PATRICK BAUDISCH

Many people today live in information-rich worlds, constantly facing the question: what should I do next? Which papers should I read to learn about a new area I'm interested in? Which movie should I go to? Which restaurant would I like? The experience of friends and colleagues is a valuable resource for making such decisions, especially friends who are familiar with the subject area and have similar tastes... The field of recommender systems (or collaborative filtering) attempts to automate this process, e.g., by supporting people in making recommendations, finding a set of people who are likely to provide good recommendations for a given person, or deriving recommendations from implicit behavior such as browsing activity, buying patterns, and time on task... When are recommender systems appropriate? For which domains, which types of decisions, and which communities of users?