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通过数据挖掘在电子商务推荐系统中的运用,在使用关联算法的基础上为客户构建虚拟导购。同时,可分析某一热销产品捆绑另一产品可被一同购买的几率为多少。通过对客户偏好的商品类别分析和捆绑销售模式为顾客提供量身定制的服务,同时将电子商务平台所得利益最大化。本文简要介绍了电子商务推荐系统,在积累了前人构建挖掘模型的基础上建立了基于Apriori算法的电子商务推荐系统。研究关联规则算法在电子商务推荐系统中的应用,目前,Apriori算法已被广泛的运用到多个领域,准确度高、简单化等优点十分利于机器记忆与学习。
Through the application of data mining in e-commerce recommendation system, we construct virtual shopping guide for customers based on the association algorithm. In the meantime, you can analyze how likely a hot product is to be bundled with another product. Through the analysis of the customer’s preferred product category and bundled sales model to provide customers with tailor-made services, while maximizing the benefits of e-commerce platform. This article briefly introduces the e-commerce recommendation system, builds the e-commerce recommendation system based on Apriori algorithm based on the accumulation of previous models of mining. At present, the Apriori algorithm has been widely used in many fields. The advantages of high accuracy and simplification are very good for machine memory and learning.