A Heuristic Hybrid Recommended Order Modle

Yi Yang, Baolin Li, Jianqiao Hu
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Abstract

As the informationized trend is developing toward intelligentized one in catering industry, the targeted ordering recommendation provide for customer based on the technique of intelligent recommendation has turned into reality. Applying in the scenario of traditional Chinese food service, a heuristic and hybrid model in ordering recommendation is proposed. First, the association rules algorithm was adopted for obtaining the association rules of historically associated dishes combination and calculating their correlation degree. Second, applying the recommended algorithm based on dishes attributes to calculate the similarities of dishes in the database. Third, to calculate comprehensive scores of dishes and create the recommendation rules in accordance with their correlation degree and similarities. Finally, a recommended order list is shaped from both the dishes ordered and the recommendation rules concluded in the former step. The effectiveness and validation of the model and algorithm are being proved by real order data in Chinese restaurants. The data shows the model is better than traditional association rules in the aspects of recommendation precision and coverage when the dishes ordered reaching to certain amount.
一种启发式混合推荐排序模型
随着餐饮业信息化趋势向智能化发展,基于智能推荐技术为顾客提供有针对性的点餐推荐已经成为现实。针对传统中式餐饮服务场景,提出了一种启发式混合点餐推荐模型。首先,采用关联规则算法获取历史关联菜肴组合的关联规则并计算其关联度;其次,应用基于菜肴属性的推荐算法计算数据库中菜肴的相似度。第三,计算菜品的综合评分,并根据菜品的关联度和相似度创建推荐规则。最后,根据所点的菜肴和在前一步中得出的推荐规则形成推荐点单。通过中餐馆的实际订单数据,验证了该模型和算法的有效性。数据表明,当点餐量达到一定数量时,该模型在推荐精度和覆盖范围上都优于传统关联规则。
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