I see it makes more sense with geometric mean. And with weight, if I want to apply say 70% for Sim1 and 30% for Sim2, would it also make sense to have it like this? The result should be around 0.194.
* Agata Filiana Erasmus Mundus DMKM Student 2011-2013 <http://www.em-dmkm.eu/> * On 17 April 2013 17:00, Sean Owen <sro...@gmail.com> wrote: > If all of your similarities are a product like this, then they're all > "low". In a relative sense this is fine. > But this is also why I proposed a geometric mean instead. For example > the geometric mean of these is about 0.424 and this notion can be > extended to include weights as well, which is what may make it > particularly interesting to you since you mentioned weighting. > > On Wed, Apr 17, 2013 at 3:56 PM, Agata Filiana <a.filian...@gmail.com> > wrote: > > Just a thought, when you say to combine the metrics by multiplying their, > > for example Sim1 = 0.9 and Sim2 = 0.2 > > When they are multiplied it would give a result of 0.18 which is very > low, > > remembering that they are pretty "similar" based on Sim1 - how can this > > problem be tackled? > > > > * > > > > Agata Filiana > > Erasmus Mundus DMKM Student 2011-2013 <http://www.em-dmkm.eu/> > > * > > > > > > On 16 April 2013 16:41, Agata Filiana <a.filian...@gmail.com> wrote: > > > >> Thanks a lot for the insight,very useful! > >> > >> > >> * > >> > >> Agata Filiana > >> Erasmus Mundus DMKM Student 2011-2013 <http://www.em-dmkm.eu/> > >> * > >> > >> > >> On 16 April 2013 16:40, Sean Owen <sro...@gmail.com> wrote: > >> > >>> Of course it's not meaningless. They provide a basis for ranking > >>> items, so you can return top-K recommendations. > >>> If it's normally based on similarity and ratings -- and you have no > >>> ratings -- similarity is of course the only thing you can base the > >>> result on. > >>> > >>> On Tue, Apr 16, 2013 at 3:36 PM, Agata Filiana <a.filian...@gmail.com> > >>> wrote: > >>> > Well right now, I am only using one boolean file -just from from this > >>> > history of reading. > >>> > So you are saying the values generated in > >>> > the GenericBooleanPrefUserBasedRecommender is actually useless in > this > >>> case > >>> > of no ratings and that it is merely based on the similarity only? > >>> > >> > >> >
