If by #3 you mean you have preferences for many users, this is of course the standard input for a recommender, yes. If you also have some user-user similarity info beyond that, you can implement UserSimliarity and use GenericUserBasedRecommender to incorporate that.
If you want to boost items according to some logic, like time (#2), use IDRescorer. It sounds like you have a priori understanding of what items are best for what users (#1). That's not something you can use directly, but I suppose you could simply use this info as a multiplier (again with IDRescorer), or perhaps the basis of a separate set of recommendations you blend. What's a time-based recommender? On Sat, Mar 10, 2012 at 2:51 PM, Alex Geller <[email protected]> wrote: > Hi, > > I want to write a recommendation system which recommends items to customers > based on the following parameters (and some others): > > - User-item similarity (for example recommend items which target certain > gender,age etc. to users which meet these criteria) > - Time of year (recommend items with a holiday theme before a major > holiday) > - Preferences of similar users > > I know Mahout supports User-User and Item-Item similarity, but how can I > implement User-Item similarity? > Also, is there any support for time-based recommendations? > > > Thanks, > > Alex
