On Sun, Aug 29, 2010 at 7:19 PM, Akshay Bhat <[email protected]> wrote:
> Item based recommender can be cached, so if you are recommending similar > items based current item being looked at/purchased, it would just be a > database lookup. > For an SVD based recommender to compute similar items for 1M items with 50 > ~ 100 eigenvectors should take ~5-6 hours on similar machine. > Please note that this is the time required to find similar items, after SVD has been performed. time for SVD would depend on number of users. > You can generate a new model every few days and update database of similar > items. > > > 2010/8/29 Young <[email protected]> > >> Hi all, >> >> >> Based on 1M dataset, about how many requests could be expected to be >> handled at a time when using item-based recommender if the engine runs on a >> Core2 2.4G CPU and 4G meomory. >> >> Thank you very much. >> >> -- Young >> >> >> > > > > -- > Akshay Uday Bhat. > Graduate Student, Computer Science, Cornell University > Website: http://www.akshaybhat.com > > -- Akshay Uday Bhat. Graduate Student, Computer Science, Cornell University Website: http://www.akshaybhat.com
