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https://issues.apache.org/jira/browse/SPARK-12153?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved SPARK-12153.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 10152
[https://github.com/apache/spark/pull/10152]
> Word2Vec uses a fixed length for sentences which is not reasonable for
> reality, and similarity functions and fields are not accessible
> --------------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-12153
> URL: https://issues.apache.org/jira/browse/SPARK-12153
> Project: Spark
> Issue Type: Bug
> Components: MLlib
> Affects Versions: 1.5.2
> Reporter: YongGang Cao
> Assignee: YongGang Cao
> Priority: Minor
> Fix For: 2.0.0
>
>
> sentence boundary matters for sliding window, we shouldn't train model from a
> window across sentences.
> the current 1000 word as a hard split for sentences doesn't really make sense
> which is not consistent with both original c version or other implementation
> like deeplearning4j etc.
> the max sentence length is fixed and not tunable. Made it tunable as well.
> I made changes to address above issues.
> here is the pull request: https://github.com/apache/spark/pull/10152
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