Interacting with recommender systems
P Baudisch, L Terveen - CHI'99 Extended Abstracts on Human Factors …, 1999 - dl.acm.org
CHI'99 Extended Abstracts on Human Factors in Computing Systems, 1999•dl.acm.org
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 am 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, eg, by supporting people in making …
should I do next? Which papers should I read to learn about a new area I am 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, eg, by supporting people in making …
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 am 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.
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