The latest user actions work just fine as the query against the last time you ran spark-itemsimilairty. Go to the Demo site https://guide.finderbots.com and run through the “trainer” those things you pick are instantly used to make recs. spark-itemsimilarity was not re-run. The only time you really have to re-run it is: 1) you have new items with interactions. You can only recommend what you trained with. 2) you have enough new user data to significantly change the model.
There is no incremental way to update the model (yet) but it can be rerun in a few minutes and as I said you get recs with realtime user history, even for new users not in the training data. On Mar 10, 2015, at 3:07 PM, Kevin Zhang <zhangyongji...@yahoo.com.INVALID> wrote: Hi, Does anybody have any idea about how to do incremental update for the item similarity? I mean how I can apply latest user action data for example today's data? Do I have to run it again for the entire dataset? Thanks, Kevin
