Utilizing multiple, boolean pref data models in a single recommender

[ro...@barclays.com]

I'd like to expand on this question and answer:

http://stackoverflow.com/questions/15707013/utilizing-multiple-weighed-data-models-for-a-mahout-recommender

Besides ParallelALSFactorizationJob and Myrrix, are there any other ways in which you can feed multiple boolean pref data models into a recommender? Is there any way to weight each model? As I understand it, both of these are implementations of ALS-WR, but I'm wondering if there are any other implementations, algorithms, or even tricks using the existing stack of Mahout components that could get me close to what I'm after.

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