About the second question,I have not the similarity,I want to know is how to pre-compute the item similarity.
On Mon, Jul 5, 2010 at 11:20 PM, Sean Owen <[email protected]> wrote: > 1) Good question. One answer is to make these "anonymous" users real > users in your data model, at least temporarily. That is, they need not > be anonymous to the recommender, even if they're not yet a registered > user as far as your site is concerned. > > There's a class called PlusAnonymousUserDataModel that helps you do > this. It wraps a DataModel and lets you quickly add a temporary user, > recommend, then un-add that user. It may be the easiest thing to try. > > (BTW the book Mahout in Action covers this in section 5.4, in the > current MEAP draft.) > > 2) Not sure I fully understand. You already have some external, > pre-computed notion of item similarity? then just feed that in to > GenericItemSimilarity and use it from there. > > Sean > > On Mon, Jul 5, 2010 at 1:52 PM, samsam <[email protected]> wrote: > > Hello,all > > I want to build recommendation engine with apache mahout,I have read some > > reading material,and I still have some questions. > > > > 1)How to recommend for anonymous users > > I think recommendation engine should return recommendations given a item > > id.For example,a anonymous user reviews some items, > > and tell the recommendation what he reviews,and compute with the reviews > > histories. > > > > 2)How to compute the items similarity dataset > > Without use items similarity dataset,we can make ItemBasedRecommender > > with PearsonCorrelationSimilarity,but > > we need to make recommendations with extra attributes of items, > > so we should use the items similarity dataset,how to build the dataset is > > the key point. > > -- > > I'm samsam. > > > -- I'm samsam.
