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Informatics Colloquium 22. 5. Recommender System Research in E-CommerceInformatics Colloquium 22. 5. 2018, 14:00 lecture hall D2 Mouzhi Ge, Ph.D., FI MU Recommender System Research in E-Commerce Abstract: Over the last decade, recommender systems have been widely applied in e-commerce, for example, video recommendations in Youtube, book recommendation on Amazon, and movie recommendation on Netﬂix. Recommender systems are developed to help users ﬁnd relevant products that may interest them. The goal of recommender systems is to reduce the information overload and provide personalized recommendations for users. In this talk, I will discuss the state-of-the-art research of recommender system in E-Commerce, which includes rationale and algorithms inside the recommender black box, important features and evaluations in recommender systems. Finally, a real-world food recommender system project in E-Commerce will be described and demonstrated to show how to construct and evaluate the recommender system in practice, as well as possible challenges that are related to the food recommender systems.