I have used the SGD classifiers for content based recommendation. It works out reasonably but the interaction variables can get kind of expensive.
Doing it again, I think I would use latent factor log linear models to do the interaction features. See http://cseweb.ucsd.edu/~akmenon/LFL-ICDM10.pdf We have a half done implementation in Mahout. There was a student at UCSD looking into completing it, but we don't have real results yet. On Wed, Jun 22, 2011 at 12:34 AM, Marko Ciric <[email protected]> wrote: > Hi guys, > > When trying to do a content-based recommender, there could be two > approaches > with Apache Mahout: > > - Having a custom implemented Taste ItemSimilarity that is calculated > with item features. > - Classifying a data set with Mahout by representing items with vectors. > > Has anybody had the experience with comparing performance/accuracy of > those? > > Thanks > > -- > Marko Ćirić > [email protected] >
