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Collaborative Filtering Recommendation Algorithm Based on Cloud Model Clustering of Multi-indicators Item Evaluation

机译:基于云模型聚类的协作过滤推荐算法 - 多指示物品评估

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Collaborative filtering recommendation algorithm is a personalized recommendation algorithm that is used widely in e-commerce recommendation system. In this paper, a collaborative filtering recomendation algorithm based on cloud model clustering of multi-indicators item evaluation is proposed. In the algorithm, the item evaluation is the object, time weighted function is introduced to item evaluation, soft culsters item based on cloud model and gets the recommended items. The algorithm solves problems of data updating and history validity of evaluation in the collaborative filtering algorithm. Soft cluster item based on cloud model is achieved to avoid the defects bringed by hard division.
机译:协作过滤推荐算法是一个个性化推荐算法,广泛用于电子商务推荐系统。本文提出了一种基于多指示器项目评估的云模型聚类的协同滤波重构算法。在算法中,项目评估是对象,将时间加权函数引入项目评估,基于云模型的软CULsters项目并获取推荐的项目。该算法解决了协同滤波算法中评估的数据更新和历史有效性的问题。实现了基于云模型的软簇项目,以避免硬部门带来的缺陷。

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