First, I think just based on your description you are indeed asking a lot of the user. For our service, we simply ask the user to vote up or down a piece of content and our dataset is pretty sparse. Users like to consume-they don't have any interest in helping you tune your algorithm.

With that said, now let's address the algorithm. You're using SVM? Is that quick enough? Are your recs computed offline? To be honest, you don't really need SVM or any complex technique to do recommendations well. You can get by just fine doing hand selected recs even though that might not scale well. To scale you can use something like Pearson correlation or naive Bayes and you'll do just fine.

With recs it's all about the quality of data and not so much the fancy algorithm.