Hi,
----- Original Message ---- > From: Sean Owen <[EMAIL PROTECTED]> > To: [email protected] > Sent: Thursday, October 23, 2008 5:37:38 AM > Subject: Re: Trimming Taste input (memory consumption) > > On Wed, Oct 22, 2008 at 5:52 PM, Otis Gospodnetic > wrote: > > So here are my questions: > > - Is there a point in keeping and loading very unpopular items (e.g. > > the ones read only once)? I think keeping those might help very few > > people discover very obscure items, so removing them will hurt this > > small subset of people a bit, but this will not affect the majority of > > people. Is this thinking correct? > > I agree, it makes sense to trim data in this way. I tried to build in > "levers" of this sort in several places in the code. If you mention > what implementation you are using I can recommend some parameters to > look at. I'm really using just this: DataModel model = new FileDataModel(new File("/tmp/input.txt")); recommender = new GenericItemBasedRecommender(model, new TanimotoCoefficientSimilarity(model)); recommender = new CachingRecommender(recommender) > > - I'm dealing with items where their freshness counts. I don't want to > recommend items older than N days - think news stories. Assume I have the > age > of each item. I could certainly then remove old items as I don't ever want > to > recommend them, but if I remove them, won't that hurt the quality of > recommendations, simply because I'll lose users' "item consumption history"? > > Yes they are still valuable data points even if they are not > recommendable items. You can use a Rescorer to exclude items from > recommendations according to any criteria you like. This is easier and > more efficient than filtering after the fact. Aha, Rescorer sounds useful. But say your rescoring logic requires additional data, such as item publishing date or item price or whatever. Where does such data enter the system? Does one then have to have custom Item implementation? And then that implies having a custom DataModel? Thanks, Otis
