Ted - I read your blog post and the paper you refer to/wrote and several other authors that sited your paper, but I am having trouble with the overall approach for putting all the pieces together. Would you mind giving me a nudge with the intuition? I realize you have been doing this for almost 30 years; however, I am just a cave man... Thank you.
> From: ted.dunn...@gmail.com > Date: Fri, 10 Jan 2014 20:09:38 -0800 > Subject: Re: Item recommendation w/o users or preferences > To: user@mahout.apache.org > > This talk of support and overlap smacks of very poor coocccurrence analysis. > > See http://tdunning.blogspot.com/2008/03/surprise-and-coincidence.html for > a better option. > > > On Fri, Jan 10, 2014 at 8:05 PM, Tim Smith <timsmit...@hotmail.com> wrote: > > > 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: rachel.ows...@safeway.com > > > To: user@mahout.apache.org > > > 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 [timsmit...@hotmail.com] > > > Sent: Friday, January 10, 2014 7:39 PM > > > To: user@mahout.apache.org > > > 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: nimar...@pssd.com > > > > To: user@mahout.apache.org > > > > 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.htmlto > > get a feel for what Mahout does in the recommendation space. > > > > > > > > -----Original Message----- > > > > From: Tim Smith [mailto:timsmit...@hotmail.com] > > > > Sent: Friday, January 10, 2014 8:27 PM > > > > To: user@mahout.apache.org > > > > 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. > > > > > > > > ============================================================================== > > > > > > >
