Very awesome, thank you! I am twisting the support knob right now! Sequential analysis in the sense that I A/B test my recommendations and feed the conversion rates back into my next set of recommendations or something else?
> From: [email protected] > To: [email protected] > Subject: RE: Item recommendation w/o users or preferences > Date: Sat, 11 Jan 2014 03:53:41 +0000 > > My mail crossed with yours. Try market basket analysis and sequential > analysis. With the market basket analysis, there are often a lot of frequent > basket combinations that are not that useful. You may want to lower the > support to get some more infrequent combinations, but up the confidence > level. > > Good luck. > > Rachel > ________________________________________ > From: Tim Smith [[email protected]] > Sent: Friday, January 10, 2014 7:39 PM > To: [email protected] > Subject: RE: Item recommendation w/o users or preferences > > Yes, thank you - read through it and several of the item and user > recommendation examples. The objective is to recommend based on the current > basket - given no users/preferences (but I do have a history of transactions) > - I have been able to leverage the item mining algorithm to calculate support > and confidence values. When I use a support threshold of 10% and group by > product and sort descending on confidence I am left we a ranking of item > combos. Basically a top N list by item that I would use to drive the > recommendations. In the actual use case, the requirement is not to recommend > a product every time, rather the most likely products based on a given basket > - with my arbitrary thresholds, I would expect to exclude some baskets. > > > From: [email protected] > > To: [email protected] > > Subject: RE: Item recommendation w/o users or preferences > > Date: Sat, 11 Jan 2014 03:08:30 +0000 > > > > I think the key question is what is the desired outcome? If you don't have > > users (customers) for which you'd like to generate recommendations that > > really handcuffs you from a recommendation standpoint. > > > > I'd recommend starting with a read through this: > > http://mahout.apache.org/users/recommender/recommender-first-timer-faq.html > > to get a feel for what Mahout does in the recommendation space. > > > > -----Original Message----- > > From: Tim Smith [mailto:[email protected]] > > Sent: Friday, January 10, 2014 8:27 PM > > To: [email protected] > > Subject: Item recommendation w/o users or preferences > > > > Say I have a retail organization that doesn't sell a diverse set of > > products, eg 2000, but has many small transactions. Also say that I don't > > have any user or preference information. Is it reasonable to use pattern > > mining (market baskets) and recommend items based on a set of thresholds > > for support, confidence, and lift? If not, what are my options? > > > > "Email Firewall" made the following annotations. > ------------------------------------------------------------------------------ > > Warning: > All e-mail sent to this address will be received by the corporate e-mail > system, and is subject to archival and review by someone other than the > recipient. This e-mail may contain proprietary information and is intended > only for the use of the intended recipient(s). If the reader of this message > is not the intended recipient(s), you are notified that you have received > this message in error and that any review, dissemination, distribution or > copying of this message is strictly prohibited. If you have received this > message in error, please notify the sender immediately. > > ============================================================================== >
