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?
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.
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.
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.