No. Not entirely surprising, but it is *really* nice to get some public results on this.
The treatment of the negatives as a separate cross term instead of just lumping them together is a very significant difference. On Tue, Nov 3, 2015 at 3:42 PM, Peter Jaumann <peter.jauma...@gmail.com> wrote: > Fascinating!!! Not too surprising really!!! > On Nov 3, 2015 6:31 PM, "Suneel Marthi" <smar...@apache.org> wrote: > >> Thanks Pat, very interesting indeed. >> >> On Tue, Nov 3, 2015 at 6:20 PM, Pat Ferrel <p...@occamsmachete.com> wrote: >> >> > A colleague of mine just build a MAP@k precision evaluator for the >> Mahout >> > based cooccurrence recommender we’ve been working on and we ran some >> data >> > scraped from rottentomatoes.com <http://rottentomatoes.com/> They have >> > “fresh” and “rotten” reviews tied to reviewer ids. >> > >> > A fair bit of discussion has gone on about how to use negative >> > preferences. We have been saying that negative preferences might be >> > predictive of positive preferences and the cross-cooccurrence code in >> the >> > new SimilarityAnalysis.cooccurrence method can make the data usable. >> > >> > We took the RT data for two “actions”: “fresh" as the primary, the best >> > indicator of preference, and “rotten” as the secondary indicator. We >> found >> > that MAP using only “fresh” was bettered by almost 20% when we included >> > “rotten” as the secondary cross-cooccorrence action. For the strict out >> > there we did not directly isolate the two actions, which is work >> remaining >> > so some of the lift might be due to just having more data but it’s a >> really >> > good first step because more data doesn't always translate to better >> > performance and anyway it’s data you wouldn’t have otherwise. >> > >> > This opens up a new way to compare all sorts of other user signals, some >> > long considered to be unusable by recommenders. Gender, location, >> category >> > preferences are now fair game for testing. >> > >> > BTW we used this recommender, which is based on Mahout Samsara’s matrix >> > math, cooccurrence and LLR. >> > https://github.com/pferrel/scala-parallel-universal-recommendation < >> > https://github.com/pferrel/scala-parallel-universal-recommendation> >> >
