This document summarizes Xavier Amatriain's presentation on recommender systems. It discusses traditional recommendation methods like collaborative filtering, content-based recommendations, and hybrid approaches. It also covers newer methods that go beyond traditional techniques, such as learning to rank, deep learning, social recommendations, and context-aware recommendations. Throughout the pres
Evaluating Recommender Systems with User Experiments Bart P. Knijnenburg, Martijn C. Willemsen Abstract Proper evaluation of the user experience of recommender systems requires conducting user experiments. This chapter is a guideline for students and researchers aspiring to conduct user experiments with their recommender systems. It first cov- ers the theory of user-centric evaluation of recommend
Personalized Location Recommendation on Location-based Social Networks Huiji Gao, Jiliang Tang, and Huan Liu Arizona State University Tutorial Abstract Personalized location recommendation is a special topic of recommendation. It is related to human mobile behavior in the real world regarding various contexts including spatial, temporal, social, and content. The development of this topic is subjec
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