摘要
餐饮信息化的快速发展将使用智能推荐系统分析客户的消费偏好,向客户提供更具针对性的点餐意见成为现实。推荐系统的运行既可以帮助客户更加合理地点餐、提升客户满意度,又可以有效提升餐饮企业的销售水平。文章在对基于关联规则的推荐系统进行分析讨论的基础上,提出面向分类预测的增量关联规则算法获取推荐规则,并进行实验验证。最后,在此基础上对点餐推荐系统的结构设计进行了研究。
The rapid development of the catering information technology makes the use of intelligent recommen- dation system a reality. The recommendation system may be used to analyze the preference of customers, and recommend dishes to targeted customers. Besides increasing customers＇ satisfaction, it also can promote the sale of the restaurant. This paper discusses the techniques of recommendation system based on association rules. Then it proposes a high efficiency incremental updating algorithm for mining classification association rules. Ex- periment results show that the algorithm is effective. Based on this, the structure of recommendation system is designed.
关键词
数据挖掘
关联规则
增量更新
频繁项集
推荐系统
data mining
association rules
incremental updating
frequent itemsets
recommendation system
