I have some Hadoop code mostly ready to go for Taste. The first thing to do is let you generate recommendations for all your users via Hadoop. Unfortunately none of the recommenders truly parallelize in the way that MapReduce needs it to -- you need all data to compute any recommendation really -- but you can at least get paralellization out of this. You can use the framework to run n recommenders, each computing 1/nth of all recommendations.
The next application is specific to slope-one. Computing the item-item diffs is exactly the kind of thing that MapReduce is good for, so, writing a Hadoop job to do this seems like a no-brainer. On Tue, Apr 29, 2008 at 11:14 AM, Goel, Ankur <[EMAIL PROTECTED]> wrote: > Hi Folks, > What's the status of hadoopifying Taste on Mahout ? > What's been done and what is in progress/pending ? > > I am looking using a scalable version of Taste for my project. > So basically trying to figure out what's already done and where > I can pitch in. > > Thanks > -Ankur >
