[apurva]

but the whole idea is... every one has their own notion of likes and dislikes.... am i missing something here?

[nostrademons]

That's why recommendation systems are hard. :-)

You could try to identify a population of users whose likes and dislikes are expected to be "similar" to the user in question, though, and then base your training set off them. I believe that's how actual recommendation engines (eg. Amazon, YouTube) work. Of course, then you have to figure out how to identify similar users, which is another hard problem.