For a limited experience such as the new user or new items, you can build traditional user segment based models using logistic regression or other modeling techniques.
This winds up being a patchwork sort of thing. On Tue, Apr 20, 2010 at 1:09 AM, Sebastian Schelter < sebastian.schel...@zalando.de> wrote: > Some details on approaches to including items with no interactions (like > brand new products) in your recommender system can be found in this paper > "Feature Based Recommendation System" > ( > http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.99.4058&rep=rep1&type=pdf > ). > > I'm currently doing some research on this and find the ideas quite > appealing but have not yet found a good way to implement this. It's > basically stating what was already said here: use the attributes > (features) of new items to find similar items for which you can make > predicitions. > > Regards, > Sebastian > > >
