Hi Pat and Ted!
Yes I agree with about the rank and MAP. But in this case, that is a good
initial guess on the parameters *number of features* and *lambda*?
Where can I find the best article about cooccurrence recommender? And can
one use this approach for different types of data, e.g., ratings,
After having integrated several versions of the Mahout and Myrrix recommenders
at fairly large scale. I was interested in solving three problems that these
did not directly provide for:
1) realtime queries for recs using data not yet incorporated into the training
set. Myrrix allows this but
On Apr 6, 2014, at 2:48 AM, Niklas Ekvall niklas.ekv...@gmail.com wrote:
Hi Pat and Ted!
Yes I agree with about the rank and MAP. But in this case, that is a good
initial guess on the parameters *number of features* and *lambda*?
20 or 30 features depending on the variance in your data,
Thanks Pat!
I did find a book by Ted Dunning and Ellen Friedman (Practical Machine
Learning: Innovations in Recommendations) I guess I can us it to read more
about co-occurrence recommender or co-occurrence analysis.
Best, Niklas
2014-04-06 19:37 GMT+02:00 Pat Ferrel p...@occamsmachete.com:
It's quite good. Sri
On Sun, Apr 6, 2014 at 10:26 AM, Pat Ferrel p...@occamsmachete.com wrote:
After having integrated several versions of the Mahout and Myrrix
recommenders at fairly large scale. I was interested in solving three
problems that these did not directly provide for:
1)
The top 3 recommendations based on videos you liked are very good!
Nice job.
On 04/06/2014 07:26 PM, Pat Ferrel wrote:
After having integrated several versions of the Mahout and Myrrix recommenders
at fairly large scale. I was interested in solving three problems that these
did not directly
Pat, do you still want help putting this into a new mahout/examples, or work
out how to do the distribution via github pointer? There's an open bug for
that.
On Apr 6, 2014, at 1:13 PM, Sebastian Schelter s...@apache.org wrote:
The top 3 recommendations based on videos you liked are very
This can actually be simplified a bit by using ItemSimilarityJob to call
RowSimilarityJob.
Nice work overall.
On Sun, Apr 6, 2014 at 10:21 PM, Andrew Musselman
andrew.mussel...@gmail.com wrote:
Pat, do you still want help putting this into a new mahout/examples, or
work out how to do the
As I said below RSJ is actually all that is needed. But with the entire
recommender also integrated we can compare the two in the demo framework. For
instance one of the lines of recs on a video detail page (the top one) is the
actual RSJ output. When I get time, the recommend page will have a
Yes. It still needs some work—the github repo is hard to use without a better
explanation of Solr integration. It kind of leaves you most of the way there
without a clear idea of how to do the rest.
Also thinking about porting to Spark since all it really needs is RSJ and
Matrix Multiply, not
BTW this isn’t an attempt to show off, it’s an attempt to start a conversation
about fast scalable hybrid recommendations—content-based + collaborative
filtering recommenders.
Anyone who has started a business that uses a recommender has had to deal with
the ‘cold-start’ problem. No
Hi Gokhan,
I still could not build the Mahout out from the trunk.
Please see below for the error.
svn co http://svn.apache.org/repos/asf/mahout/trunk/ mahout-trunk
cd mahout-trunk
mvn clean install
On Mon, Apr 7, 2014 at 5:18 AM, Pat Ferrel p...@occamsmachete.com wrote:
Combining this kind of metadata with CF data has been important to the big
guys but elusive to the rest of us. And a recommender that seamlessly
integrates the different methods is rare. Solr + Mahout does it better than
On Mon, Apr 7, 2014 at 2:04 AM, Pat Ferrel p...@occamsmachete.com wrote:
As I said below RSJ is actually all that is needed. But with the entire
recommender also integrated we can compare the two in the demo framework.
For instance one of the lines of recs on a video detail page (the top one)
It looks like it works well.
And it is gorgeous as well.
Nice work. Very nice.
On Sun, Apr 6, 2014 at 8:59 PM, SriSatish Ambati srisat...@0xdata.comwrote:
It's quite good. Sri
On Sun, Apr 6, 2014 at 10:26 AM, Pat Ferrel p...@occamsmachete.com wrote:
After having integrated several
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