mahout-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Manuel Blechschmidt <Manuel.Blechschm...@gmx.de>
Subject Re: Purchase prediction
Date Tue, 03 Jan 2012 19:39:15 GMT
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

-- 
Manuel Blechschmidt
Dortustr. 57
14467 Potsdam
Mobil: 0173/6322621
Twitter: http://twitter.com/Manuel_B


Mime
  • Unnamed multipart/alternative (inline, None, 0 bytes)
View raw message