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From Sebastian Schelter <...@apache.org>
Subject Re: Purchase prediction
Date Tue, 03 Jan 2012 21:33:12 GMT
A very simple approach would be to use an item-based recommender with a
precomputed model (that might be a day old) and simply use the items
most similar to the latest items the user preferred as recommendations.

These recommendations can be found in "real time" where "real time"
means that a user fills a shopping cart and his recommendations are
immediately updated after each item he adds.

--sebastian

On 03.01.2012 20:59, Mike Spreitzer wrote:
> I suspect the original request was concerned with --- and I, on my own, am 
> concerned with --- a scenario in which it is desired to be able to quickly 
> make predictions based on very recent data.  Thus, approaches that 
> occasionally take a lot of time to build a model are non-solutions.  Are 
> there solutions for my scenario in what you mentioned, or elsewhere?
> 
> Thanks,
> Mike
> 
> 
> 
> From:   Manuel Blechschmidt <Manuel.Blechschmidt@gmx.de>
> To:     user@mahout.apache.org
> Date:   01/03/2012 02:40 PM
> Subject:        Re: Purchase prediction
> 
> 
> 
> Hello Nishan,
> you can use the recommender approaches with the boolean reference model.
> 
> You can use IRStatistics (Precision, Recall, F-Measure) to benchmark your 
> results.
> https://cwiki.apache.org/confluence/display/MAHOUT/Recommender+Documentation
> 
> 
> Further you could also use the hidden markov model to predict 
> probabilities of next purchases.
> http://isabel-drost.de/hadoop/slides/HMM.pdf
> https://issues.apache.org/jira/browse/MAHOUT-396
> 
> There are some papers describing how to combine some of these methods:
> 
> Rendle. et. al presented a paper using a combination of both:
> Factorizing Personalized Markov Chains for Next-Basket Recommendation
> http://www.ismll.uni-hildesheim.de/pub/pdfs/RendleFreudenthaler2010-FPMC.pdf
> 
> 
> In my opinion some seasonal models could also help to better predict next 
> purchases.
> 
> There is currently an resolved enhancement request for 0.6 making 
> evaluation for a use case like yours better:
>  https://issues.apache.org/jira/browse/MAHOUT-906
> 
> If you have further questions feel free to ask.
> 
> /Manuel
> 
> On 03.01.2012, at 19:02, Nishant Chandra wrote:
> 
>> Hi,
>>
>> I am trying to predict shopper purchase and non-purchase intention in
>> E-Commerce context. I am more interested in finding the later.
>> A near-real time approach will be great. So given a sequence of pages
>> a shopper views, I would like the algorithm to predict the intention.
>>
>> Any algorithms in Mahout or otherwise that can help?
>>
>> Thanks,
>> Nishant
> 


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