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From Mridul Kapoor <>
Subject Re: Generating similarity file(s) for item recommender?
Date Tue, 03 Jul 2012 12:01:35 GMT
> I'm thinking the session ID (in the cookie) would be used as the user ID.
> The events
> are tied to product IDs, so these would be used in generating the
> preferences.

I guess if you consider product-preference on a per session-basis (i.e.
only items for which a user expresses preference for, in a single session,
are similar to each other, in some way or the other). This way, you would
be considering the session-ids as dummy user-ids, which I think should be

I'd like to eventually run this on Hadoop, but it'd also be nice to know if
> there is a way to do this locally, while developing the app, maybe using a
> smaller
> dataset?

Yes just writing a small offline recommender (made to run on a local
machine) should do; you could take a subset of the data, use a
FileDataModel, then do something like

LongPrimitiveIterator itemIDs = dataModel.getItemIDs();

and iterate over these; getting _n_ recommended items for each, storing
them somewhere (and maybe use this evaluating the recommender somehow)


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