Hi, I learned in this site below how to use ALS facorization algoritm to made recommendations in Mahout Framework.
https://mahout.apache.org/users/recommender/intro-als-hadoop.html >From this: - we inform a file with the rating (user, item, rating), in my case I have implicit ratings; - then get the files of the two latent matrices generated; and - finally we insert theses files in a recommender engine that generate a file with the list of recomendations for each user. I think that it is made for big e-commerce companies periodically. (the model and recomendations is built periodically in an offline moments) At my case, I'm going to do an online experiment of recommender. This model recommender will be the control group. I have a file with ratings of a set of old users and I will have a set of new users on this online experiment. The old users will not participate this experiment. Theses new users will use the recommener system for 2 weeks in the online experiment. >> How to use ALSWRFactorizer recommender (non-hadoop) from Mahout in online experiments ? I'd like to build a model once and use it to the new users... >> Will I have to run the algoritm (re-buid the model) in each recomendation made during the online experiment ? Thanks and Regards, Alessandro Dias
