Hi Manuel,
Thank you for the reference. I am just testing the waters for now,
trying to find out what's available. I should have a usecase in a
couple of weeks. I'll reread what's said here then, and continue the
thread.
Cheers,
Anatoliy
On 11/29/2011 03:21 PM, Manuel Blechschmidt wrote:
Hello Anatoliy,
On 29.11.2011, at 10:32, Anatoliy Kats wrote:
Hi,
There was a conversation some time ago about incorporating time dependency for
preferences: http://thread.gmane.org/gmane.comp.apache.mahout.user/2951
Has there been any more discussion about this? Has anything been checked into
Mahout? Is anyone working on it? I might be able to pitch in.
I am currently working with a data set which has highly seasonal data. Actually
it is the sales data of a merchant selling tea and spices.
I benchmarked the different recommenders against it:
http://thread.gmane.org/gmane.comp.apache.mahout.user/10433
As far as I know there are currently no recommenders that incorporate time or
seasons. The DataModel supports it but it isn't used.
I would guess that identifying seasonal patterns could enhance my
recommendations a lot.
I scanned the following paper:
Improving E-Commerce Recommender Systems by the Identification of Seasonal
Products
http://www.aaai.org/Papers/Workshops/2007/WS-07-08/WS07-08-011.pdf
Actually I think that what the paper is doing is not that advanced.
I currently try to identify seasonal products with R. I am playing around with
seasonal ARIMA models (http://www.duke.edu/~rnau/seasarim.htm
http://cran.r-project.org/web/packages/forecast/forecast.pdf). If I have a
working solution with R I might implement it in Mahout.
What is your use case? Do you already have a data set?
Thanks,
Anatoliy
/Manuel
