Which methods are you referring to specifically? Are they available in Mahout? if not then perhaps we can think about including them.
-----Original Message----- From: Ted Dunning [mailto:[email protected]] Sent: Tuesday, January 20, 2009 12:19 PM To: [email protected] Subject: Re: RE: RE: [jira] Commented: (MAHOUT-19) Hierarchial clusterer Item based recommenders can be very effective even with very large numbers of items, especially if the distribution of usage is a long-tailed one so that you get significant amounts of co-occurrence. Utlimately, the sparsity will hurt you, however. Then you have to move to a latent variable formulation. That provides smoothing so that you can reason from one item to another even without any explicit co-occurrence. LSI was a very fashionable choice for this at one time, but there are much better methods available now. On Mon, Jan 19, 2009 at 5:31 AM, Sean Owen <[email protected]> wrote: > > Do you have relatively lots of users, or lots of items? If you have > relatively few items, and item-based recommender is ideal -- and vice > versa with user-based recommenders. -- Ted Dunning, CTO DeepDyve 4600 Bohannon Drive, Suite 220 Menlo Park, CA 94025 www.deepdyve.com 650-324-0110, ext. 738 858-414-0013 (m)
