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. We will look at different aspects of recommender systems and fundamental algorithms of the field.
In this seminar, each student will present one topic related to recommender systems in a 30-minutes talk followed by 10 minutes of discussion. Additionally, teams of 2 students will work on a self chosen practical recommender task and present the result at the end of the course informally.
This seminar is limited to 10 participants. If more apply we will pick randomly.
The grade will consist of:
- 40% Presentation
- 30% Active Participation
- 30% Practical Project
The seminar takes place on Wednesday at 11:00 on Campus III.