Recommender Systems
Research
Since 1992 I have been working on recommender systems, which I
believe have the potential to change the way people interact with
all types of information, including newspapers, music, books, and
Web sites. I co-founded the GroupLens Research group with Paul Resnick
in 1992. In 1995 I invited Joe Konstan to join the group as co-director
because his expertise in user interfaces opened tremendous opportunities.
In 2002 Joe and I invited Loren Terveen, an expert in diverse types
of recommender systems, to join our team. The group has been active
in research on all aspects of recommender systems, including algorithms,
interfaces, and social effects.
Joe Konstan and I co-authored Word
of Mouse, a book on the business applications of recommender
systems, and hold several patents on various aspects of recommender
systems.
- Algorithms: We have studied many aspects
of recommender algorithms, including the orginal collaborative
filtering algorithms mentioned under applications below, a careful
study of the parameters that affect collaborative filtering algorithms,
and a new item-based recommender algorithm. Nearly all of our
user interface and applications research involves developing novel
algorithms and testing their effectiveness. We have also studied
the effects of agents in algorithms. Agents complement recommender
systems by providing a tireless source of rapid and reliable opinions.
Recommender systems complement agents by choosing the agents that
are the best recommender for each user.
- User Interfaces: We have studied many
aspects of the user interface effects of recommenders, including
experiments on user preferences for different types of explanations
of the recommendations , experiments on the best ways for recommender
systems to get to know new users, and experiments on the effect
on the user experience of having the recommender manipulate the
predictions maliciously.
- Applications: our application research
typically requires new algorithms, new
interfaces, and research on what happens when users use the new
algorithms and interfaces in practice.
On to e-commerce research
|