Recommender systems have become very popular in recent years. Many applications include recommender algorithms in one way or another. An early example of industrial application of recommender systems is recommending books by Amazon. Other application areas include movies, music, news, web queries, tags, and products in general. Independent of the application domain, various approaches have been developed to improve recommendations. Further, explanations of recommendations and evaluating recommender systems are active research fields, together with psychological and economical implications, as well as privacy concerns.
In the first half, we will look (in theory and practice) at different aspects of recommender systems and fundamental algorithms of the field.
In the second half, students will pick a research paper from the 2018 ACM Conference on Recommender Systems and present the findings in the seminar.
This seminar is limited to 6 participants. If more apply, we will pick randomly.
The seminar takes place on Mondays at 11:00 on Campus II in Room F-2.11