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From Manuel Blechschmidt <>
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.

Further you could also use the hidden markov model to predict probabilities of next purchases.

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

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:

If you have further questions feel free to ask.


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

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