Hi all, I'm using the GenericItemBasedRecommender (Mahout 0.5 Snapshot) in Tomcat 6 with PostgreSQL 9 as database backend and a C3PO connection pool (50 concurrent connections).
Since my items are ordered in a tree I'm using the Wu & Palmer correlation to calculate the item similarity. My dataset contains 17000 items, 279000 similarities and 5000 user preferences. My current problem is that it takes about 15 seconds to give one recommendation to a user. Based on your experience and the dataset size (which should grow a lot in the next few months) do you think this time is normal? I'd like to use the recommender in real time. Should I change it to precalculate the recommendations offline? Regards, Saúl Moncada -- Visita: http://www.kentriki.com.ve Compras - Vendes - Compartes
