Group items tagged

ecommendations are based on the quality of items, rather than more objective properties of the items themselves

The basic idea is: The system maintains a user profile, a record of the user's interests (positive as well as negative) in specific items. It compares this profile to the profiles of other users, and weighs each profile for its degree of similarity with the user's profile. The metric used to determine similarity can vary. Finally, it considers a set of the most similar profiles, and uses information contained in them to recommend (or advise against) items to the user.

One observation is that a social information filtering system becomes more competent as the number of users in the system increases.

The system may need to reach a certain {\em critical mass} of collected data before it becomes useful.

Finally, we haven't even begun to explore the very interesting and controversial social and economical implications of social information filtering systems like Ringo.

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