In order to save shopping time and to help customers find the favorite goods conveniently from numerous merchandises,this paper attempted to develop an intelligent recommendation system for individual commodity based on association rules.We established the comprehensive score formula of commodity selection by introducing the FP-tree association rules,using the correlation index of the recommended formula and synthesizing some factors such as the maximum of benefits,hot commodity,etc..The merchandise recommendation service is based on the rank of comprehensive score,the sorted results are finally pushed to the customer.%为了节省顾客商品选购对间,帮助顾客从海量商品中快速找寻意购物品,本文尝试将关联规则与个性化导购相结合,引入FP-tree关联规则算法,利用商品推荐公式中的关联度,同时综合利用商家利益最大化、热销商品等因素,建立商品推荐综合评分公式.基于综合评分值对待推荐商品进行动态排序,并将排序结果推送给客户,实现个性化商品智能动态推荐服务.
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