摘要
针对用户不确定性决策问题,提出基于变精度双论域粗糙集的个性化推荐方法。首先,基于置信度的含义提出一种新的知识库构建方法,并利用SQL语言实现。在此基础上构建基于变精度双论域粗糙集的个性化推荐模型,并将该模型应用到男士衬衫的个性化推荐中。最后通过推荐方法比较分析,实验结果说明了基于变精度双论域粗糙集的个性化推荐模型的有效性。
Aiming at the problem of user uncertainty decision, a personalized recommendation method based on variable precision dual-universe rough set is proposed. First, a new knowledge base construction method is proposed based on the meaning of confidence, and implemented by SQL language. Based on this, a personalized recommendation model based on variable-precision dual-domain rough set is proposed, and the model is applied to the personalized recommendation of men, s shirts. Finally, the effectiveness of the personalized recommendation model based on variable precision dual-universe rough sets is illustrated by the comparative analysis of experimental results.
出处
《计算机应用与软件》
2017年第6期250-256,共7页
Computer Applications and Software
基金
国家自然科学基金项目(71301100)
上海市教委科研创新项目(14YZ140)
上海市教委青年教师计划项目(ZZGJD12036)
上海市自然科学基金项目(16ZR1414000)
上海工程技术大学研究生科研创新项目(15KY0354)
关键词
变精度粗糙集
双论域
个性化推荐
关联规则
非确定性决策
Variable precision rough set Dual-universe Personalized recommendation Association rule Uncer-tainty decision-making
