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 15 minutes of discussion. At the beginning of the semester each student should present his/her topic in a 5-minutes short talk. At the end of the semester, each student has to hand in a written summary report (5 pages; two column style) of his/her topic. Active participation in all discussions is mandatory.
This seminar is limited to 6 participants. If more apply we will pick randomly.
The grade will consist of
- 30% Presentation
- 30% Active Participation
- 40% Summary Report
The seminar Usually takes place Mondays at 13:30 in A-2.2.