This project is a joint cooperation with ECHO, Sophia-Antipolis, France.
Collaborative Filtering is a technique by which the interest of
a user for an object is predicted from the knowledge of the interest of
other users for this object. It is a basic technique to build Recommender
Systems on the Internet, where people can advise other on good and
One major problem of Collaborative Filtering is that
a large database of user's advices is needed for a reliable prediction.
We are investigating techniques to make a robust prediction even
in cases where little data is available. This is of great help
in the initial phase where a system is setup, and when a new
user joins the system.
As an illustrative example we are building a Active WebMuseum,
a personalized navigation within a collection of painting,
where the system can advise you for painting that you are likely
to appreciate, based on the ratings from previous visitors.
- Arnd Kohrs
and Bernard Merialdo.
Clustering for collaborative filtering applications.
In Proceedings of CIMCA'99. IOS Press, 1999.