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From Helder Martins <helder.ga...@corp.terra.com.br>
Subject Setting up a recommender
Date Fri, 19 Jul 2013 19:33:55 GMT
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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