+1 for getting something like that in a future release of Mahout On Jul 19, 2013, at 10:02 PM, Sebastian Schelter <[email protected]> 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 <[email protected]> > >> 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 < >> [email protected]> 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 >>> >>> >>> Esta mensagem e seus anexos se dirigem exclusivamente ao seu >> destinatário, >>> podem conter informação privilegiada ou confidencial e são de uso >> exclusivo >>> da pessoa ou entidade de destino. Se não for destinatário desta mensagem, >>> fica notificado de que a leitura, utilização, divulgação e/ou cópia sem >>> autorização pode estar proibida em virtude da legislação vigente. Se >>> recebeu esta mensagem por engano, pedimos que nos o comunique >> imediatamente >>> por esta mesma via e, em seguida, apague-a. >>> >>> Este mensaje y sus adjuntos se dirigen exclusivamente a su destinatario, >>> puede contener información privilegiada o confidencial y es para uso >>> exclusivo de la persona o entidad de destino. Si no es usted él >>> destinatario indicado, queda notificado de que la lectura, utilización, >>> divulgación y/o copia sin autorización puede estar prohibida en virtud de >>> la legislación vigente. Si ha recibido este mensaje por error, le pedimos >>> que nos lo comunique inmediatamente por esta misma vía y proceda a su >>> exclusión. >>> >>> The information contained in this transmissión is privileged and >>> confidential information intended only for the use of the individual or >>> entity named above. If the reader of this message is not the intended >>> recipient, you are hereby notified that any dissemination, distribution >> or >>> copying of this communication is strictly prohibited. If you have >> received >>> this transmission in error, do not read it. Please immediately reply to >> the >>> sender that you have received this communication in error and then delete >>> it. >>> >>
