Actually, making this user based is a really good thing because you get recommendations from one session to the next. These may be much more valuable for cross-sell than things in the same order.
On Thu, Apr 11, 2013 at 12:50 PM, Sean Owen <[email protected]> wrote: > 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 <[email protected]> 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" <[email protected]> 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 <[email protected]> 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 >
