A No-Code Platform for Developing Customizable Recommender Systems for Restaurants

With the rapid growth of e-commerce and the increasing importance of recommender systems in enhancing customer experience, there is a pressing need for customized systems that can be quickly developed in collaboration with domain experts. In the restaurant industry, this need is particularly acute, as consumers seek personalized dining experiences that cater to their unique tastes and preferences. Effective recommender systems can assist restaurants not only in suggesting menu items based on individual customer profiles but also in adapting to local trends, dietary restrictions, and seasonal ingredients. In this paper, we introduce CURSOR, a novel no-code platform designed to automatically develop customizable recommender systems for restaurants. CURSOR enables businesses to design and deploy tailored systems without the need to hire specialized development teams. Our evaluation results demonstrate that CURSOR reduces development time, lowers costs, and enhances system performance for restaurants. The output from CURSOR enhances customer experience by providing personalized suggestions, which in turn increases satisfaction and encourages purchases.