Mirzayev, EmilBabutsitdze, ZakariaRand, WilliamDelahaye, Thierry2020-12-242020-12-242021-01-05978-0-9981331-4-0http://hdl.handle.net/10125/71135The cold-start problem has become a significant challenge in recommender systems. To solve this problem, most approaches use various user-side data and combine them with item-side information in their systems design. However, when such user data is not available, those methods become unfeasible. We provide a novel recommender system design approach which is based on two-stage decision heuristics. By utilizing only the item-side characteristics we first identify the structure of the final choice set and then generate it using stochastic and deterministic approaches.9 pagesEnglishAttribution-NonCommercial-NoDerivatives 4.0 InternationalElectronic Marketingclusteringcold-start problemrecommender systemstwo-stage choice10.24251/HICSS.2021.518