collaborative filtering

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collaborative filtering

Also known as "social filtering" and "social information filtering," it refers to techniques that identify information people might be interested in. Collaborative filtering is used to create "recommendation systems" that can enhance the experience on a website; for example, by suggesting music or movies.

Different algorithms are used, but the basic principle is to develop a rating system for matching incoming material. "Collaborative" means that a group of people interested in the subject define their preferences when setting up the system. See collaborative software and music recommendation service.
References in periodicals archive ?
Greiner, "A mixture imputation-boosted collaborative filter," in Proceedings of the 21th International Florida Artificial Intelligence Research Society Conference (FLAIRS'08), 2008, pp.
Sartin, "Combining content-based and collaborative filters in an online newspaper," in In Proceedings of ACM SIGIR Workshop on Recommender Systems.
We started Digg in 2004 based on the concept of using a collaborative filter of a larger community to prioritize the overwhelming amount of material online," said Kevin Rose, founder and chief architect of Digg.
Digg harnesses the collaborative filter of the world's Internet audience to prioritize the overwhelming amount of content available on the Web.
8--Ways to combine content-based and collaborative filters in an online newspaper

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