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协同过滤算法的优化研究
引用本文:熊波元,陈军华. 协同过滤算法的优化研究[J]. 上海师范大学学报(自然科学版), 2018, 47(5): 622-624
作者姓名:熊波元  陈军华
作者单位:上海师范大学 信息与机电工程学院, 上海 200234,上海师范大学 信息与机电工程学院, 上海 200234
摘    要:对协同过滤算法中用户相似性计算方面进行优化,在计算用户相似性的公式中添加用户兴趣偏差度作为权重,以提高相似性计算的准确性.通过实验对改进的算法进行了验证,结果表明改进的算法提高了推荐系统的准确度.

关 键 词:个性化推荐  协同过滤  相似性
收稿时间:2017-08-28

Research on collaborative filtering algorithm optimization
XIONG Boyuan and CHEN Junhua. Research on collaborative filtering algorithm optimization[J]. Journal of Shanghai Normal University(Natural Sciences), 2018, 47(5): 622-624
Authors:XIONG Boyuan and CHEN Junhua
Affiliation:College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China and College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China
Abstract:The calculation of user similarity was optimized. By adding the user interest bias as weight into the formula of the calculation of user similarity, the accuracy was highly improved. The experiment results showed that the improved algorithm could enhance the accuracy of the recommended system.
Keywords:personalized recommendation  collaborative filtering  similarity
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