摘要
针对B2C网上购物的实际背景和要求,设计了一个运用多种技术相结合的个性化推荐系统模型,这种推荐模型既能有效解决单独关联规则推荐不适合同类产品推荐问题,又能有效解决协同过滤算法不适合异类产品推荐问题;既能有效处理电子商务中产品种类和类别层次繁多的产品推荐问题,又能加快推荐速度,在电子商务系统中具有良好的推荐效果和应用价值.
According to the background and request of the B2C online shopping,one kind of personalized recommendation system is designed.This kind of recommendation model,not only solves the same class product recommendation to which association rule is not suit and different class product recommendation to which collaborative filtering is not suit,but also improves recommending speed which is very key for online recommendation.Therefore,it greatly achieves good recommending results and application value in E-Commerce.
出处
《泰山学院学报》
2010年第3期30-33,共4页
Journal of Taishan University
基金
山东省教育科学"十一五"规划课题(2008GG068)
关键词
个性化推荐系统
协同过滤
关联规则
电子商务
personalized recommendation systems
collaborative filtering
association rule
E-Commerce
