What I need is actually just a hint where I can start.
I'm somewhat familiar to Mahout, at least theoretically. I know how it work, how to set it up, etc, and I could build a simple recommendation system based in collaborative filtering.
However, now I'm trying to do something more complex and even after reading quite some about different algorithms, I'm not sure which direction to go.
Quickly what I want to do is:
The final goal is to define one scalar (a "score") of each one of a set of entities based on some "known" entities. The entities interact with each other, known scores influence and define the unknown ones. You can imagine with the following example.
I have a lot if white clothes and a few pieces of colorful ones; red, blue, green... I put them into the washing machine. I want to know what colors the white ones will get after the wash.
Things to take into account:
You can see that while calculating, entities actually have 2 assigned scalars:
So, again, what I know:
What I want to know: - the hue of all clothes in the end of the washing
The problem is that I don't know what (type) of algorithm should I start with. If you were so kind to read so far, please suggest me something (or further reading).
Obviously I don't ask for any detailed thing, again, only hints.
Thank you!
The only thing I can think of that sounds like this problem is PageRank. It's computed by a sort of iterative simluation. Each page has some influence (color) which flows via its links (socks its washed with) and at some point the page influence reaches a steady state (final color). You can look up PageRank algorithms but it is essentially a matter of calculating eigenvectors of a big, erm, sock color matrix.