The similarity computation as it is currently implemented is not described in Mahout in Action.
We wrote a paper about the current approach which was published at this years RecSys conference: http://ssc.io/wp-content/uploads/2012/06/rec11-schelter.pdf If the preferences are boolean, you simply have to use a similarity measure that can handle such data, e.g. jaccard/tanimoto or loglikelihood ratio. --sebastian On 26.09.2012 16:10, William Quinones wrote: > Hello, I am currently writing my Bachelor thesis and am using Mahout for a > recommendation system. I bought the book Mahout in Action and understand > how the similarity matrix works for the distributed RecommenderJob. > However, this explanation only shows how it works when the user has > expressed some preferences towards the items. I would like to know how this > works when there are no preferences (booleanData true). Are all preference > values somehow inferred? Or treated as 1? I would also like to know what > role the similarity metrics play in these Map/Reduce implementation. > > Thank you very much in advance, > William >
