I don't want to have the recent items in the data model. My data model is based on more historical data, and for the recent items I just guess a preference value. I have already tried to use an IDRescorer, but this its computation takes way too long since it is computed for every item. For me it seems reasonable, to use my standard recommender besides the anonymous user recommender for recent items and combine their results. Or are there any better ideas?
2010/10/30 Sean Owen <[email protected]>: > Recent item associations aren't any different than others -- if you want to > use them as data, they need to go in the DataModel. And then recommendations > need to be re-computed to take them into account. That's the simplistic > answer. > > In practice this can be inefficient for some algorithms. Slope one is good > at incorporating new information like this; others aren't as efficient. > > This is actually an area of personal interest for me. It's ideal to be able > to regularly re-compute recommendations based on all data, but, between > those large recomputations, "adjust" them imperfectly to incorporate very > new information. I'm in the process of creating a framework for just this. > It is not trivial. > > 2010/10/30 Matthias Böhmer <[email protected]> > >> Hello, >> >> I played around a little bit with recommendations for anonymous users. >> Therefore I have simply build a preference array based on the recently >> visited items, like it is explained in "Mahout in Action". This seems >> to work out pretty well since the recent items perfectly relate the >> user's latest interests. However, now I want to include the most >> recent visited items into my main recommender, i.e. the recommender >> based on the historical data of known users. Any ideas on how to add >> temporary user preferences to the data model? As far as I understood >> the PlusAnonymousDataModel, this is no solution since it only supports >> one user and is not thread safe. Thanks in advance! >> >> Best, >> Matthias >> >
