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From Ted Dunning <ted.dunn...@gmail.com>
Subject Re: Realtime update of similarity matrices
Date Fri, 19 Jun 2015 22:46:28 GMT
The standard approach is to re-run the off-line learning.

It is possible, though not yet supported in Mahout tools, to do real-time
updates.

See here for some details:
https://www.mapr.com/resources/videos/fully-real-time-recommendation-%E2%80%93-ted-dunning-sf-data-mining



On Fri, Jun 19, 2015 at 2:35 AM, James Donnelly <jamesjdonnelly@gmail.com>
wrote:

> Hi,
>
> First of all, a big thanks to Ted and Pat, and all the authors and
> developers around Mahout.
>
> I'm putting together an eCommerce recommendation framework, and have a
> couple of questions from using the latest tools in Mahout 1.0.
>
> I've seen it hinted by Pat that real-time updates (incremental learning)
> are made possible with the latest Mahout tools here:
>
>
> http://occamsmachete.com/ml/2014/10/07/creating-a-unified-recommender-with-mahout-and-a-search-engine/
>
> But once I have gone through the first phase of data processing, I'm not
> clear on the basic direction for maintaining the generated data, e.g with
> added products and incremental user behaviour data.
>
> The only way I can see is to update my input data,  then re-run the entire
> process of generating the similarity matrices using the itemSimilarity and
> rowSImilarity jobs.  Is there a better way?
>
> James
>

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