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Recommendation algorithm based on collaborative filtering under social network environment

机译:社交网络环境下基于协同过滤的推荐算法

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A collaborative recommendation algorithm based on community found is proposed in this paper. The idea of community is introduced in collaborative recommendation, at the same time the scoring pre-treatment is joined, in order to solve some problems in the traditional collaborative filtering recommendation. Results demonstrate that algorithm proposed in this paper is better than the algorithms based on the Pearson similarity and Cosine similarity.
机译:提出了一种基于社区发现的协同推荐算法。在协同推荐中引入了社区思想,同时加入了评分预处理,以解决传统协同过滤推荐中的一些问题。结果表明,本文提出的算法优于基于皮尔逊相似度和余弦相似度的算法。

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