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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2015/12/05 23:13:10 UTC

[jira] [Assigned] (SPARK-12153) Word2Vec uses a fixed length for sentences which is not reasonable for reality, and similarity functions and fields are not accessible

     [ https://issues.apache.org/jira/browse/SPARK-12153?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-12153:
------------------------------------

    Assignee:     (was: Apache Spark)

> 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: Improvement
>          Components: MLlib
>    Affects Versions: 1.5.2
>            Reporter: YongGang Cao
>            Priority: Minor
>              Labels: patch
>
> sentence boundary matters for sliding window, we shouldn't train model from a window across sentences. the current 100 word as a hard split for sentences doesn't really make sense.
> And the cosinesimilarity functions is private which is useless for caller. 
> we may need to access the vocabulary and wordindex table as well, those need getters
> I made changes to address above issues.
> here is the pull request: https://github.com/apache/spark/pull/10152



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