Collaborative Filtering

In Video 12e, Hinton shows how RBMs can be used for collaborative filtering, as in the Netflix competition, where each user has rated only a small fraction of the movies.

For what other tasks might collaborative filtering be helpful?

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1 Response to “Collaborative Filtering”


  1. 1 Nicholas LĂ©onard March 21, 2013 at 13:49

    Collaborative filtering is an approach to Recommendation Systems, the other being the Content-based approach, and the any combination of both being a Hybrid approach. Collaborative filtering can be used in image search to recommend images give a query, where the data set used to generate such a model could be click-through data. It can be used to recommend documents given a query or a document or a user profile. It also has medical applications for recommending course of actions. Finally, it can also be applied to match-making in online dating sites, or in online games, for example to recommend combinations of users to create teams or competitions.


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