Re: How to use Mahout's model recommender in online experiments ?

[Trevor Grant <tr...@gmail.com>]

Sorry for late response on this.

Might be worth checking out:
https://github.com/rawkintrevo/fsf17-twitter-recos

This is the corresponding talk. (relevant part starts at about 18:30)
https://youtu.be/h3j1JdtbhOI


Trevor Grant
Data Scientist
https://github.com/rawkintrevo
http://stackexchange.com/users/3002022/rawkintrevo
http://trevorgrant.org

*"Fortunate is he, who is able to know the causes of things."  -Virgil*


On Thu, May 25, 2017 at 9:51 AM, Alessandro Dias <al...@gmail.com>
wrote:

> Hi,
>
> I learned in this site below how to use ALS facorization algoritm to made
> recommendations in Mahout Framework.
>
> https://mahout.apache.org/users/recommender/intro-als-hadoop.html
>
> From this:
> - we inform a file with the rating (user, item, rating), in my case I have
>  implicit ratings;
> - then get the files of the two latent matrices generated; and
> - finally we insert theses files in a recommender engine that generate a
> file with the list of recomendations for each user.
>
>
> I think that it is made for big e-commerce companies periodically. (the
> model and recomendations is built periodically in an offline moments)
>
>
>
> At my case, I'm going to do an online experiment of recommender. This model
> recommender will be the control group.
>
> I have a file with ratings of a set of old users and I will have a set of
> new users on this online experiment. The old users will not participate
> this experiment.
>
> Theses new users will use the recommener system for 2 weeks in the online
> experiment.
>
>
>
> >> How to use ALSWRFactorizer recommender (non-hadoop) from Mahout in
> online experiments ?
>
> I'd like to build a model once and use it to the new users...
>
> >> Will I have to run the algoritm (re-buid the model) in each
> recomendation made during the online experiment ?
>
> Thanks and Regards,
>
> Alessandro Dias
>