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A very basic test of a recommendation system is the following scenario:

You're a fan of a local band, listen to them a lot. This band is sampled, and actually praised, by a Korean rap artist. Suddenly thousands of Koreans are listening to it. Will the recommender system now recommend Korean rap to you?

Most recommender systems will.



I used to use rd.io, and had an annoying episode where I liked a Polish electronic musician. Suddenly I was assaulted by track after track of 70's Polish pop-music. It took a lot of effort to get it to stop playing them. The quality of a lot of recommendation systems is still surprisingly bad.


Requesting clarification. What do you mean is the desired outcome here? Should it or should it not recommend Korean rap?


It should not. That people liked this Korean rap artist implied that they might like your local band, but the opposite might not be true (in this example, it probably isn't).


I think it should recommend at least one Korean rap song. And hey maybe you like it and discover a whole knew genre of music. And if not nothing is lost.

I think most recommendation systems can cluster similar users together, and so avoid your problem. But I think very few recommendation systems do "exploration" instead of "exploitation". Ie just recommending whatever you are the most likely to like, and never trying new things.


Yeah, I agree recommender systems need exploration. But user-centered approaches have closely related symmetry problems.


So hypothetically speaking, gangnam style shouln't show up in an English speaking person's list?


The other direction. Fans of K-pop shouldn't start getting Taylor Swift recommendations when a K-pop single goes viral.

And people that like lots of viral songs should get Gangnam Style recommended.


Gangnam style became a hit because of the silly dance, not because of the music.




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