[AmberShah]

My startup faces a variant of this problem. Not exactly a recommender system, but it will get more accurate as time goes on. I am compensating by putting an initial value that is a guess, and then it will adjust as time goes on. Sort of messy but necessary.

It sounds like you're saying that in your case, the value will be different for each person, so you don't have a way of seeding it correctly for different people. I sort of think you have to have SOME info to go off of. Sort of like hunch asks you questions, maybe you could do something like that?

[apurva]

well so here is what I am doing instead... I get only a notion of the likes of the user, and since "everything else" is too huge a domain to consider as dislike, I try and rank the user's like concepts and pick the lower one's as the one's they like lesser. This only for initialization, and then I leave the filter to tune itself through feedback. I know it's not the best approach in the world, but let me see how this shapes up. Thanks of course, and any other ideas still welcome!