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Date: Mon, 20 Jun 2011 09:11:47 +0000 (UTC)
From: "Sebastian Schelter (JIRA)" <jira@apache.org>
To: dev@mahout.apache.org
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Subject: [jira] [Commented] (MAHOUT-737) Implicit Alternating Least Squares
 SVD
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    [ https://issues.apache.org/jira/browse/MAHOUT-737?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13051863#comment-13051863 ] 

Sebastian Schelter commented on MAHOUT-737:
-------------------------------------------

Do you think it would be possible to refactor this code to implement org.apache.mahout.cf.taste.impl.recommender.svd.Factorizer ? That would be great because then we could easily drop it into the existing (very lean) SVDRecommender. 

> Implicit Alternating Least Squares SVD
> --------------------------------------
>
>                 Key: MAHOUT-737
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-737
>             Project: Mahout
>          Issue Type: Improvement
>            Reporter: Tamas Jambor
>         Attachments: MAHOUT-737.patch
>
>
> I am sharing this Java implementation of mine that is based on the paper - Collaborative Filtering with Implicit Datasets. The implementation is multi-treading and can be easily extended to use it on Hadoop. In fact this approach would possibly work with non-implicit datasets, but further testing is needed. The algorithm is tried and tested on an implicit TV-viewing dataset, and the performance was pretty good (details to follow). 

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