You should try:
- the implicit preference
ParallelALSFactorizationJob
(hadoop based) - Or the implicit preference
ALSWRFactorizer
alongside anSVDRecommender
(not hadoop based) (I think the this non-hadoop implicit preference variant is only available in mahout-0.8),
In these the number you assign to a user preference for an item is an indication of how strong that association is, and not a rating, so they are all positive associations, just with different strengths. This way you can model your different interactions, such as view, edit, click, etc. Although the strength assigned to each will vary according to your particular business.
This presentation (link) should give you a rough idea of what is happening. Also this paper (link) describes the implicit feedback variant of the factorizers (they are the same, one is just meant to scale with hadoop)