绍了基于本体学习和BP神经网络的电子商务推荐系统。实验结果表明,该算法具有高效率。

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