Thanks Sharma, does all similarity measures have this problem or only some specific similarity measures have?
On Mon, Aug 25, 2014 at 4:48 PM, Yash Sharma <[email protected]> wrote: > 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 <[email protected]> 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 <[email protected]> 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 <[email protected]> > > 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 <[email protected]> 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 > > >> > > > > >
