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An item-based weighted collaborative recommended algorithm based on screening users' preferences

机译:基于筛选用户偏好的基于项目的加权协同推荐算法

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Facing the quality of the collaborative recommendation algorithm system, an item-based collaborative filtering recommendation algorithm based on screening users' preferences was put forward. First, users have a unified interest measure for the project, and have a selection for the project based on the fuzzy membership of interests to build to project preference vector which reflects the user characteristics, using the cosine distance between vectors, the users were classified based on the weighted Item-based collaborative filtering. Experiments show that the algorithm is better than the traditional collaborative filtering algorithms in improving the recommendation dependability and accuracy.
机译:面对协作推荐算法系统的质量,提出了一种基于项目的协作过滤推荐算法,基于筛选用户的偏好。首先,用户对项目有统一的兴趣措施,并根据利益模糊成员资格对项目偏好向量的模糊会员资格进行选择,这些偏好矢量反映用户特征,使用向量之间的余弦距离,用户被基于分类在基于加权项目的协同滤波上。实验表明,该算法优于传统的协作滤波算法,提高了推荐可靠性和准确性。

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