Recommendation system: Difference between revisions
imported>Yash Prabhu (Reference to "Next gen" paper 2005) |
imported>Yash Prabhu |
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== References == | == References == | ||
[http://www.computer.org/portal/web/csdl/doi/10.1109/TKDE.2005.99 Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions] | 1. [http://www.computer.org/portal/web/csdl/doi/10.1109/TKDE.2005.99 Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions] |
Revision as of 19:56, 25 July 2010
To provide students with experience in collaboration, you are warmly invited to join in here, or to leave comments on the discussion page. The anticipated date of course completion is 13 August 2010. One month after that date at the latest, this notice shall be removed. Besides, many other Citizendium articles welcome your collaboration! |
A recommendation system is a software program which attempts to narrow down selections for users based on their expressed preferences, past behavior, or other data which can be mined about the user or other users with similar interests.
History
Classification
The current generation of recommendation methods can be broadly classifed into the following three categories, based on how recommendations are made:
1. Content-based recommendations.
2. Collaborative recommendations.
3. Hybrid recommendations.
Content-based recommendation
In Content-based recommendation, the user receives recommendations based on his past preferences.
Collaborative RS
Collaborative recommendation systems recommend items that people with similar taste preferred in the past.
Hybrid RS
Hybrid systems use a combined content-based and collaborative approach.