No you can’t, the value is ignored. The algorithm looks at occurrences, cooccurrences, and cross-occurrences of several event types not values attached to events.
If you are trying to use rating info, this has been pretty much discarded as being not very useful. For instance you may like comedy movies but they always get lower ratings than drama (raters bias) so using ratings to recommend items is highly problematic, but if a user watched a movie, that is a good indicator that they liked it and that is a boolean value. With cross-occurrence you can also use dislike as an indicator of preference but this is also boolean—a thumbs down. To see an end-to-end recommender with all the necessary surrounding infrastructure check the Apache-PredictionIO project and the Universal Recommender, which uses the code behind spark-itemsimilarity to serve recommendations. Read about the UR here: http://actionml.com/docs/ur <http://actionml.com/docs/ur> On Nov 30, 2016, at 6:58 AM, Niklas Ekvall <niklas.ekv...@gmail.com> wrote: I found that you can, so ignore my question! Best reagrds, Niklas 2016-11-30 15:42 GMT+01:00 Niklas Ekvall <niklas.ekv...@gmail.com>: > Hello! > > I'm using *spark-itemsimilarity *to produce related recommendations and > the input data has the form *userID, itemID. *Could I also use the from > *userID, > itemID, value* (value > 0)? Or does *spark-itemsimilarity* only handles > binary values? > > Best regards, Niklas >
