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. >
