A comparison of clustering-based privacy-preserving collaborative filtering schemes
Applied Soft Computing
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E-commerce recommendation system is one of the most important and the most successful application field of data mining technology. Recommendation algorithm is the core of the recommendation system. In this paper, a neural networks-based clustering collaborative filtering algorithm in e-commerce recommendation system is designed, trying to establish an classifier model based on BP neural network for the pre-classification to items and giving realization of clustering collaborative filtering algorithm and BP neural network algorithm, and carring on the analysis and discussion to this algorithm from multiple aspects. This algorithm is helpful to improve sparsity problem of collaborative filtering algorithm and to form the more effective and the more accurate recommendation result.