[GitHub] flink pull request #2542: [FLINK-4613] [ml] Extend ALS to handle implicit fe...

[gaborhermann <gi...@git.apache.org>]

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.


---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastructure@apache.org or file a JIRA ticket
with INFRA.
---