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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作推荐算法

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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:针对协同推荐算法系统的质量,提出了一种基于筛选用户偏好的基于项目的协同过滤推荐算法。首先,用户对项目具有统一的兴趣度量,并基于兴趣的模糊隶属度对项目进行选择,以构建反映用户特征的项目偏好向量,利用向量之间的余弦距离,对用户进行分类基于加权项的协作过滤。实验表明,该算法在提高推荐的可靠性和准确性方面优于传统的协同过滤算法。

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