Hi, I am building an Item Based Recommender System for 10 million users who rate categories over 20 possible categories (new categories like politic, sport etc...) I would like for each one of them to be recommended at least another category which they don't know (no rating).
I runned a GenericUserBasedRecommender and asked for recommendations for each user but It looks extremely long: maybe 1000 user proceeded per minute. My questions are: Can I run this same GenericUserBasedRecommender on hadoop and would it really befaster? I saw and run an ItemBasedRecommender with command line on a cluster, but I would prefer run a User Based one. Is there another smarter way to deal with my problem? Maybe some clustering solution instead of recommendation? I don't exactly see how. Finally, am I right when I say that the algorithms who have no command line are not to use with hadoop? Thank you for your answers, xenlee -
