Courses in winter term 2006/7 / Seminar on Recommender Systems and Personalization:

Time:	Tuesday 16:00-18:00
Location:	J 204
Begin:	31.10.2006

Recommender Systems are an intelligent access technology to large information systems as online catalogs in e-commerce or digital libraries and have been identified as one of the key technologies for e-commcerce. Recommender systems try to recommend users items that are of specific interest for them, based on user profiles of an online community build from explicit ratings of products or implicit usage information. Recommender systems may be as simple and ubiquitous as Amazons "who bought this, also bought that" crosslinks, and they may be rather complex knowledge and data driven systems aiming at modelling human counselors. Thus, recommender systems are the probably most advanced technology for personalization, drawing input from disciplines as heterogenous as e-commerce, online information systems, dynamic web technologies, data mining, information retrieval, articifical intelligence, user modelling, and human computer interaction.

The seminar gives a broad overview of different technologies and methods used for modeling, building, and deploying recommender systems.

Talks can be given in English or German.

Topics (M = methodological, T = technological focus):

0. -- Introduction --
1. (T) Recommeder System Introduction and Application.
2. (M) Collaborative Filtering.
3. (M) Content-based filtering and Hybrid filtering Models.
4. (M) Semantic web Personalization.
5. (M) Ontology Recommender Systems.
6. (M) Collaborative Tagging.
7. (M) Sentiment analysis in Recommender System.
8. (M) Time issues in Recommender Systems.
9. (T) Attack issues in Recommender System.
10. (T) Implicit Feedback.
11. (T) Interactive Recommender Systems.
12. (M) Trust-Aware RS.
13. (M) Multi-agent models.

For more information on the topics see readings. You can register for a topic by email from now.