基于关联规则的推荐系统在电子商务中的应用

电子商务的发展加剧了企业的竞争。为了充分应用商务网站的信息,本文提出了建立基于关联规则的电子商务的推荐系统;探讨了电子商务推荐系统模型、生成关联规则和形成推荐集的过程。主要应用FP-Tree算法挖掘客户的行为模式和购买组合,根据用户的兴趣度和置信度产生相应的推荐侯选集,实现网站的个性化服务。根据挖掘的客户知识,网站可以制定针对目标客户的营销方案,从而提高客户的忠诚度,增加商务网站的赢利水平和竞争能力。

The Applications of E-Commerce Recommendations Based on Association Rules

The e-commerce leads to the more-intensive competition among the entities,to make full use of the information on the web site,it proposes the e-commerce recommendations based on association rules.It studied the system model,association rules and how to give the recommenders.By analyzing and mining the customers' on-line purchasing,the association rules were find by means of FP-Tree algorithm.Then the patterns for frequently purchasing were extracted by filtering support degrees.The candidating webs to be recommendated can be determined according to the customers' interest degree and the credibility of the rules,so that personalization recommdation services could be provided.Then the company makes the selling promotion for the special customers.It would increase the customer's loyalty and bring a promotion of profit as well as the competition for the enterprise.