I think Ted's suggestion is you'll find Lucene will be _a lot faster_
for this task as you don't need all the other trappings of a DB.
On Jul 13, 2009, at 4:36 AM, Sean Owen wrote:
How does Lucene go from item-item links to recommendations? I'm
missing where the notion of user ratings, or even users, come into
play, or the strength of the association.
If the issue is really just storing the item-item links efficiently in
a way that isn't in memory, how about I cook up a JDBC-based
implementation? Seem more direct.
On Fri, Jul 10, 2009 at 11:56 PM, Ted Dunning<[email protected]>
wrote:
Yes.
One gotcha is that you generally have to limit document size a bit
to get
good performance. This is not a big deal because document
normalization
makes it hard for these documents to be retrieved in any case.
Also, these
are typically not good second order recommendations. First order
recommendations are the top-40 kinds of things and make poor
recommendations
for a bunch of reasons. Second order recommendations are those
that are
based on your history. They make much better recommendations.
On Fri, Jul 10, 2009 at 3:50 PM, Jason Rutherglen <
[email protected]> wrote:
Interesting. So we're creating the item-item matrix using one of
the Mahout
algorithms (like Taste?), then dumping it into Lucene.
--------------------------
Grant Ingersoll
http://www.lucidimagination.com/
Search the Lucene ecosystem (Lucene/Solr/Nutch/Mahout/Tika/Droids)
using Solr/Lucene:
http://www.lucidimagination.com/search
