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From gaborhermann <...@git.apache.org>
Subject [GitHub] flink pull request #2542: [FLINK-4613] [ml] Extend ALS to handle implicit fe...
Date Thu, 29 Sep 2016 11:04:08 GMT
Github user gaborhermann commented on a diff in the pull request:

    https://github.com/apache/flink/pull/2542#discussion_r81112516
  
    --- Diff: docs/dev/libs/ml/als.md ---
    @@ -49,6 +49,21 @@ By applying this step alternately to the matrices $U$ and $V$, we can
iterativel
     
     The matrix $R$ is given in its sparse representation as a tuple of $(i, j, r)$ where
$i$ denotes the row index, $j$ the column index and $r$ is the matrix value at position $(i,j)$.
     
    +An alternative model can be used for _implicit feedback_ datasets.
    +These datasets only contain implicit feedback from the user
    +in contrast to datasets with explicit feedback like movie ratings.
    +For example users watch videos on a website and the website monitors which user
    +viewed which video, so the users only provide their preference implicitly.
    +In these cases the feedback should not be treated as a
    +rating, but rather an evidence that the user prefers that item.
    +Thus, for implicit feedback datasets there is a slightly different
    +minimalization problem to solve (see [Hu et al.](http://dx.doi.org/10.1109/ICDM.2008.22)
for details).
    --- End diff --
    
    Thanks. Changed.


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