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https://issues.apache.org/jira/browse/SPARK-20903?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16026669#comment-16026669
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Apache Spark commented on SPARK-20903:
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User 'shubhamchopra' has created a pull request for this issue:
https://github.com/apache/spark/pull/18123
> Word2Vec Skip-Gram + Negative Sampling
> --------------------------------------
>
> Key: SPARK-20903
> URL: https://issues.apache.org/jira/browse/SPARK-20903
> Project: Spark
> Issue Type: Sub-task
> Components: ML, MLlib
> Affects Versions: 2.1.1
> Reporter: Shubham Chopra
>
> SkipGram + Negative Sampling is shown to be comparative or out-performing the
> hierarchical softmax based approach currently implemented with Spark. Since
> word2vec is largely a pre-processing step, the performance often can depend
> on the application it is being used for, and the corpus it is estimated on.
> These implementation give users the choice of picking one that works best for
> their use-case.
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