[jira] Resolved: (MAHOUT-329) Implement some recommendation ideas used by the Netflix top teams to boost the recommenders package

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MAHOUT-329?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved MAHOUT-329.
------------------------------

      Assignee: Robin Anil
    Resolution: Later

Shelving this as GSoC projects are set and if something like this is taken up, it'd probably be in the form of a more specific proposal to implement an algorithm.

> Implement some recommendation ideas used by the Netflix top teams to boost the recommenders package
> ---------------------------------------------------------------------------------------------------
>
>                 Key: MAHOUT-329
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-329
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Collaborative Filtering
>            Reporter: Robin Anil
>            Assignee: Robin Anil
>
> A student with a good proposal 
> - should be free to work for Mahout in the summer and should be thrilled to work in this area :)
> - should be able to program in Java and be comfortable with datastructures and algorithms
> - must be clear about the algorithm or heuristic, how it works, its strengths, its weaknesses and possible tweaks.
> - must have a plan on making it a map/reduce implementation
> - should be able to show the improvement on the netflix data as compared to the baseline recommender package by the end of summer of code
> - must have clear deadlines and pace it evenly across the span of 3 months.
> - may have a background in these area.  Past work, thesis etc counts, so show it in the proposal clearly
> If you can do something extra it counts, but make sure the plan is reasonable within the specified time frame.

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