Recommender systems help users to navigate through web sites and to highlight items of interest that may not have been found otherwise. From an algorithmic point of view, recommender systems need to understand the content as well as the user. In practice, their performance is strongly connected to business strategies and to the overall revenue of the company. In this seminar, we will study classical and state-of-the-art recommender systems in terms of their applicability to prototypical scenarios. We'll address scalability issues and extensions including personalization. Applications include business, media, and social recommendation scenarios.
Access to course materials will be provided in the first seminar session.
Each student is expected to give a talk in class, answer questions, write a term paper, and show active participation in class.
The course management Moodle is used as the primary communication platform for the seminar and also contains any related material. The access key will be provided in the first seminar session.
For general advice on presenting your topic, please have a look at these guidelines.
Thursdays, 15.20 – 17.00, Room S115/021
First session: 18.10.2012
Prof. Dr. Ulf Brefeld