Sure. I would suggest you create an ItemSimilarity implementation which loads this additional information, and constructs some formula for similarity based on whether movies share genre, actors, etc. For example maybe being in the same genre is worth +0.1 similarity. Maybe same actor is worth +0.2.
(Of course you could do as much work as you like to construct an even smarter function.) Then you simply use this with your existing DataModel and a GenericItemBasedSimilarity. That's the most direct way to incorporate this info. On Fri, Oct 1, 2010 at 12:14 AM, web service <[email protected]> wrote: > I have got the group lens example working. Had a couple of doubts though - > The dataset in grouplens has movieid, userid and the corresponding ratings. > However a rating is meant to rate a movie but there are other things > related > to a movie to which the rating contributes. > For example, the actors, directors, movie genre or may be the year of > release etc. > > So, is there any way to capture this relationship and then generate > recommendation. > > Any suggestions, ideas about how to represent data or vector and then > compute recommendations or how it is done usually etc. would be nice. > > -Mac >
