Collaborative filtering: Difference between revisions
Jump to navigation
Jump to search
imported>Yash Prabhu m (Italic) |
imported>Yash Prabhu m (CF) |
||
Line 14: | Line 14: | ||
== Collaborative Filtering Techniques == | == Collaborative Filtering Techniques == | ||
====Memory-based(Heuristic) Recommendation Technique==== | |||
====Model-based Recommendation Technique==== | |||
====Hybrid Recommendation Technique=== | |||
Revision as of 14:25, 8 August 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! |
Definition
A Collaborative Filtering(CF) refers to the use of software algorithms for narrowing down a large set of choices by using collaboration among multiple agents, viewpoints, and data sources.
Overview
The term Collaborative Filtering was first coined by the makers of one of the first recommendation systems, Tapestry. The basic assumption in CF is that user A and user B's personal tastes are co-related if both users rate n items similarly.