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From B Lyon <bradfl...@gmail.com>
Subject Re: Setting up a recommender
Date Fri, 19 Jul 2013 20:08:32 GMT
+1 as well.  Sounds fun.

On Fri, Jul 19, 2013 at 4:06 PM, Dominik Hübner <contact@dhuebner.com>wrote:

> +1 for getting something like that in a future release of Mahout
>
> On Jul 19, 2013, at 10:02 PM, Sebastian Schelter <ssc@apache.org> wrote:
>
> > It would be awesome if we could get a nice, easily deployable
> > implementation of that approach into Mahout before 1.0
> >
> >
> > 2013/7/19 Ted Dunning <ted.dunning@gmail.com>
> >
> >> My current advice is to use Hadoop (if necessary) to build a sparse
> >> item-item matrix based on each kind of behavior you have and then drop
> >> those similarities into a search engine to deliver the actual
> >> recommendations.  This allows lots of flexibility in terms of which
> kinds
> >> of inputs you use for the recommendation and lets you blend
> recommendations
> >> with search and geo-location.
> >>
> >>
> >> On Fri, Jul 19, 2013 at 12:33 PM, Helder Martins <
> >> helder.garay@corp.terra.com.br> wrote:
> >>
> >>> Hi,
> >>> I'm a dev working for a web portal in Brazil and I'm particularly
> >>> interested in building a item-based collaborative filtering recommender
> >>> for our database of news articles.
> >>> After some coding, I was able to get some recommendations using a
> >>> GenericItemBasedRecommender, a CassandraDataModel and some custom
> >>> classes that store item similarities and migrated item IDs into
> >>> Cassandra. But know I'm in doubt of what is normally done with this
> >>> recommender: Should I run this as a daemon, cache the recommendations
> >>> into memory and set up a web service to consult it online? Should I pre
> >>> process these recommendations for each recent user and store it
> >>> somewhere? My first idea was storing all these recs back into
> Cassandra,
> >>> but looking into some classes it seems to me that the norm is to read
> >>> the input data and store the output always using files. Is this a
> common
> >>> practice that benefits from HDFS?
> >>> My use case here is something around 70k recommendations requests per
> >>> second.
> >>>
> >>> Thanks in advance,
> >>>
> >>> --
> >>>
> >>> Atenciosamente
> >>> Helder Martins
> >>> Arquitetura do Portal e Sistemas de Backend
> >>> +55 (51) 3284-4475
> >>> Terra
> >>>
> >>>
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>


-- 
BF Lyon
http://www.nowherenearithaca.com

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