Technical Note—The Multinomial Logit Model with Sequential Offerings: Algorithmic Frameworks for Product Recommendation Displays
研究顺序推荐问题，提出强多项式时间近似方案，并在Expedia酒店预订数据上验证模型拟合精度优于其他选择模型。
In the paper “The Multinomial Logit Model with Sequential Offerings: Algorithmic Frameworks for Product Recommendation Displays,” we consider a sequential assortment problem that has applications ranging from appointment scheduling in hospitals, restaurants, and fitness centers to product recommendation in e-commerce settings. Our main contribution comes in the form of a strongly polynomial-time approximation scheme for the most general form of the problem. We also conduct an extensive case study in which we fit our sequential model to historical search data from Expedia’s hotel booking platform. We observe substantial gains in fitting accuracy when our model is benchmarked against other well-known choice models designed for the setting at hand.