No, excepting approximate methods like LSH to figure out the relatively small set of candidates for the users in the partition, and broadcast or join those.
On Fri, Oct 31, 2014 at 5:45 AM, Nick Pentreath <nick.pentre...@gmail.com> wrote: > Sean, re my point earlier do you know a more efficient way to compute top k > for each user, other than to broadcast the item factors? > > (I guess one can use the new asymmetric lsh paper perhaps to assist) > > — > Sent from Mailbox > > > On Thu, Oct 30, 2014 at 11:24 PM, Sean Owen <so...@cloudera.com> wrote: >> >> MAP is effectively an average over all k from 1 to min(# >> recommendations, # items rated) Getting first recommendations right is >> more important than the last. >> >> On Thu, Oct 30, 2014 at 10:21 PM, Debasish Das <debasish.da...@gmail.com> >> wrote: >> > Does it make sense to have a user specific K or K is considered same >> > over >> > all users ? >> > >> > Intuitively the users who watches more movies should get a higher K than >> > the >> > others... >> > > > --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org For additional commands, e-mail: dev-h...@spark.apache.org
