Couple clarifications - The CF components are oriented to on-line, real-time use, though of course one can trivially build a batch job out of that. That is what I did with the EC2 image that cranks out recommendations for all users.
The CF component is also already parallelized as much as is practical. There are already Hadoop jobs for parallel, batch operation. Finally if you have some external notion of item similarity, like text similarity between articles, you can and should include this info by creating an ItemSimilarity with this knowledge. In that case you want to use an item-based recommender, since it is only in such a case that item-based recommenders have a distinct advantage. On Apr 1, 2009 10:32 AM, "Otis Gospodnetic" <[email protected]> wrote: it's the former. Taste is still not parallelized, but other parts of Mahout are, and they make use of Hadoop. Otis -- Sematext -- http://sematext.com/ -- Lucene - Solr - Nutch ----- Original Message ---- > From: Vinicius Carvalho < [email protected]> > To: mahout-... > On Tue, Mar 31, 2009 at 1:32 PM, Tim Bass wrote: > > > Most prior-work in news related classifica... > > On Tue, Mar 31, 2009 at 10:39 PM, Jason Rennie wrote: > > > Sorry for my misunderstanding. Than... > > >wrote: > > > > > >> > > >> On Mar 31, 2009, at 9:47 AM, Jason Rennie wrote: > > >> > > >> > > >...
