门店以销量取胜，需避免随意性与盲目性来控制库存。本文研究了净菜连锁门店一年的销售数据，基于Apriori关联规则算法，应用IBM的Modeler平台，构造出连锁门店的净菜关联规则挖掘模型。挖掘到了24条提升度大于3的关联规则，与居民的烹饪规律高度吻合，证明了算法模型的科学性。规则从数万条交易记录中提取，能够优化门店的菜品配置，也能指导菜品上架。
Shops which win with sales volume, must avoid casualness and blindness to control stocks. With a whole year clean dishes sale data of chain shops, based on the Apriori association rule arithmetic, applying IBM modeler platform, it has constructed an association rule mining model of clean dishes in chain shops. 24 association rules, highly close to the dietary pattern of residents, have been gotten with lift bigger than 3, which prove the scientific of this arithmetic model. These rules, drawn from tens of thousands of transaction records, can optimize dish items configuration and guide to stack them on shelves.
