杨丽丽,袁浩浩

• 1:广西政法管理干部学院
• 2:广西科技大学

摘要(Abstract)：

针对传统推荐系统中的协同过滤推荐算法无法解决数据间的高度稀疏问题,采用余弦相似性度量运算的物品相似性误差较高,导致系统推荐质量降低,提出基于局部组合优化的协同过滤推荐算法,其改进了物品间相似性的运算,为了解决数据稀疏性问题,选择目标的近邻对象时利用局部优化方法选择推荐群,降低了预测的误差,确保误差值收敛到某固定值,并采用基于内容的方法调整协同过滤预测存在的异常预测结果。实验结果表明,所提算法抑制了数据稀疏性的不利影响,提高了协同过滤预测评分的准确度。

关键词(KeyWords)： 局部;组合优化理论;协同过滤;推荐算法;稀疏问题;评分精度

Abstract:

Keywords:

基金项目(Foundation): 广西科技厅项目(桂科攻1598010-4);; 广西高校青年教师基础能力提升项目(桂教科研KY2016YB746,2017KY1032)~~

作者(Author): 杨丽丽,袁浩浩

DOI: 10.16652/j.issn.1004-373x.2018.01.031

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