摘要
本文在计算用户评分相似度的基础上,引入了用户人口统计属性相似度。将用户评分相似度和人口统计属性相似度进行加权线性融合得到用户相似度,根据用户相似度为目标用户选取相似邻居集。最终为目标用户产生推荐。最后通过仿真实验验证了该算法的有效性。
User demographic attribute similarity is introduced based on user rating similarity. The similarity between user rating similarity and demographic attribute similarity is weighted linearly to get user similarity. The similar neighbor set of target user is selected according to user similarity. Finally, drugs are recommended to target user. Finally, the effectiveness of the algorithm is verified by simulation experiments.
作者
周锡玲
张莉敏
田小路
宋强
Zhou Xiling;Zhang Limin;Tian Xiaolu;Song Qiang(Guangdong Polytechnic College,Zhaoqing Guangdong,526100)
出处
《电子测试》
2018年第21期68-69,共2页
Electronic Test
关键词
协同过滤
人口统计属性
用户相似度
collaborative filtering
demographic attribute
user similarity
