摘要
为了节省顾客商品选购时间,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。
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.
出处
《价值工程》
2017年第35期199-201,共3页
Value Engineering
基金
上海市2015年度"科技创新行动计划"高新技术领域项目(15511102100)
上海市2015年度"科技创新行动计划"高新技术领域项目--基于大数据分析技术的社区便民服务平台和示范应用(项目编号:15511102100)资助
研究成果在上海市嘉定区智慧社区管理平台已经得到了实际应用
关键词
个性化商品导购
数据挖掘
关联规则
智能推荐系统
guiding-purchase of individual commodity
data mining
association rules
intelligent recommendation system
