Pearson Coefficient Similarity does not go very well with small datasets with less similarities - and removes those from output. Since you are using co-occurrence similarity this is not the case.
On Mon, Aug 25, 2014 at 2:11 PM, Peng Zhang <pzhang.x...@gmail.com> wrote: > If there are no suitable recommendations for a user, the output will not > contain any records related to this user. > > > Peng Zhang > > > On Aug 25, 2014, at 4:38 PM, Wei Li <wei.le...@gmail.com> wrote: > > > thanks Peng's answers. Yes, I know this case, but RecommenderJob does not > > output these records? > > > > > > On Mon, Aug 25, 2014 at 3:37 PM, Peng Zhang <pzhang.x...@gmail.com> > wrote: > > > >> If an item is not similar to anyone else, and a user only connects with > >> this item, this user doesnt get any recommended items. > >> > >> This is just one example. > >> > >> Peng Zhang > >> > >> -- > >> Sent from my iPhone > >> > >>> On Aug 25, 2014, at 2:22 PM, Wei Li <wei.le...@gmail.com> wrote: > >>> > >>> Hi Mahout users: > >>> > >>> We have tried the item-based CF recommender with a user_id, item_id, > >>> rating data. while the recommendation output is less than our expected, > >> for > >>> example, if we have 1000 users, the output should have 1000 records, > one > >>> for each user, right? > >>> > >>> Best > >>> Wei > >> > >
