Hi guys,

I want to implement a media recommendation engine. I saw a similar posts on this, but I think my requirements are bit different from those, so posting here.

Here is the deal.

I want to implement a recommendation engine for media players like VLC, which would be an engine that has to care for only single user. Like, it would be embedded in a media player on a PC which is typically used by single user. And it will start learning the likes and dislikes of the user and gradually learns what a user likes. Here it will not be able to find similar users for using their data for recommendation as its a single user system. So how to go about this?

Or you can consider it as a recommendation engine that has to be put in say iPods, which has to learn about a single user and recommend music/Movies from the collections it has.

I thought of start collecting the genre of music/movies (maybe even artist name) that user watches and recommend movies from the most watched Genre, but it look very crude, isn't it?

So is there any algorithms I can use or any resources I can refer up to?

Regards,

MicroKernel :)