Some features are numeric (like LCD size screen, resolution, optical zoom) and others are categorical (like camera type, image sensor type). I’m working from data that I’ve scrapped from epinions.com (academic purposes) but I haven’t normalized yet. Now for the ItemSimilarity implementation, maybe I would use rochio algorithm but I’m not sure because I need to understand it better or understand others algorithms.
Is good to know that mahout can be useful for this problem, thanks for your reply. 2012/5/12 Sean Owen <[email protected]> > You can write your own ItemSimilarity metric based on the features and > then use an item-based recommender. That piece you'd have to do > yourself by making up some notion of similarity; if the features were > all numeric and normalized you can look at repurposing something based > on Euclidean distance or cosine similarity or something, but I don't > know if those are the features you have. > > Sean > > On Sat, May 12, 2012 at 2:15 AM, EDUARDO ANTONIO BUITRAGO ZAPATA > <[email protected]> wrote: > > Hi All, > > > > As far I've seen, all mahout recommenders uses this setting for input > file: > > > > User1, item1, rating1 > > User1, item2, rating2 > > ... > > User2, item1, rating3 > > > > What I need to do is a recommender for new digital cameras. I want to > know > > which user is more interested in a camera when it arrives, then I can > make > > recommendation. To do that, I want to take into account the camera > > features (optical zoom, LCD size, etc). ¿Is there a way to implement > this > > in mahout? Maybe the input file is something like this: > > > > User1, item1, feat1, feat2, … , featn, rating1 > > User1, item2, feat1, feat2, … , featN, rating2 > > ... > > User1, itemN, feat1, feat2, … , featN, rating3 > > User1, newItem, feat1, feat2, … , featn, ? > > > > Any help would be appreciated. > > > > -- > > Eduardo** <[email protected]> > -- EDUARDO BUITRAGO Est. Msc. en Ingeniería - Sistemas y Computación - Universidad de los Andes Ing. de Sistemas - Universidad Francisco de Paula Santander Cisco Certified Network Associate - CCNA
