Do you do any calculus on the relative values of false positives and false negatives? It seems that a person with a large number of feeds would put a greater importance on limiting the number of false positives (non-interesting messages classified as interesting by your program), whereas a person with a small number of feeds would be more worried about false negatives (interesting stories classified as uninteresting).

Also, see this comment in this thread: http://news.ycombinator.com/item?id=435837 . For something like this, I doubt a machine learning algorithm will work as well as social algorithms. Web search is a very similar problem (find the most interesting link given input from the user) and social algorithms won out. Of course, the kind and quality of input that you are getting from the user is different. However, your problem is much less well-defined (finding interesting things in general instead of interesting things related to a particular topic).