摘要
以数据挖掘中的关联规则理论为基础,从应用的角度出发,设计了一套相关产品推荐系统ARecom,实现了电子购物中的个性化服务。针对直接决定整体算法效率的频繁大项集生成步骤,应用大量的数据,研究比较了三种典型算法,并在此基础上,提出了适合电子商务相关推荐系统的完整的算法模型。
Based on the Association Rule theory in data mining technology, a suit of Correlated-Product Recommendation System is designed for the individuation service in e-marketing. By using much correlated data, we study and compare three typical algorithms for generating the frequent item-set that is the most important step for the whole efficiency. At last an integrated algorithm model, which is well suitable for the system in e-commerce,is given.
关键词
关联规则
个性化
相关产品推荐
association rule
individuation
correlated-product recommendation
