Papers from the AAAI Workshop
Henry Kautz, Chair
Over the past few years a new kind of application, the "recommender system," has appeared, based on a synthesis of ideas from artificial intelligence, human-computer interaction, sociology, information retrieval, and the technology of the WWW. Recommender systems assist and augment the natural process of relying on friends, colleagues, publications, and other sources to make the choices that arise in everyday life. Examples of the kinds of questions that could be answered by a recommender system include: What kind of car should I buy? What web-pages would I find most interesting? What people in my company would be best assigned to a particular project team?
Some of the issues we explored in this workshop include identifying different types of recommendations: Techniques for generating recommendations and learning user profiles, personalized versus non-personalized recommendations; when does social filtering work, and when does it fail? Can we trust the recommendations received from remote, anonymous users to be trustworthy and representative? What happens when recommender systems meet the "real world" -- how do you get a business model and a user base? What is the current state of the art? Social implications of recommendation systems, and how the technology relates to traditional publishers and editors; and visualizing recommendation spaces.