yes The demo https://guide.finderbots.com has a “trainer” and returns recs immediately after you indicate some preferences (using the trainer or just browsing and hitting thumbs up). It is not implemented in the way we’d want for a general recommender though and that is what I’d like to do.
On Sep 9, 2014, at 7:36 AM, Peng Zhang <[email protected]> wrote: That will be a great feature. Currently if the offline brach job will run hours to update the recs. Can this api update recs in realtime? i.e. can we update the recs for a user based on her last few behaviors 5 minutes ago? On Sep 9, 2014, at 10:28 PM, Pat Ferrel <[email protected]> wrote: > Now that we have the basis of several significant improvements to Mahout’s > recommender it seems like we need to go the last step and provide a service. > Without this it is left to the user to do a lot of integration making the > current next gen somewhat incomplete. > > Using the Hadoop mapreduce code you can get all recs for all people using > collaborative filtering data or you can use the in-memory single machine > recommender if you have a small dataset. > > The next generation would require Solr or Elasticsearch so why not go the > extra step and provide a recommender API on top? At very least it would give > users a single machine API they can call, analogous to the in-memory > recommender of Mahout 0.9. But it would also be indefinitely scalable. > > Is anyone interested in discussing this here?
