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Topics of interest for RecSys 2019 include but are not limited to (alphabetically ordered *Algorithm scalability, performance, and implementations *Bias, bubbles and ethics of recommender systems *Case studies of real-world implementations *Context-aware recommender systems *Conversational recommender systems *Cross-domain recommendation *Economic models and consequences of recommender systems *Evaluation metrics and studies *Explanations and evidence *Innovative/New applications *Interfaces for recommender systems *Novel machine learning approaches to recommendation algorithms (deep learning, reinforcement learning, etc.) *Preference elicitation *Privacy and Security *Social recommenders *User modelling *Voice, VR, and other novel interaction paradigms
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