摘要
为满足B2B电子商务平台下供应商选择个性化服务需求,引入云模型中云的相似性度量算法和基于资源相似度的数据权重,对基于项目的协同过滤推荐算法进行改进,并用于供应商推荐过程中。实验表明,改进后的算法可以在一定程度上解决数据稀疏性问题并及时反映用户兴趣变化,从而实现个性化推荐服务,帮助企业快速有效开发供应商伙伴关系,提高企业的生产效率和竞争力。
In order to meet the demand of personalized service for supplier selection found on B2B E-business platform, both the measurement method of cloud similarity and item similarity-based data weight are combined efficiently to improve the algorithms ofitem-based collaborative filtering, and the improved algorithm is applied to the supplier recommendation process. Experimental results show that the improved algorithm can solve the problem of data sparsity and consider the change of users interests in some extent, thus , it implements personalized recommendation service and contributes to the enterprise ’s friendship developing with suppliers and production efficiency and competitive power as well.
出处
《微计算机信息》
2011年第2期56-58,共3页
Control & Automation
关键词
供应商选择
协同过滤
云模型
基于资源相似度的数据权重
个性化推荐
supplier selection
collaborative filtering
cloud model
item similarity-based data weight
personalized recommendation
