You can try treating your orders as the 'users'. Then just compute item-item similarities per usual.
On Thu, Apr 11, 2013 at 7:59 PM, Billy <b...@ntlworld.com> wrote: > Thanks for replying, > > > I don't have users, well I do :-) but in this case it should not influence > the recommendations > > , > these need to be based on the relationship between > " > items ordered with other items > in the 'same order' > ". > > E.g. If item #1 has been order with item #4 > > [ > 22 > ] > times and item #1 has been order with item #9 > [ > 57 > ] > times then > if I added item #1 to my order > these would both be recommended > but item #9 would be recommended above item #4 purely based on the fact that > the relationship between item #1 and item #9 is greater than the > relationship with item #4. > > What I don't want is; if a user ordered items #A, #B, #C separately > 'at some point in their order history' then recommen > d #A and #C to other users who order #B ... I still don't want this if the > items are similar and/or the users similar. > > Cheers > > Billy > > > > On 11 Apr 2013 18:28, "Sean Owen" <sro...@gmail.com> wrote: >> >> This sounds like just a most-similar-items problem. That's good news >> because that's simpler. The only question is how you want to compute >> item-item similarities. That could be based on user-item interactions. >> If you're on Hadoop, try the RowSimilarityJob (where you will need >> rows to be items, columns the users). >> >> On Thu, Apr 11, 2013 at 6:11 PM, Billy <b...@ntlworld.com> wrote: >> > I am very new to Mahout and currently just ready up to chapter 5 of >> > 'MIA' >> > but after reading about the various User centric and Item centric >> > recommenders they all seem to still need a userId so still unsure if >> > Mahout >> > can help with a fairly common recommendation. >> > >> > My requirement is to produce 'n' item recommendations based on a chosen >> > item. >> > >> > E.g. "if I've added item #1 to my order then based on all the >> > other items; in all the other orders for this site, what are the >> > likely items that I may also want add to my order based; on the item to >> > item relationship in the history of orders of this site?" >> > >> > Most probably using the most popular relationship between the item I >> > have >> > chosen and all the items in all the other orders. >> > >> > My data is not 'user' specific; and I don't think it should be, but more >> > like order specific as its the pattern of items in each order that >> > should >> > determine the recommendation. >> > >> > I have no preference values so merely boolean preferences will be used. >> > >> > If Mahout can perform these calculations then how must I present the >> > data? >> > >> > Will I need to shape the data in some way to feed into Mahout (currently >> > versed in using Hadoop via Aws Emr using Java) >> > >> > Thanks for the advice in advance, >> > >> > Billy
