The Universal Recommender uses Mahout Samsara so yes, of course. See the UR template for how to do this “wrapping”.
The core algorithm for Correlated Cross-Occurrence comes from this bit: http://mahout.apache.org/users/algorithms/recommender-overview.html <http://mahout.apache.org/users/algorithms/recommender-overview.html> BTW the backend support is spotty for everything but Spark. Some things are implemented and some not. On Jan 20, 2017, at 10:07 AM, Gustavo Frederico <[email protected]> wrote: Is it possible to create an engine using Mahout Samsara? I was looking at http://predictionio.incubator.apache.org/system/ <http://predictionio.incubator.apache.org/system/> and comparing with Samsara's features at http://mahout.apache.org/ <http://mahout.apache.org/> . I can see that Samsara runs on distributed Spark, H2O, and Flink. I can see that Spark is a binding for Samsara ( http://mahout.apache.org/users/sparkbindings/home.html <http://mahout.apache.org/users/sparkbindings/home.html> ). I'm not very familiar with the terminology, but would it be a matter of 'wrapping' the Samsara algorithm in some class that implements the interfaces described in the DASE page ( http://predictionio.incubator.apache.org/customize/dase/ <http://predictionio.incubator.apache.org/customize/dase/> ) ? Thanks Gustavo Frederico
