GitHub user gaborhermann opened a pull request: https://github.com/apache/flink/pull/2542
[FLINK-4613] Extend ALS to handle implicit feedback datasets This extension of the ALS algorithm changes some parts of the code if `implicitPrefs` flag is set to true. Mainly the local parts parts are changed: the `Xt * X` computation takes into consideration the confidence, thus computing `Xt * (C - I) * X` instead (see the paper by Hu et al. for details). The `Xt * X` matrix is precomputed and broadcasted, and that is the only thing that affects distributed execution. Note, that we use a temporary directory in the test, because there would not be enough memory segments to perform a hash join for prediction. I assume that memory segments are not freed up after the training if no temporary directory is set, but I did not investigate the issue as using a tempdir is a simple workaround. You can merge this pull request into a Git repository by running: $ git pull https://github.com/gaborhermann/flink ials Alternatively you can review and apply these changes as the patch at: https://github.com/apache/flink/pull/2542.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #2542 ---- commit 84d338b11f77b20fa1825029f8ca847a40eb4673 Author: Gábor Hermann <c...@gaborhermann.com> Date: 2016-09-12T09:47:40Z [FLINK-4613] Compute XtX for IALS & test, docs commit 8e7c0d67a6f0390f03765fcdc9e03f3c391807cd Author: jfeher <feh...@gmail.com> Date: 2016-09-12T09:57:44Z [FLINK-4613] Extend ALS for implicit case XtX matrix precomputation is not yet done. ---- --- 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 infrastruct...@apache.org or file a JIRA ticket with INFRA. ---