Opportunity in this case does not refer to "Saw something and decided to buy/click/view/listen". Instead, it refers to the entire process including the UI and whatever discovery mechanisms exist.
You are correct that it is not just measuring the human component. On Mon, Aug 11, 2014 at 4:56 PM, Dmitriy Lyubimov <dlie...@gmail.com> wrote: > this logic does assume though that every user had an opportunity to eyeball > (A,B) pair and chose (vastly) not to buy them whereas it may have > overwhelmingly happened due to lack of exploration. thus, (not A & not B) > figures are probably grossly overestimated > > > On Mon, Aug 11, 2014 at 4:53 PM, Dmitriy Lyubimov <dlie...@gmail.com> > wrote: > > > No, the question was why total number of trials sent to LLR is considered > > to be m where M is m x n is a user/item matrix. > > > > ok i got it. i made some incorrect assumption about previous code steps, > > hence my inference derailed. > > > > > > > > > > On Mon, Aug 11, 2014 at 4:07 PM, Ted Dunning <ted.dunn...@gmail.com> > > wrote: > > > >> If you binarize the original occurrence matrix then it seems to me that > >> the > >> values in the cooccurrence matrix *are* user counts. > >> > >> Perhaps I misunderstand your original question. > >> > >> > >> > >> On Mon, Aug 11, 2014 at 3:44 PM, Dmitriy Lyubimov <dlie...@gmail.com> > >> wrote: > >> > >> > sorry rather total occurrences of a pair should be sum(a_i) + > sum(a_j) - > >> > a_ij (not 1norm of course) > >> > > >> > > >> > On Mon, Aug 11, 2014 at 3:11 PM, Dmitriy Lyubimov <dlie...@gmail.com> > >> > wrote: > >> > > >> > > Why coocurrence code takes number of users as total interactions? > >> > > shouldn't that be 1-norm of the co-occurrence matrix? > >> > > > >> > > > >> > > On Wed, Aug 6, 2014 at 4:21 PM, Dmitriy Lyubimov <dlie...@gmail.com > > > >> > > wrote: > >> > > > >> > >> So, compared to original paper [1], similarity is now hardcoded and > >> > >> always LLR? Do we have any plans to parameterize that further? Is > >> there > >> > any > >> > >> reason to parameterize it? > >> > >> > >> > >> > >> > >> Also, reading the paper, i am a bit wondering -- similarity and > >> distance > >> > >> are functions that usually are moving into different directions > (i.e. > >> > >> cosine similarity and angular distance) but in the paper distance > >> scores > >> > >> are also considered similarities? How's that? > >> > >> > >> > >> I suppose in that context LLR is considered a distance (higher > scores > >> > >> mean more `distant` items, co-occurring by chance only)? > >> > >> > >> > >> [1] http://ssc.io/wp-content/uploads/2012/06/rec11-schelter.pdf > >> > >> > >> > >> -d > >> > >> > >> > > > >> > > > >> > > >> > > > > >
