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. > > >
