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The collaborative filtering algorithm based on domain ontology and user preferences

机译:基于领域本体和用户偏好的协同过滤算法

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摘要

This paper proposes a method of user ratings similarity, based on forgetting function, which adjusts the importance of the user ratings according to time, considering the impact of the changes in user's preferences. While the user clustering algorithm is presented, which takes into account the personal characteristics of the user's information to affect its form ultimately choose to purchase goods weighting factor improved characteristics of the user similarity algorithm, reducing the nearest neighbor range of options.
机译:本文提出了一种基于遗忘功能的用户评分相似度计算方法,该方法考虑了用户偏好变化的影响,根据时间调整了用户评分的重要性。当提出用户聚类算法时,它考虑了用户信息的个人特征以影响其形式,最终选择购买商品加权因子,改善了用户相似性算法的特征,减小了选项的最近邻范围。

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