论文标题
在快餐店的售货亭推荐系统中使用语言模型
Using a Language Model in a Kiosk Recommender System at Fast-Food Restaurants
论文作者
论文摘要
售货亭是许多快餐店中流行的自助服务选项，它们为游客节省了时间，并为快餐连锁店节省了劳动力。在本文中，我们提出了售货亭购物车推荐系统的有效设计，该系统将语言模型组合为矢量器和基于神经网络的分类器。该模型在离线测试中的性能优于其他模型，并且展示性能与A/B/C测试中最佳模型相当。
Kiosks are a popular self-service option in many fast-food restaurants, they save time for the visitors and save labor for the fast-food chains. In this paper, we propose an effective design of a kiosk shopping cart recommender system that combines a language model as a vectorizer and a neural network-based classifier. The model performs better than other models in offline tests and exhibits performance comparable to the best models in A/B/C tests.
