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From Pat Ferrel <...@occamsmachete.com>
Subject Re: Knowing the probability of purchase
Date Tue, 25 Apr 2017 18:43:23 GMT
I read this dissertation and came away wondering why it was important. The job of a recommender
is not to predict what you *will* buy but rather what you would like to buy if you knew about
it—in other words it determines your taste or preferences and finds item that match. This
tends to increase conversions (sales for E-Commerce). A predictor may only predict the inevitable
and lead to 0 lift in conversions.


On Apr 24, 2017, at 1:10 AM, Vaghawan Ojha <vaghawan781@gmail.com> wrote:

Hi, 

I was following a research paper regarding the probability of a user buying a particular item
recommended by the recommendation system. It's here, if you want to checkout as well http://www.kecl.ntt.co.jp/as/members/iwata/doctor.pdf
<http://www.kecl.ntt.co.jp/as/members/iwata/doctor.pdf> 

I was wondering if there is a way or anybody has done with the current templates of PIO, the
calculation of the probability of a user buying an item. 

I think this should be possible with current templates as well, I am just wondering, if anybody
could provide me a brief way to do that, or any documentation of the algorithms that could
be used. 


Thanks 

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