Recommender systems have already been successfully used in e-commerce industry and have been influencing our daily lives. We may all have got (personalized) recommendation of news, music, movies, videos, books, restaurants, hotels, etc. This talk will introduce the recent research in my group about promoting personalized recommendation by learning representations for users/objects to recommend. Examples of applications will be given for recommendation of the next movie to watch, the interesting research papers to read, the useful datasets to explore, and interesting places to visit. Also, important issues like fairness and user privacy in recommendation will be discussed.
Dr. Xiangliang Zhang is an Associate Professor of Computer Science at KAUST, Saudi Arabia. She earned her Ph.D. degree in computer science from INRIA-Universite Paris-Sud, France, in 2010. Zhang and the MINE group she leads focus on learning from complex and large-scale streaming data, social graph mining and recommendation systems.