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https://issues.apache.org/jira/browse/MAHOUT-1430?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sebastian Schelter resolved MAHOUT-1430.
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Resolution: Won't Fix
GSoC is now running.
> GSOC 2014 Proposal of implementing a new recommender
> ----------------------------------------------------
>
> Key: MAHOUT-1430
> URL: https://issues.apache.org/jira/browse/MAHOUT-1430
> Project: Mahout
> Issue Type: New Feature
> Components: Collaborative Filtering
> Reporter: Mihai Pitu
> Labels: features, gsoc, mentor
>
> I would like to ask about possibilities of implementing Sparse Linear Methods
> (SLIM) recommender in Mahout during GSOC 2014.
> The SLIM algorithm generates efficient recommendations and its performance is
> shown in the original paper
> (http://glaros.dtc.umn.edu/gkhome/fetch/papers/SLIM2011icdm.pdf). The study
> demonstrates that SLIM outperforms traditional algorithms (such as itemkNN,
> userkNN, SVD or Matrix Factorization approaches) on various data-sets in
> terms of run-time and recommendation quality. The algorithm can be
> paralellized and Map-Reduce can help us achieve that.
> I am aware of real world systems that are using SLIM as a recommendation
> engine (e.g. Mendeley: http://www.slideshare.net/MarkLevy/efficient-slides)
> and I think it represents the state-of-the-art in collaborative filtering
> right now.
> Would this be an interesting addition to Mahout and is somebody interested in
> mentoring this at Google Summer of Code 2014?
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